\documentclass[12pt,a4paper,dvips]{article} %\input{lowe_format} \usepackage{graphicx,epsfig} \usepackage{hhline} \usepackage{amsmath,amssymb} \usepackage{times} %\usepackage[varg]{txfonts} \DeclareMathAlphabet{\mathbold}{OML}{txr}{b}{it} \usepackage{array,multirow,dcolumn} \usepackage[mathlines,displaymath]{lineno} \usepackage{rotating} % we use natbib instead of cite to work with hyperref %\usepackage{cite} \usepackage[numbers,square,comma,sort&compress]{natbib} \usepackage{hypernat} \usepackage{textcomp} %\bibliographystyle{unsrt} %\bibliographystyle{unsrtnat} %\bibliographystyle{apsrev} \bibliographystyle{lowe} %\bibliographystyle{JHEP-2} %\usepackage{caption2} %\renewcommand{\captionfont}{\normalfont\slshape\normalsize} %\renewcommand{\captionlabelfont}{\normalfont\bfseries\normalsize} \newcommand{\tablecaption}{% %\setlength{\abovecaptionskip}{0pt} %\setlength{\belowcaptionskip}{10pt} \caption} \newcommand{\D}{\displaystyle} \newcolumntype{.}{D{.}{.}{-1}} 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\renewcommand{\topfraction}{1.0} \renewcommand{\bottomfraction}{1.0} \renewcommand{\textfraction}{0.0} % \renewcommand{\arraystretch}{1.2} \newlength{\dinwidth} \newlength{\dinmargin} \setlength{\dinwidth}{21.0cm} \textheight24cm \textwidth16.0cm \setlength{\dinmargin}{\dinwidth} \setlength{\unitlength}{1mm} \addtolength{\dinmargin}{-\textwidth} \setlength{\dinmargin}{0.5\dinmargin} \oddsidemargin -1.0in \addtolength{\oddsidemargin}{\dinmargin} \setlength{\evensidemargin}{\oddsidemargin} \setlength{\marginparwidth}{0.9\dinmargin} \marginparsep 8pt \marginparpush 5pt \topmargin -42pt \headheight 12pt \headsep 30pt \footskip 32pt \parskip 3mm plus 2mm minus 2mm % % Definitions for F2 low Q2 paper % \newcommand{\empz}{\mbox{$E$$-$$P_z$}} \newcommand{\qqe}{\mbox{$Q^2_e$}} \newcommand{\qqs}{\mbox{$Q^2_\Sigma$}} \newcommand{\ys}{\mbox{$y_\Sigma$}} \newcommand{\xs}{\mbox{$x_\Sigma$}} \newcommand{\ee}{\mbox{$E_e^{\prime}$}} \newcommand{\thetae}{\mbox{$\theta_e$}} \newcommand{\thetah}{\mbox{$\theta_h$}} \newcommand{\gp}{\mbox{$\gamma p$}} \newcommand{\pt}{\mbox{$P_\perp$}} \newcommand{\piz}{\mbox{$\pi^0$}} \newcommand{\Pth}{\mbox{$P_{\perp}^h$}} \newcommand{\electron}{\mbox{positron}} \newcommand{\Fig}{\mbox{figure}} \newcommand{\Tab}{\mbox{table}} \newcommand{\Eq}{\mbox{equation}} \newcommand{\Sec}{\mbox{section}} \newcommand{\FFig}{\mbox{Figure}} \newcommand{\TTab}{\mbox{Table}} \newcommand{\EEq}{\mbox{Equation}} \newcommand{\SSec}{\mbox{Section}} \def\ytrans{0.56} \newcommand{\Figs}{\mbox{figures}} \newcommand{\Tabs}{\mbox{tables}} \newcommand{\Eqs}{\mbox{equations}} \newcommand{\Secs}{\mbox{sections}} \newcommand{\FFigs}{\mbox{Figures}} \newcommand{\TTabs}{\mbox{Tables}} \newcommand{\EEqs}{\mbox{Equations}} \newcommand{\SSecs}{\mbox{Sections}} \renewcommand{\perp}{{\rm T}} \newcommand{\MB}{\mbox{NVX}} \newcommand{\SVX}{\mbox{SVX}} \newcommand{\thetamaxsvx}{178^{\circ}} \newcommand{\thetamaxmb}{176.5^{\circ}} \newcommand{\permil}{\textperthousand} \def\cov{\mathop{\rm cov}\nolimits} \def\dof{\mathop{n_{\rm dof}}\nolimits} \def\DeltaM{\mathop{ w_{i,e}}\nolimits} \def\DeltaMK{\mathop{ w_{k,e}}\nolimits} \newcommand\T{\rule{0pt}{2.3ex}} \newcommand\B{\rule[-1.ex]{0pt}{0pt}} \newcommand\hqcjc{medium $Q^2$ CJC $E_p=920$~GeV} \newcommand\lqbst{low $Q^2$ BST $E_p=920$~GeV} \newcommand\ler{\mbox{$E_p=460$~GeV}} \newcommand\mer{\mbox{ $E_p=575$~GeV}} \newcommand\lermer{$E_p=460$~GeV and $E_p=575$~GeV} \newcommand\ner{$E_p=920$~GeV} \newcommand\Hqcjc{Medium $Q^2$ CJC $E_p=920$~GeV} \newcommand\Lqbst{Low $Q^2$ BST $E_p=920$~GeV} \newcommand\Ler{\mbox{$E_p=460$~GeV}} \newcommand\Mer{\mbox{$E_p=575$~GeV}} \newcommand\Lermer{$E_p=460$~GeV and $E_p=575$~GeV} \newcommand\lumicjcplus{\mbox{$53.2$}} \newcommand\lumicjcminus{\mbox{$44.4$}} \newcommand\lumibstplus{\mbox{$3.4$}} \newcommand\lumibstminus{\mbox{$2.5$}} \newcommand\lunit{\mbox{pb$^{-1}$}} \newcommand\lumiler{\mbox{$12.2$}} \newcommand\lumimer{\mbox{$5.9$}} \newcommand\lumicjc{\mbox{$97.6$}} \newcommand\lumibst{\mbox{$5.9$}} \newcommand\gbw{GBW} \newcommand\gbwdglap{GBW+DGLAP$_{\rm valence}$} \newcommand\iim{IIM} \newcommand\iimdglap{IIM+DGLAP$_{\rm valence}$} \newcommand\bsat{B-SAT} \newcommand\bsatdglap{B-SAT+DGLAP$_{\rm valence}$} % acot/rt etc \newcommand\ndfdefone{782} \newcommand\chacotone{722.7} \newcommand\chrtone{773.2} \newcommand\ndfdef{781} \newcommand\chacot{715.2} \newcommand\chrt{764.5} \newcommand\chrtqcut{288.8} \newcommand\chacotqcut{248.3} \newcommand\ndfdglapqcut{249} % comes automatically ... %\newcommand\iimchsq{$397.6/352$} %\newcommand\gbwchsq{$718.8/352$} %\newcommand\bsatchsq{$424.9/352$} %\newcommand\iimqchsq{$259.4/252$} %\newcommand\gbwqchsq{$559.7/252$} %\newcommand\bsatqchsq{$xxx/252$} %\newcommand\iimqdvchsq{$287.6/252$} %\newcommand\gbwqdvchsq{$739.4/252$} %\newcommand\bsatqdvchsq{$xxx/252$} %\input{tables/chi2.tex} \newcommand\bsatchsq{$424.9/352$} \newcommand\bsatqchsq{$261.7/252$} \newcommand\bsatqdvchsq{$371.4/252$} \newcommand\gbwqdvchsq{$739.5/252$} \newcommand\iimqdvchsq{$287.6/252$} \newcommand\gbwchsq{$718.8/352$} \newcommand\gbwqchsq{$559.7/252$} \newcommand\iimchsq{$397.6/352$} \newcommand\iimqchsq{$259.4/252$} %\documentclass[prd,superscriptaddress,unsortedaddress,twocolumn,showpacs,floatfix]{revtex4} %\documentclass[preprint,superscriptaddress,unsortedaddress,showpacs,preprintnumbers,floatfix]{revtex4} %\usepackage{epsfig} %\usepackage{dcolumn} %\usepackage{amsmath} % \linenumbers % Remove for final publication!!!!! \begin{document} % change natbib spacing between numbers in citations \makeatletter \def\NAT@space{} \makeatother \begin{titlepage} \noindent DESY 10-228 \hfill ISSN 0418-9833 \\ December 2010 \\ \vspace*{4.5cm} \begin{center} \begin{Large} {\bfseries Measurement of the Inclusive $\boldsymbol{e^{\pm}p}$ Scattering Cross Section at High Inelasticity $\boldsymbol{y}$ and %Determination of the Structure Function $\boldsymbol{F_L}$ % by the H1 %Experiment. } \vspace*{2cm} H1 Collaboration \end{Large} \end{center} \vspace*{2cm} \begin{abstract} \noindent A measurement is presented of the inclusive neutral current $e^\pm p$ scattering cross section using data collected by the H1 experiment at HERA during the years 2003 to 2007 with proton beam energies $E_p$ of $920$, $575$, and $460$~GeV. The kinematic range of the measurement covers low absolute four-momentum transfers squared, $1.5$~GeV$^2 3.4$~GeV} \\ Radial cluster position & $400.8$} \\ & \multicolumn{3}{c}{$R_{\rm log}<4.5$~cm for $R_{sp}>60$~cm} \\ %$R_{4}>0.8$~cm & $R_{\log}<5$~cm & $R_4>0.8$ \\ & ${\tt ECRA}<4.5$~cm & ${\tt ECRA}<4.5$~cm & ---\\ Energy in hadronic section & \multicolumn{3}{c}{$E_h/\ee<0.15$} \\ Tracker validation & $D_{\rm CJC}<6$~cm & \multicolumn{2}{c}{$D_{\rm BC}<3$~cm} \\ Lepton charge & \multicolumn{3}{c}{ Agree with beam charge for $y\ge \ytrans$} \\ Energy-momentum match & --- & \multicolumn{2}{c}{$|\ee/P|>0.5$ for $\ee <7$~GeV} \\ Longitudinal momentum balance & \multicolumn{3}{c}{$\empz>35$~GeV} \\ Total energy in hadronic SpaCal & --- & --- & $E_{h,{\rm tot}}<16$~GeV \\ QED Compton rejection & \multicolumn{3}{c}{Topological veto} \\ Kinematic range & $Q^2>7.5$~GeV$^2$ & $Q^2>2.37$~GeV$^2$ & $Q^2>1.33$~GeV$^2$ \\ \hline \end{tabular} \end{footnotesize} \end{center} \caption{\label{tab:selection}Selection criteria used for the analyses.} \end{table} \renewcommand{\arraystretch}{1.} The energy of the scattered lepton is required to exceed $\ee>3.4$~GeV to ensure a high trigger efficiency. The radial position of the scattered lepton is required to be well inside the SpaCal acceptance and within the active trigger region. Several cuts are applied to suppress photoproduction background. In photoproduction events, hadronic final state particles may scatter in the SpaCal calorimeter and mimic the electron signal. The main sources of such background are charged hadrons (pions, kaons and (anti-)protons) as well as $\pi^0\to \gamma\gamma$ decays for which one of the photons converts into an $e^+e^-$ pair prior to entering the tracking devices. The selection against photoproduction events includes cuts on the transverse shower radius, estimated using logarithmic ($R_{\log}$) and square root ({\tt ECRA}) energy weighting \cite{Glazov:2010zz}, as well as the fraction of energy of the cluster contained in the four highest energy cells, $R_4$. The cut $R_4>0.8$ is found to be more efficient than the cluster radius estimators, but an L4 condition requires the {\tt ECRA} cut to be used for the $E_p=920$~GeV analyses. The transverse shape requirements are efficient against hadronic background as well as background from $\pi^0 \to \gamma\gamma$ where the two photon clusters merge together. The cut on the fraction of energy in the hadronic SpaCal behind the lepton candidate cluster, $E_h/\ee<0.15$, rejects purely hadronic background. The cut does not reject background for $R_{sp}> 60$~cm because of the limited acceptance of the hadronic SpaCal. As a compromise between signal efficiency and background rejection, an extra cut $R_{\log}<4.5$~cm is introduced for $R_{sp}>60$~cm. % for the \lermer\ analyses. The photoproduction background is suppressed further by requiring cluster validation by a track (``track link''). The \hqcjc\ analysis uses tracks reconstructed solely in the CJC tracker. The other analyses use a dedicated reconstruction algorithm which combines information obtained from the CJC, BST, event vertex and the SpaCal (``BC'' algorithm~\cite{sebastian}). The tracks are extrapolated to the SpaCal position and required to match the SpaCal cluster within $D_{\rm CJC}<6$~cm for the CJC reconstruction and within $D_{\rm BC}<3$~cm for the BC algorithm. The tighter cut on the track-cluster matching for the BC compared to the CJC algorithm is possible for low $R_{sp}$ because of accurate BST $\thetae$ reconstruction and for higher $R_{sp}$ because the SpaCal cluster is used in the BC algorithm and pulls the track towards the cluster. As discussed below, in \Sec~\ref{sec:background}, the measured scattered lepton charge is required to match the beam charge for $y>\ytrans$. The sample for which the charges are different is used to estimate the remaining background. For $\ee <7$~GeV, the momentum reconstruction is accurate enough and $|\ee/P_e|>0.5$ is required, where $P_e$ is the track momentum of the electron candidate. The total energy reconstructed in the hadronic section of the SpaCal, $E_{h,{\rm tot}}$, is required to be below $16$~GeV for the \lermer\ data. This avoids a trigger inefficiency arising from a veto on the total energy deposited in the hadronic SpaCal. Events with high energy initial state photon radiation are rejected by requiring $\empz >35$~GeV. This cut is also efficient against the photoproduction background. The QED Compton process, $ep \to ep\gamma$, is suppressed using a topological cut against events with two back-to-back electromagnetic clusters reconstructed in the SpaCal. Distributions of the variables which are used for the scattered lepton identification are shown for the \ler\ sample in \Fig~\ref{fig:eid}. While the shapes observed in the data are sometimes not perfectly reproduced by the simulation, those differences occur far from the cut values. The electron identification selection criteria are designed to have high efficiency for the signal while rejecting a significant amount of the background. \subsection{Background Subtraction} %\input{background} \label{sec:background} \begin{figure} \end{figure} At low $E'_e$, corresponding to high $y$, the background contribution after the event selection is of a size comparable to the DIS signal. To reduce the systematic uncertainty, the background determination in this analysis relies on data. Two distinct methods are applied depending on the event inelasticity $y$. For high $y\ge \ytrans$, the background estimation is based on a sample of events, in which the charge of the lepton candidate is opposite to the beam charge (``wrong charge method''). For lower $y < \ytrans$ the background contamination is small, however, the uncertainty due to the charge determination becomes large, and an alternative method is employed. In this method the background is estimated using a sub-sample of events, in which the scattered lepton is detected in the electron tagger (``tagger method''). The wrong charge subtraction method relies on the approximate charge symmetry of the background and a good charge reconstruction with the tracker at low momenta. The residual charge asymmetry of the background is defined as \begin{equation} \kappa_+ = \frac{\textstyle N^{\rm bg}_+}{\textstyle N^{\rm bg}_-},~~~~~~~\kappa_- = 1/\kappa_+ = \frac{\textstyle N^{\rm bg}_-}{\textstyle N^{\rm bg}_+}\,, \end{equation} where $N^{\rm bg}_{\pm}$ is the number of background events in which the lepton candidate is associated with a positively (for $+$) and a negatively (for $-$) charged track. The charge asymmetry of the background arises from the different response of the SpaCal to particles compared to antiparticles (in particular $p$ and $\bar{p}$) and detector misalignments. The asymmetry depends on the electron identification cuts since they alter the ratio of the electromagnetic to hadronic components of the background. The charge asymmetry is measured directly from the data by comparing background estimates from the $e^+p$ and $e^-p$ scattering periods as well as using clean background samples with the scattered lepton measured in the electron tagger. The charge asymmetry of the background is found to deviate from unity by $5\%$ and $1\%$ for scattering angles between $155^{\circ}$ and $174^{\circ}$. The scattered lepton charge may be misidentified which leads to an overestimation of the background at $y>\ytrans$. The charge reconstruction is studied in the background free sample at $\ee > 15$~GeV by comparing events with correctly and wrongly reconstructed lepton charge. The fraction of wrongly reconstructed events depends on both the energy and the angle of the scattered electron. This dependence is well reproduced by the simulation. The fraction is smaller at small $\ee$ due to a larger track curvature and at small $\thetae$ since the CJC has a better momentum resolution than the BST. Charge reconstruction at low energy ($E'_e < 15$~GeV) is studied using events with initial state radiation in which the radiative photon is detected in the photon tagger. For these events, the sum of the scattered electron and photon energies, $E_{e+\gamma}$, peaks at the beam energy which allows the estimation of the residual background using a side-band method. This procedure is illustrated for the combined \lermer\ dataset in \Fig~\ref{fig:charge}. The DIS signal is approximated by a Gaussian while the background is assumed to follow an exponential distribution. The Gaussian width of the signal distribution is fixed to be the same for both lepton candidate charges. The data are fitted by the sum of signal and background hypotheses. From these fits, the fraction of events with wrongly reconstructed charge in the data is determined to be $(1.1 \pm 0.2_{\rm stat}) \% $, compared to $0.6\%$ in the simulation. The simulation is corrected for the $0.5\%$ difference and a systematic uncertainty of $0.5\%$ is used for the charge determination of the lepton candidate. The tagger method of background estimation used at low $y<\ytrans$ relies on an accurate determination of the tagger acceptance, $A_{\rm tag}$, which is defined in this analysis as the fraction of background events in which the scattered electron is tagged. The acceptance is measured by comparing all wrong charge events with $\ee<8$~GeV passing nominal selection cuts to those in which a scattered electron candidate is detected in the electron tagger. For this selection, the wrong charge sample is almost entirely comprised of photoproduction events with a small admixture of DIS events with charge misidentification, which is subtracted using the MC estimate. The tagger acceptance is seen to vary between $(16.9\pm0.2_{\rm stat})\%$ for the \hqcjc\ $e^-$ sample, taken in the year $2005$, and $(20.5\pm 0.4_{\rm stat})\%$ for the \mer\ sample. This difference in acceptance may be explained by differences in the beam optics. Stability of the tagger acceptance for different kinematic ranges is studied by varying the $\thetae$ and $\ee$ cuts. A systematic uncertainty of $20\%$ is assigned to the tagger acceptance. This uncertainty also accounts for a potential variation of the acceptance as a function of $E'_e$ and $\thetae$. Finally, to avoid a subtraction of overlapping DIS and Bethe-Heitler events containing energy deposits in the electron tagger, in the background estimation the tagged events are also required to have a charge opposite to the lepton beam charge. Neglecting the background charge asymmetry, this reduces the number of tagged background events by a factor of two. To summarise, the number of signal events for the $e^+p$ and $e^-p$ running periods is estimated as \begin{equation} N^{e^{\pm}p}_{\rm sig} = \left\{ \begin{array}{ll} \textstyle N^{e^{\pm}p}_{\pm} - \kappa_{\pm} N^{e^{\pm}p}_{\mp}~&\mbox{for }y \ge \ytrans\,,\\ \textstyle N^{e^{\pm}p} - \frac{\textstyle 2}{\textstyle A_{\rm tag}} N^{e^{\pm}p}_{\mp \rm tag}~&\mbox{for }y < \ytrans\,. \end{array} \right. \end{equation} Here $N^{e^{\pm} p}_{\pm}$ ($N^{e^{\pm}p}_{\mp}$) is the number of events with the charge of the lepton candidate the same as (opposite to) the lepton beam charge and $N^{e^{\pm}p}_{\mp \rm tag}$ is the number of tagged events with the charge of the lepton candidate opposite to the lepton beam charge. \subsection{Efficiencies} The efficiency of the electron identification cuts is studied in the data and MC, and the simulation is adjusted accordingly. %\input{effic} \subsubsection{Online Selection and Vertex Efficiency} % The efficiencies of the triggers used in the analysis are determined using events collected with independent triggers. The efficiency of the L1 energy condition is checked with tracker-based triggers. It is found to be fully efficient for $\ee>3$~GeV. The efficiency of the L1 tracking condition (CIP or BST for \lermer\ data) is checked using events triggered by SpaCal-based triggers without tracking conditions. The efficiency of the L1 tracking condition is correlated with the vertex efficiency. To avoid biases, a combined efficiency is calculated as \begin{equation} \epsilon_{\rm (CIP||BST) \& VTX} = \epsilon_{\rm CIP||BST} \cdot \epsilon_{\rm VTX|_{(CIP||BST)}} \end{equation} where $\epsilon_{\rm CIP||BST}$ is the CIP or BST L1 condition efficiency based on events without vertex cut and $\epsilon_{\rm VTX|_{(CIP||BST)}}$ is the vertex efficiency for the events passing the CIP or BST tracking condition. A similar decomposition is used for the $\epsilon_{\rm CIP \& VTX}$ condition, used for $E_p=920$~GeV data. The {\rm CIP} L1 condition is found to have uniform efficiency for $R_{\rm sp}>30$~cm, i.e. within the CIP acceptance. The efficiency varies for different periods between $95\%$ and $98.5\%$. For lower radii, the efficiency decreases by about $2\%$ since the scattered lepton leaves the CIP acceptance. This region is covered by the BST pad detector and for the combined ${\rm CIP||BST}$ condition, there is no drop of the efficiency. The efficiency $\epsilon_{\rm VTX|_{(CIP||BST)}}$ decreases at low $R_{\rm sp}<40$~cm and high $y>0.5$ since the scattered lepton as well as part of the hadronic final state leave the CJC acceptance. The decrease in the efficiency occurs mostly for diffractive events which have a rapidity gap between the proton remnant and the struck quark. For $R_{\rm sp}<20$~cm at $y=0.85$, the inefficiency in the data reaches $8\%$ compared to $5\%$ in the Monte Carlo simulation. The difference in the efficiency is parameterised as a function of $R_{\rm sp}$ and $\ee$ and is applied to the simulation. \subsubsection{Offline Selection Efficiency} %\input{eid} \label{sec:eid} The determination of the offline electron selection efficiencies at high $y$ is complicated due to the large background contamination. %This contamination increases if the electron identification cuts are not % applied. Thus an accurate estimation of the background is a matter of paramount importance for this analysis. As discussed in \Sec~\ref{sec:background}, this estimation is provided by the wrong charge data sample, for which a track link is required for the lepton candidate. The track-link efficiency is measured using a background free sample with $17 < \ee < 22$~GeV and no track condition, as the fraction of events satisfying the track link requirement. For the \hqcjc\ sample, the SpaCal cluster is linked with a track from the CJC. It is observed that the track-link efficiency has a radial dependence which is well reproduced by the MC simulation. For the overall level of inefficiency, however, the MC prediction has to be downgraded by $3.6\%$, $3.3\%$ and $5\%$ for the $2003$-$2004$, $2004$-$2005$ and the $2006$-$2007$ running periods, respectively. The track-link efficiency for the {\lqbst}, \lermer\ analyses has radial and azimuthal dependencies in the BST and BST-CJC overlap regions. It has a typical value of $90\%$ but drops in some regions to $75\%$. The simulation is corrected in radial steps of $2$~cm in the $18\le R_{sp}\le 45$~cm range for the $12$~BST azimuthal sectors individually. This correction does not exceed $10\%$. The correction factors to the MC %, which are determined at intermediate $\ee$, are applied for all lepton energies. A cross check for low $\ee$ events is performed using a sample of ISR events for which a good agreement between the data and corrected MC is observed. \begin{sloppypar} %For events with low inelasticity ($y < 0.5$) the energy of the %scattered %electron is larger than the energy of the hadronic jet, and the angle of %the hadronic jet is smaller than that of the electron. In that case an %electron is identified with the electromagnetic cluster in the SpaCal %which has the highest energy (so called $E^{max}$ ordering). In the case %of high $y$ analysis, the situation is different since: %\begin{itemize} %\item The energy of the scattered electron becomes smaller (for example %for $y > 0.6$, $E' < 11$~GeV). This energy is less than the total energy %of the hadronic jet which always is bigger than 15~GeV; %\item The polar angle of the scattered electron is relatively small and is %smaller than the hadron angle which also can be seen from the formula, %\begin{equation} %{\rm tan} {\theta_h \over 2} = {y \over {1 - y}} \cdot {\rm tan} {\theta_e %\over 2}. %\end{equation} %\end{itemize} %From the previous statements it is clear that maximum energy selection %needs to be checked. As alternative, different kinematic criteria have %been investigted. As for high $y$ the polar angle becomes smaller, %selection of a cluster with the minimal polar angle ($\theta^{min}$ %ordering) can be applied. Another approach could be based on the $P_t$ %balance in the event which imposes that the transverse momentum of the %electron is compensated by the sum of transversal momenta of the hadronic %final state particles. In most of the cases the electron is the particle %which has the largest $P_t$ ($P_t^{max}$ ordering). This method is %applicable to the whole $y$ range of the measurement. \\ %A comparison of the different electron identification methods was done %based on the Monte-Carlo simulation. The study shows that applying the %cluster validation brings all the methods close together; they are %approaching the limit, caused mainly by the track-link efficiency.\\ The transverse and longitudinal distributions of the electromagnetic shower energies (``show\-er shapes'') are affected by the amount of material passed through by the scattered lepton before entering the calorimeter. The total amount of material before the SpaCal depends on the scattering angle and varies between $1.7$ and $1.2$ radiation lengths. A detailed map of the detector material is included in the simulation. The distribution of the material in the CT is checked using reconstructed photon conversions and nuclear interactions. A significant contribution to the material budget is due to the BST sensors, cooling circuit and readout electronics. The contribution due to the readout electronics %can not be checked using secondary verticies, this contribution is determined using the transverse shower shapes. The method exploits the fact that the BST was removed from the H1 detector for repair during the $2005$ data taking. A comparison of the shower shapes in the data and MC simulation for the 2005 and 2006 data taking periods thus allows a check of the BST material contribution with high accuracy. \end{sloppypar} The signal efficiencies of the other offline selection cuts listed in \Tab~\ref{tab:selection} are studied after the background subtraction described in \Sec~\ref{sec:background}. %These efficiencies were studied for %different $y$ and $Q^2$ intervals and it was observed that MC describes %inefficiency in data within 2~$\%$. Since the background is large and its level typically varies significantly upon applying these cuts, a variation of the background asymmetry is also considered for each cut of the electron identification. The background subtraction is the dominant systematic uncertainty for the efficiency determination. It is measured with $3\%$ accuracy for $y>0.8$, with $1.5\%$ for $0.70.5$ and low $x$ the kinematics reconstruction using the electron method is prone to large radiative corrections which can reach a level of more than $50\%$ of the Born cross section. Studies based on the DJANGO and HECTOR programs show that the largest radiative contribution arises because of hard initial state radiation from the incoming lepton. The hard ISR process is strongly suppressed by the cut $\empz>35$~GeV. After this cut, the radiative corrections amount to about $10\%$ of the Born cross section with no strong dependence on $y$. A slight increase in the corrections occurs at the highest $y>0.7$ due to QED Compton events. These events are efficiently rejected using the topological cut against two back-to-back clusters in the SpaCal. Events rejected by the cut $\empz>35$~GeV can be used to study the description by the simulation of the hard ISR. This is illustrated in \Fig~\ref{fig:empzrad} which shows the background subtracted $\empz$ distribution for events passing all cuts excluding the $\empz$ cut for the \mer\ sample. The sample is restricted to $\ee<5$~GeV which corresponds to $y>0.8$. A prominent peak for $\empz \approx 10$~GeV corresponds to the hard ISR process. The data in this kinematic region are well described by the simulation. %\subsection{Electron Identification Efficiency} -- move to efficiencies %\input{eid} \subsection{Control Distributions} %\input{control} Data and MC distributions of the main quantities used to reconstruct the event kinematics for the events passing all selection criteria are compared in \Figs~\ref{fig:cont460} to \ref{fig:cont920b} for all data sets included in the analysis. The MC distributions are normalised to the integrated luminosity and corrected for selection efficiency differences, as explained above. The control distributions illustrate the considerable level of background for low $\ee$, that is estimated from the data. The DIS simulation uses the H1PDF2009 set of parton distributions~\cite{Aaron:2009kv}. There is a good overall agreement observed between the measurements and predictions. The local residual differences, visible for the energy distribution in the lowest $Q^2$, BST sample near to $\ee \simeq 10$\,GeV and corresponding to $y_e\simeq 0.7$ (\Fig~\ref{fig:cont920a}a and \Fig~\ref{fig:cont920a}d ), do not affect the cross-section measurement. %\subsection{Cross Checks} %\input{checks} \subsection{Systematic Uncertainties} %\input{systematics} \label{sec:systematics} The systematic uncertainty on the cross-section measurements arises from several contributions. Besides the global normalisation uncertainty, these contributions are classified as correlated uncertainties, which affect measurements at different $Q^2,x$ in a correlated manner, and as uncorrelated ones, for which each of the measurements is affected individually. The summary of all systematic uncertainties is given in table~\ref{tab:systematics}. The global normalisation uncertainty is $3\%$ for the $E_p=920$~GeV period and $4\%$ for the \lermer\ analyses. The uncertainty includes the uncertainty of the luminosity measurement as well as global trigger and reconstruction efficiency uncertainties. The uncertainty on the SpaCal electromagnetic energy scale is determined to be $0.2\%$ at $\ee=27.5$~GeV increasing to $1\%$ at $\ee=2$~GeV for all but the \hqcjc\ analysis. The latter covers a large period of runs, from the year $2003$ to $2005$, and therefore is prone to variations of the SpaCal performance. For this analysis the scale uncertainty is $0.3\%$ at $\ee=27.5$ increasing to $1\%$ at $\ee=2$~GeV. The uncertainty at around $27.5$~GeV is estimated from the difference between the result of the double-angle calibration and the position of the kinematic peak. The uncertainty at $\ee=2$~GeV is obtained using $J/\psi\rightarrow e^+e^-$ and $\pi^0\rightarrow\gamma\gamma$ decays~\cite{H1:2009bp}. The uncertainty on the lepton polar angle is $0.5$\,mrad, which covers uncertainties of the alignment of the SpaCal as well as of the cluster position determination. The hadronic energy scale has an uncertainty of $4\%$. Apart from reconstruction in the LAr calorimeter and in the tracker, this value covers the uncertainty of the hadronic energy scale of the SpaCal, which is important at high $y$. The uncertainty of the LAr electronic noise and beam related background is $20\%$. These uncertainties have %a small little impact on the cross-section measurement which is based on the electron method since they enter only via the $\empz$ cut. The background charge asymmetry is determined with a precision of $2\%$. It affects only the data for $y\ge \ytrans$ where the wrong charge subtraction method is used. Its uncertainty has negligible impact on the \hqcjc\ and \lqbst\ measurements since these are based on both $e^+p$ and $e^-p$ HERA running periods and have a charge symmetric background sample. For the \lermer\ runs, the impact on the cross section reaches $3.5\%$ at $y=0.85$. \renewcommand{\arraystretch}{1.2} \begin{table} \begin{center} \begin{tabular}{l|r} %\multicolumn{2}{c}{\bf Correlated systematic errors} \\ \hline {\bf Correlated uncertainty source} & {\bf Uncertainty} \\ \hline Global normalisation & $3\%$ for \ner\ run \\ & $4\%$ for \lermer\ run\\ \hline $\ee$ energy scale & $0.2\%$ at $27.5$ to $1\%$ at $2$~GeV \\ & (all, but \hqcjc)\\ & $0.3\%$ at $27.5$ to $1\%$ at $2$~GeV \\ & (\hqcjc) \\ Polar angle $\thetae$ & $0.5$~mrad \\ Hadronic energy scale & $4\%$ \\ LAr noise & $20\%$ \\ Background charge asymmetry & $2\%$ \\ Electron tagger acceptance & $20\%$ \\ \hline %\multicolumn{2}{c}{\bf Uncorrelated systematic errors} \\ {\bf Uncorrelated uncertainty source} & {\bf Uncertainty} \\ \hline Trigger efficiency & $1\%$\\ Track-cluster link efficiency & $1.5\%$\\ Lepton charge determination & $1\%$ \\ Electron identification efficiency & $1-3\%$\\ Radiative corrections & $1\%$\\ \hline \end{tabular} \end{center} \caption{\label{tab:systematics} Summary of systematic uncertainties. For the correlated error sources, the uncertainties are given in terms of the uncertainty in the corresponding source. For the uncorrelated error sources, the uncertainties are given in terms of the effect on the measured cross section.} \end{table} \renewcommand{\arraystretch}{1.} The electron tagger acceptance is known to $20\%$. This uncertainty is applied for $y< \ytrans$ only and, since the background at low $y$ is small, this source does not have a significant impact on the measurement. The uncorrelated systematic uncertainties include the Monte Carlo statistical errors and the following sources: the uncorrelated part of the trigger efficiency, known to $1\%$; the track-cluster link efficiency, known to $1.5\%$; the uncertainty of the lepton charge determination of $0.5\%$ leading to $1\%$ uncertainty of the cross section, for $y\ge \ytrans$ only; the electron identification uncertainty varies from $3\%$ for $y>0.8$ to $1\%$ for $y<0.6$; the uncertainty due to the radiative corrections is determined to be $1\%$. % % \section{Cross Section Determination} \label{sec:xs} % %\subsection{This Measurement} %\input{xsec} \subsection{Method} \label{xsec} At low $Q^2$ the contributions to the NC scattering process are completely dominated by photon exchange with negligible differences between the $e^+p$ and $e^-p$ scattering cross sections. The background determination at high $y$ is based on the measured lepton-candidate charge. In order to reduce the sensitivity to the background charge asymmetry, the cross section is determined for a charge symmetric data sample for the \hqcjc\ and the \lqbst\ samples. The reduced cross section is calculated in this case for each $x,Q^2$ bin as \begin{equation} \sigma_r(x,Q^2) = \frac{\textstyle N^{e^-p}_{\rm sig} + N^{e^+p}_{\rm sig} \frac{\textstyle {\cal L}^{e^-p}} {\textstyle {\cal L}^{e^+p}}} {\textstyle N^{e^-p}_{\rm sig,MC} \frac{\textstyle {\cal L}^{e^-p}} {\textstyle {\cal L}^{e^-p}_{\rm MC}} + N^{e^+p}_{\rm sig,MC} \frac{\textstyle {\cal L}^{e^-p}} {\textstyle {\cal L}^{e^+p}_{\rm MC}}}\, \sigma_r^{\rm MC}(x,Q^2)\,. \label{eq:chsym} \end{equation} Here ${\cal L}^{e^{\pm} p}$ (${\cal L}^{e^{\pm}p}_{\rm MC}$) is the integrated luminosity for the data (MC), $N^{e^{\pm} p}_{\rm sig,MC}$ is the number of signal events in the MC and $\sigma_r^{\rm MC}(x,Q^2)$ is the value of the reduced cross section in the MC. \EEq~\ref{eq:chsym} is rather insensitive to the uncertainty of the background charge asymmetry $\kappa_{\pm}$ since for $y\ge \ytrans$, the total background is estimated as $N_{bg} = \kappa_{-}N^{e^{-}p}_+ + \kappa_+N^{e^+p}_- ({\cal L}^{e^-p} /{\cal L}^{e+p})$. The statistical accuracy of \Eq~\ref{eq:chsym} is limited by the sample with the smaller luminosity, therefore the data taking strategy was tuned to obtain $e^+p$ and $e^-p$ samples of about equal size. For the \lermer\ samples, the absence of $e^-p$ data does not allow for usage of \Eq~\ref{eq:chsym}, and a more standard cross section determination formula is used as \begin{equation} \sigma_r(x,Q^2) = \frac{\textstyle N^{e+p}_{\rm sig}}{\textstyle N^{e+p}_{\rm sig,MC} \frac{\textstyle {\cal L}^{e^+p}} {\textstyle {\cal L}^{e^+p}_{\rm MC}} }\, \sigma^{\rm MC}_r(x,Q^2)\,. \end{equation} These cross sections are therefore more sensitive to the uncertainty % Steve wants ``in'' not ``on'': in $\kappa_{\pm}$. \begin{table} %\begin{small} \begin{center} \begin{tabular}{l|llllllllll} \hline {\bf Sample} & \multicolumn{10}{c}{\bf Bin boundaries in $\boldsymbol{y}$} \\ \hline $E_p=460$~GeV & & & $0.9$ & $0.8$ & $0.7$ & $0.6$ & $0.38$ & $0.24$ & $0.15$ & $0.095$ \\ $E_p=575$~GeV & $0.896$ & $0.80$ & $0.72$ & $0.64$ & $0.56$ & $0.48$ & $0.304$ & $0.192$ & $0.12$ & $0.076$\\ $E_p=920$~GeV & $0.56$ & $0.50$ & $0.45$ & $0.40$ & $0.35$ & $0.30$ & $0.19$ & $0.12$ & $0.075$ & $0.0475$\\ \hline \end{tabular} \end{center} %\end{small} \caption{\label{tab:bins}Bin boundaries in $y=Q^2/sx$ for the cross-section analyses at different $E_p$ used to measure the structure function $F_L$.} \end{table} The \hqcjc\ and \lqbst\ samples extend the published H1 measurements to high $y$ and for them the same mixed $(Q^2,x) - (Q^2,y)$ binning is adapted as used in~\cite{H1:2009bp}. The \lermer\ samples are used to measure the structure function $F_L$. For this measurement, an optimal binning is in $(Q^2,y)$ with the $y$ boundaries of the bins adjusted so that the corresponding $x=Q^2/(4 E_e \cdot E_p \cdot y)$ values agree for different $E_p$. This binning is given in \Tab~\ref{tab:bins}. Bin centres are calculated as an arithmetic average of the bin boundaries. Apart from the \lermer\ samples, the binning is also employed in the reanalysis of the published H1 data at $E_p=920$~GeV for the $F_L$ measurement, as is discussed below, in \Sec~\ref{sec:fl}. The purity and stability~\cite{H1:2009bp} of the cross-section measurements are typically above $70\%$ at highest $y$ reducing to about $50\%$ at lowest $y$. \subsection{Results} % The cross-section measurements are given in \Tabs~\ref{tab:bst920}-\ref{tab:h1575last} and shown in \Fig~\ref{fig:newdata}. The new data cover the range between $1.5$~GeV$^2$ and $90$~GeV$^2$ in $Q^2$ reaching values of inelasticity $y$ as high as $0.85$. For the $E_p=920$~GeV sample, the new data can be compared to the previous H1 results~\cite{H1:2009bp,Aaron:2009kv}. For the high $y$ region, the precision of the new data is significantly better than that of the previous H1 result, apart from the global normalisation uncertainty that is larger for the new result. This uncertainty is significantly reduced by combining the H1 measurements. \subsection{Combination of Data} %\input{combination} \label{sec:combination} %\input{tables/920ave} \def\h19500s1v{-0.38} \def\h19500s1e{0.91} \def\h19500s2v{-0.01} \def\h19500s2e{1.00} \def\h19500s3v{0.03} \def\h19500s3e{0.99} \def\h19500s4v{-0.16} \def\h19500s4e{0.94} \def\h19500s5v{-0.04} \def\h19500s5e{1.00} \def\h19500s6v{0.04} \def\h19500s6e{0.99} \def\h19500s7v{-0.09} \def\h19500s7e{0.99} \def\h19500s8v{-0.10} \def\h19500s8e{1.00} \def\h19500s9v{-0.04} \def\h19500s9e{0.98} \def\h19500s10v{0.14} \def\h19500s10e{0.97} \def\h19500s11v{0.05} \def\h19500s11e{0.98} \def\h19500s12v{0.06} \def\h19500s12e{0.99} \def\h19500s13v{-0.05} \def\h19500s13e{0.98} \def\h19500s14v{-0.06} \def\h19500s14e{0.99} \def\h19500s15v{0.15} \def\h19500s15e{0.97} \def\h19500s16v{-0.10} \def\h19500s16e{0.99} \def\h19500s17v{0.15} \def\h19500s17e{0.97} \def\h19500s18v{0.10} \def\h19500s18e{0.91} \def\h19500s19v{-0.15} \def\h19500s19e{0.96} \def\h19500s20v{0.04} \def\h19500s20e{0.99} \def\h19500s21v{-0.03} \def\h19500s21e{1.00} \def\h19500s22v{0.04} \def\h19500s22e{1.00} \def\h19500s23v{-0.14} \def\h19500s23e{0.99} \def\h19500s24v{-0.03} \def\h19500s24e{1.00} \def\h19500s25v{-0.10} \def\h19500s25e{0.99} \def\h19500s26v{-0.03} \def\h19500s26e{1.00} \def\h19600s1v{-0.42} \def\h19600s1e{0.87} \def\h19600s2v{-0.46} \def\h19600s2e{0.92} \def\h19600s3v{0.58} \def\h19600s3e{0.87} \def\h19600s4v{0.08} \def\h19600s4e{0.99} \def\h19600s5v{0.16} \def\h19600s5e{0.98} \def\h19600s6v{-0.01} \def\h19600s6e{0.99} \def\h19600s7v{-0.01} \def\h19600s7e{1.00} \def\h19600s8v{-0.05} \def\h19600s8e{1.00} \def\h19600s9v{-0.05} \def\h19600s9e{0.99} \def\h19600s10v{0.15} \def\h19600s10e{0.98} \def\h19600s11v{0.00} \def\h19600s11e{1.00} \def\h19600s12v{-0.03} \def\h19600s12e{1.00} \def\h19600s13v{-0.02} \def\h19600s13e{1.00} \def\h19600s14v{-0.01} \def\h19600s14e{1.00} \def\heratwoev{-0.25} \def\heratwoee{0.85} \def\heratwothv{0.14} \def\heratwothe{0.84} \def\heratwolarv{-0.03} \def\heratwolare{0.99} \def\heratwonoisev{0.00} \def\heratwonoisee{0.99} \def\heratwolumiv{0.03} \def\heratwolumie{0.96} \def\heratwolumiBSv{-0.30} \def\heratwolumiBSe{0.37} \def\chiave{15.4} \def\dofave{ 36} %\input{tables/lowEave} \def\ElowPv{-0.00} \def\ElowPe{0.91} \def\thlowPv{-0.09} \def\thlowPe{0.92} \def\ehlowPv{-0.00} \def\ehlowPe{1.00} \def\noilowPv{-0.00} \def\noilowPe{1.00} \def\asylowPv{0.00} \def\asylowPe{1.00} \def\gplowPv{0.03} \def\gplowPe{1.00} \def\lum460v{0.08} \def\lum460e{0.71} \def\lum575v{-0.08} \def\lum575e{0.71} \def\chiavelowP{17.2} \def\dofavelowP{ 27} For the proton beam energy $E_p=920$, the new data cover a phase space similar to previous H1 results~\cite{H1:2009bp,Aaron:2009kv} which are based on HERA-I data, collected in the years $1994$ to $2000$. Therefore the data are combined, following the procedure described in~\cite{H1:2009bp,glazov}. \begin{sloppypar} Four data sets are considered in this combination: the combined H1 results from HERA-I \cite{H1:2009bp,Aaron:2009kv}, reported for $E_p=820$~GeV and $E_p=920$~GeV, and the two new data sets, \hqcjc\ and \lqbst. The systematic uncertainties are assumed to be uncorrelated between the HERA-I and HERA-II measurements, apart from a $0.5\%$ overall normalisation uncertainty due to the theoretical uncertainty on the Bethe-Heitler process cross section used for the luminosity measurement. In total, there are $46$ independent sources of systematic uncertainty. %The treatment of correlated, uncorrelated and statistical %uncertainties follows \Eq~31 of~\cite{H1:2009bp}. For $Q^2\ge12$~GeV$^2$, the new data extend the kinematic coverage towards high $y>0.6$. At low $y<0.6$ and for all values of $y$ at low $Q^2$, there is a sizable region of overlap. \end{sloppypar} The combined cross-section measurements are given in \Tabs~\ref{tab615a1} to \ref{tab615a4}. The full information about correlation between cross-section measurements can be found elsewhere~\cite{fullcorr}. The data show very good compatibility, with $\chi^2/\dof = \chiave/\dofave$. At low $y$, the previous H1 data from~\cite{H1:2009bp,Aaron:2009kv} have a higher precision than the new result. In particular, the global normalisation uncertainty was significantly smaller: about $1\%$ at HERA-I compared to $3\%$ at HERA-II. Therefore, in the combination, the new HERA-II data are effectively normalised to the HERA-I result and their global normalisation uncertainties are reduced significantly. \TTab~\ref{tab:syst920} lists those few systematic sources of the HERA-II analyses, which are noticeably altered by the averaging procedure. All alterations stay within one standard deviation of the estimated error. \begin{table} \begin{center} \begin{tabular}{l|rr} \hline {\bf Systematic Source} & {\bf Shift in $\boldsymbol{\sigma}$} & {\bf Uncertainty in $\boldsymbol{\sigma}$} \\ \hline $\ee$ scale & $\heratwoev$ & $\heratwoee$\\ $\thetae$ & $\heratwothv$ & $\heratwothe$\\ ${\cal L}_{CJC}$ & $\heratwolumiv$& $\heratwolumie$\\ ${\cal L}_{BST}$ & $\heratwolumiBSv$& $\heratwolumiBSe$\\ \hline \end{tabular} \end{center} \tablecaption{\label{tab:syst920} Shifts of the central values and reduction of the uncertainty of the systematic error sources in the combination of the \hqcjc\ and \lqbst\ data sets with HERA-I data, expressed as fractions of the original uncertainty.} \end{table} The systematic errors of the HERA-I data are not significantly affected by the combination. At low $y$, the gain in the combined data precision compared to the HERA-I result is small. The uncertainties are reduced by at most $5\%$ of their size and the shift of central values does not exceed $0.2\%$. At high $y$, however, there is a significant gain in the precision achieved by the data combination. For the region $2.5\le Q^2<12$~GeV$^2$ and $y=0.8$, for example, the accuracy of the $E_p=920$~GeV data is improved by about a factor of two. For medium $Q^2$, $12\le Q^2\le 35$~GeV$^2$, the new high $y$ measurements, corresponding to $E_p=920$~GeV, exceed the accuracy of the HERA-I %points data, corresponding to $E_p=820$~GeV, by a factor $1.5$ to $2$. The $E_p=920$\,GeV measurement at HERA-I was limited to $y \leq 0.6$. The \lermer\ data sets are measured using an identical grid of $(Q^2,x)$ bin centres. At low $y$, the influence of the structure function $F_L$ is small. Therefore the two data sets are combined for all $(Q^2,x)$ points satisfying $y_{460}=Q^2/(4 E_e\cdot 460~{\rm GeV}\cdot x )<0.35$ after a small correction of the cross-section values to $E_p=575$~GeV. At higher $y$ the measurements are kept separately but they are affected by the combination procedure. The data show good compatibility, with $\chi^2/\dof = \chiavelowP/\dofavelowP$, and the combined reduced cross-section values are given in \Tabs~\ref{tablowea1} and \ref{tablowea2}. This combined reduced $E_p$ set, together with the combined nominal $E_p$ set, is used for the phenomenological analysis presented in \Sec~\ref{sec:theory}. % \section{Determination of the Structure Function $\mathbold{F_L}$} %\input{flong} \label{sec:fl} \subsection{Procedure} % % %\input{tables/r_val} \def\rchisq{113.8} \def\rval{0.260} \def\rndf{ 150} \def\rerr{0.050} % The structure function $F_L$ is determined using the separate \lermer\ samples and the published $920$~GeV data from~\cite{H1:2009bp,Aaron:2009kv}. To determine $F_L$, common values of the $(x,Q^2)$ grid centres are required for all centre-of-mass energies. The published $920$~GeV data have therefore been reanalysed using the binning adopted for the $F_L$ analysis, see \Tab~\ref{tab:bins}. To determine $F_L$, the data measured at high $y$ for $E_p=460$~GeV are combined with the data at intermediate $y$ for $E_p=575$~GeV and low $y$ for $E_p=920$~GeV. The usage of the published $920$~GeV data compared to a new analysis of the HERA-II data is motivated by a wider $Q^2$ acceptance at low $y$, extending to $Q^2=1.5$~GeV$^2$. In addition, as %it is discussed in \Sec~\ref{sec:combination}, adding the HERA-II data does not improve the precision at low $y$. %The cross section measurements at three different %centre-of-mass energies are shown in \Fig~\ref{fig:flextract}. The determination of the structure function $F_L$ depends on the treatment of the relative normalisations and systematic uncertainties of the data sets. A straightforward but simplified procedure was adopted in~\cite{h1fl} where the data sets were normalised to each other at low $y$. The values of the structure function $F_L$ were determined in straight-line fits to the reduced cross section as a function of $y^2/(1+(1-y)^2)$ in each $(x,Q^2)$ bin using the statistical and uncorrelated systematic uncertainties. The correlated systematic errors were determined using an offset method. An illustration of this procedure, applied to the cross-section data from the current analysis, is shown in \Fig~\ref{fig:rosen}. The procedure adopted in~\cite{h1fl} does not fully take into account correlations between the low and high $y$ regions, used for the cross-section normalisation and the $F_L$ computation. The offset method does not allow for shifts of the central values of the correlated systematic error sources. Thus the information on the goodness of the straight-line fits to the cross-section measurements at the three centre-of-mass energies is not fully employed. The procedure for the $F_L$ determination is improved in the current analysis. The new method extends the averaging procedure of~\cite{H1:2009bp}. For additive uncertainties it %\footnote{Extension to more complex %dependence of the uncertainties can be performed in analogous way as %in~\cite{H1:2009bp}.} is based on the minimisation of the function \begin{equation} \label{eq:flex} \chi^2_0 \left({\bf F_2,F_L,b}\right) = \sum_i \frac{\textstyle \left[ \left(F_2^i - f(y^i) F_L^i\right) - \sum_j \Gamma^i_j b_j - \mu^i\right]^2}{\textstyle \Delta^2_i} + \sum_j b^2_j\,. \end{equation} Here $\mu^i$ is the measured central value of the reduced cross section at a $(Q^2,x;s)$ point $i$ with a combined statistical and uncorrelated systematic uncertainty $\Delta_i = (\Delta_{i,{\rm stat}}^2+\Delta^2_{i,{\rm uncor}})^{1/2}$. The effect of correlated error sources $b_j$ on the cross-section measurements is approximated by the systematic error matrix $\Gamma^i_j$. The function $\chi^2_0$ depends quadratically on the structure functions $F^i_2$ and $F^i_L$ ( denoted as vectors $\bf F_2,F_L$) as well as on $b_j$. Minimisation of $\chi^2_0$ with respect to these variables leads to a system of linear equations. % which can be solved. For low $y\le 0.35$, the coefficient $f(y)$ is small compared to unity and thus $F_L$ can not be accurately measured. In this kinematic domain, the constraint $0\le F_L\le F_2$ provides an even better bound on the value of $F_L$ than the experimental data. Furthermore, the ratio $R$ is not expected to vary strongly as a function of $x$ in the limited $x$ range of sensitivity to $F_L$. For the kinematic range studied in this paper it is measured to be consistent with $R\sim 0.25$. %see \cite{h1fl} and below. To avoid unphysical values for $F_L$, an extra prior is introduced for the $\chi^2$ minimisation: % \begin{equation} \label{eq:flfull} \chi^2\left({\bf F_2,F_L,b}\right) = \chi^2_0\left({\bf F_2,F_L,b}\right) + \sum_i \left(\frac{\textstyle F^i_L - \frac{\textstyle R}{\textstyle R+1} F_2^i } {\textstyle \Delta_{F_L}}\right)^2\,, \end{equation} % where $R=0.25$ and the width $\Delta_{F_L} = 3$ is chosen such that it has a negligible influence for $y > 0.35$. The additional prior preserves the quadratic dependence of the $\chi^2$ function on $F^i_2$ and $F^i_L$. The prior has a significant contribution at low $y$ only and is very similar to imposing a common cross-section normalisation at low $y$ used in~\cite{h1fl}. Since $\Delta_{F_L}$ is chosen to be large, the prior affects only points with large uncertainty on $F_L$. The bias introduced by the prior is investigated by varying the value of $R$ between $0$ and $0.5$ and $\Delta_{F_L}$ between $1$ and $5$, and found to be negligible, for the points chosen for the $F_L$ determination. \subsection{Results} \label{sec:flresults} The measured structure function $F_L(x,Q^2)$ is given in \Tab~\ref{tab:flf2xq} and shown in \Fig~\ref{fig:flxq}. By convention, only measurements with total uncertainties below $0.3$ for $Q^2\le 35$~GeV$^2$ and below $0.4$ for $Q^2=45$~GeV$^2$ are presented. The selection on the total uncertainty removes the bias due to the prior in \Eq~\ref{eq:flfull}. The measurement spans over two decades in $x$ at low $x$, from $x=0.00002$ to $x=0.002$. The data are compared to the result of the DGLAP ACOT fit, which is described in \Sec~\ref{sec:dglap}. The structure function $F_2$ measured for the corresponding bins is given in \Tab~\ref{tab:flf2xq} and shown together with $F_L$ in \Fig~\ref{fig:flf2xq}. Note that compared to the previous determinations of $F_2$ by the H1 collaboration, this measurement represents a model independent determination without extra assumptions on $F_L$. The values of $F_L(x,Q^2)$ resulting from averages over $x$ at fixed $Q^2$ are given in \Tab~\ref{tab:flave} and presented in \Fig~\ref{fig:flaveth}. The average is performed taking into account correlations. The measured structure function $F_L$ is compared with theoretical predictions from HERAPDF1.0~\cite{h1zeus:2009wt}, CT10~\cite{Lai:2010vv}, NNPDF2.1~\cite{Ball:2010de,Forte:2010ta}, MSTW08~\cite{Martin:2009iq}, GJR08~\cite{Gluck:2007ck,Gluck:2008gs} and ABKM09~\cite{Alekhin:2009ni} sets. Depending on the PDF set, the calculations are performed at NLO or NNLO in perturbative QCD. Within the uncertainties all predictions describe the data reasonably well. The measurement of the structure functions $F_2$ and $F_L$ can be used to determine the ratio $R$ (see \Eq~\ref{ratio}). This ratio is shown in \Fig~\ref{fig:flr}. Apart from conditions applied to select $F_L$ results, only measurements with total uncertainties below $0.6$ are included. For $Q^2\ge3.5$~GeV$^2$, the ratio $R$ is consistent with a constant behaviour. This hypothesis is tested by a simultaneous determination of the values of the structure function $F_2(x,Q^2)$ at all $(x,Q^2)$ data points under the assumption that $R$ is constant. In this procedure, values of $R$ are scanned between $R=0$ and $R=0.6$ in $\Delta R=0.01$ steps, and each of the cross-section measurements is used to calculate the structure function $F_2(x,Q^2)$ using \Eq~\ref{eq:rrr}. The measurements of $F_2(x,Q^2)$ from different $E_p$ are then combined using the standard averaging programme~\cite{H1:2009bp} taking into account correlations of the systematic uncertainties. \FFig~\ref{fig:rscan} shows the results of this scan represented as $\chi^2$ for each average as a function of $R$. The minimum is found at $R_{\rm min} = \rval \pm \rerr$ where $\chi^2_{\rm min}/\dof=\rchisq/\rndf$ suggesting a conservative error estimation. It is remarkable that all the low $7\cdot 10^{-5} < x < 2\cdot 10^{-3}$, low $3.5\le Q^2\le 45$~GeV$^2$ data are consistent with the hypothesis that $R$ is constant. % % \section{Phenomenological Analysis} \label{sec:theory} The combined cross-section data for $E_p=460,575$ and $E_p=820,920$~GeV are used for several phenomenological analyses. The fits are applied to the combined reduced cross-section measurements accounting for correlations between the data points. In the following, the quality of different fits is compared in terms of $\chi^2/\dof$. Since the systematic uncertainties dominate over statistics, and they are estimated conservatively, in several cases $\chi^2/\dof$ is observed to be less than unity. This, however, does not prevent the comparison of quality among different fits with the same number of degrees of freedom in terms of $\Delta \chi^2$ since the average error overestimation, approximated as $\sqrt{\chi^2/\dof}$, does not exceed $5-10\%$. % %\subsection{Rise of $\mathbold{F_2}$ Towards Low $\mathbold{x}$} \subsection{$\boldsymbol{\lambda}$ Fit} %\input{rise} The increase of the structure function $F_2$ for $x\to 0$ can be approximated by a power law in $x$, $F_2 = c(Q^2) x^{-\lambda(Q^2)}$. This simple parameterisation was shown to describe previous H1 data rather well for $x<0.01$~\cite{adloff-2001-520}. In the recent H1 analysis~\cite{H1:2009bp}, a fit was performed to the measured reduced cross section, $\sigma_r$, represented as \begin{equation} \sigma_{r}(Q^2,x) = c(Q^2) x^{\textstyle -\lambda (Q^2)}\left[1 - \frac{\textstyle y^2}{\textstyle 1+(1-y)^2} \frac{\textstyle R}{1+\textstyle R} \right]\, \label{eq:lamfit} \end{equation} by allowing $R$ to float for each $Q^2$ bin independently. At low $Q^2\le 10$~GeV$^2$, this lead to surprisingly large values of $R \approx 0.5$, which are incompatible with the result $R \approx 0.26$ obtained in \Sec~\ref{sec:flresults}. A similar behaviour is observed when equation\,\ref{eq:lamfit} is applied to the present data. This points to some inconsistency in the simple power law for the rise of $F_2$ towards low $x$ and the measured value of $R$. A different approach is therefore adopted in this analysis. It is generally assumed that $R=0.26$ for all $Q^2$ bins. A fit termed the $\lambda$ fit is made with only $c(Q^2)$ and $\lambda(Q^2)$ as free parameters. This is extended in a subsequent step to allow for possible deviations in the behaviour of $F_2$ from the simple $\lambda$ fit formula. The combined H1 data are fitted using the offset method to evaluate systematic uncertainties. The parameters obtained in the fits as a function of $Q^2$ are shown in \Fig~\ref{fig:xlamlc}. The parameter $\lambda$ exhibits an approximately linear increase as a function of $\ln Q^2$ for $Q^2 \ge 2$~GeV$^2$. For lower $Q^2$, the variation of $\lambda$ deviates from that linear dependence. The normalisation coefficient $c(Q^2)$ rises with increasing $Q^2$ for $Q^2 < 2$\,GeV$^2$ and is consistent with a constant behaviour for higher $Q^2$, as in\,\cite{adloff-2001-520}. The total $\chi^2$ of the fit is $\chi^2/\dof=538/350$ when the uncertainties are taken as the statistical and uncorrelated systematic uncertainties added in quadrature. Values of $\chi^2/n_{dof}$ significantly larger than unity may arise in the offset method because it does not take into account the correlated systematic uncertainties. Studies show that the largest contribution to the $\chi^2$ arises from the $1 20$~GeV$^2$. Therefore, for the low $Q^2$ domain, the $\lambda'$ fit shows somewhat softer increase towards low $x$ compared to the $\lambda$ fit opposite to that observed for higher $Q^2$ values. %The $\lambda$ and $\lambda'$ fits are compared to the H1 data in \Fig~\ref{fig:f2} %for $Q^2\ge 2$~GeV$^2$. %For this comparison, the measured cross %sections are corrected to the structure function %$F_2$ assuming $R=0.25$. % \FFig~\ref{fig:2f2} shows results of the %fits and their ratio for $Q^2=5$~GeV$^2$ and $Q^2=90$~GeV$^2$ bins. %For the low $Q^2$ domain, %the $\lambda'$ fit shows somewhat softer increase towards low $x$ %compared to the $\lambda$ fit opposite to that observed % for higher $Q^2$ values. The present measurement of $R$ therefore leads to a refined understanding of the rise of $F_2$ towards low $x$, which appears to be tamed at low $Q^2$, and correspondingly lower $x$, compared to a pure power-law behaviour, as it was predicted in~\cite{DeRujula:1974rf}. In order to consolidate the observations obtained with the offset method, an analysis is performed in which the errors are evaluated using the Hessian method following the $\chi^2$ definition given in~\cite{Aaron:2009kv}. The fitted parameters are $2\times 24$ coefficients $c(Q^2),\lambda(Q^2)$ or $c(Q^2),\lambda'(Q^2)$ for the $24$ $Q^2$ bins and the parameters for the sources of the systematic uncertainty. The $\lambda'$ fit returns $\chi^2/\dof = 345.7/350$ compared to a worse $\chi^2/\dof = 370.5/350$ of the $\lambda$ fit. \subsection{DGLAP Fit} \label{sec:qcdfit} %\input{qcd} %\subsubsection{Settings} The new combined H1 data are used together with the previously published high $Q^2\ge 90$~GeV$^2$ H1 data~\cite{Adloff:1999ah,Adloff:2000qj,Adloff:2003uh} as input to a DGLAP pQCD fit analysis to NLO, with the main objective of studying $F_L$ predictions. The HERA measurement regions are limited by $W^2_{min} = 300$~GeV$^2$ and $x_{max} = 0.65$, such that target mass corrections and higher twist contributions can be assumed to be small. In addition, in order to restrict to a region where perturbative QCD is valid, only data with $Q^2 \ge Q^2_{min} = 3.5$~GeV$^2$ are used in the central fit. The influence of this value is discussed further in this section. The internal consistency of the input data set %and its small systematic uncertainties enables a calculation of the experimental uncertainties on the PDFs using the $\chi^2$ tolerance criterion of $\Delta\chi^2=1$. The data are fitted using the program QCDNUM~\cite{qcdnum} and the complete error correlation information in a $\chi^2$ fit as in~\cite{Aaron:2009kv} using MINUIT~\cite{minuit} as the minimisation program. The fit procedure begins with parameterising the input parton distribution functions (PDFs) at a starting scale $Q^2_0=1.9~ \rm GeV^2$, chosen to be below the charm mass threshold. The PDFs are then evolved using the DGLAP evolution equations~\cite{Gribov:1972ri,Gribov:1972rt,Lipatov:1974qm,Dokshitzer:1977sg,Altarelli:1977zs} at NLO~\cite{Curci:1980uw,Furmanski:1980cm} in the $\overline{MS}$ scheme with the renormalisation and factorisation scales set to $Q^2$, and the strong coupling to $\alpha_s(M_Z) = 0.1176$~\cite{pdg}. The QCD predictions for the structure functions are obtained by convoluting the PDFs with the calculable NLO coefficient functions. Those are calculated using the general mass variable-flavour scheme of ACOT~\cite{Kramer:2000hn} and cross checked against the RT scheme~\cite{Thorne:1997ga,Thorne:2006qt}. The ACOT and RT schemes differ in the inclusion of various terms at higher orders in $\alpha_s$ for the computation of the heavy quark structure functions, and for the structure function $F_L$. % For the QCD fit, the following independent input PDFs are chosen: the valence quark distributions $xu_v$ and $xd_v$, the gluon distribution $xg$ and anti-quark distributions $x\bar{U}$ and $x\bar{D}$. The conditions $x\bar{U} = x\bar{u}$, and $x\bar{D} = x\bar{d} +x\bar{s}$ are imposed at the starting scale $Q^2_0$. A standard generic functional form is used to parameterise these PDFs: \begin{equation} xf(x) = A x^{B} (1-x)^{C} (1 + D x + E x^2). \label{eqn:pdf} \end{equation} % The normalisation parameters, $A_{u_v}, A_{d_v}$ and $A_g$, are constrained by the fermion number and momentum sum rules. The up and down quark type $B$ parameters %$B_{\bar{U}}$ and $B_{\bar{D}}$ are set equal, $B_{\bar{U}}=B_{\bar{D}}$, such that there is only a single $B$ parameter for the sea distributions, which governs the PDFs at low $x$. The strange quark distribution is already present at the starting scale, and it is assumed that $x\bar{s}= f_s x\bar{D}$ at $Q^2_0$. The strange fraction is chosen to be $f_s=0.31$, which is consistent with determinations of this fraction using neutrino induced di-muon production data~\cite{Martin:2009iq,Nadolsky:2008zw}. % In addition, to ensure that $x\bar{u} \to x\bar{d}$ as $x \to 0$, the constraint $A_{\bar{U}}=A_{\bar{D}} (1-f_s)$ is applied. The initial fits are performed using the same parameterisation type as for the HERAPDF1.0 fit~\cite{h1zeus:2009wt}, which has only one free polynomial parameter, $E_{u_v}$. For this parameterisation, the ACOT and RT heavy flavour schemes are compared. Both fits give good descriptions of the data, but the ACOT fit, which has $\chi^2/\dof = \chacotone/\ndfdefone$, is superior to the RT fit, with $\chi^2/\dof = \chrtone/\ndfdefone$, by about $50$~units. Therefore, the ACOT fit is chosen for further more detailed investigations. The central fit is chosen in a $\chi^2$ optimisation procedure, as previously used by H1~\cite{Aaron:2009kv}, in which all extra parameters $D,E$ are first set to zero, leading to a nine parameter fit. They are then added, one at a time until no significant improvement in $\chi^2$ is observed. In addition, the assumption that $B_{u_v} = B_{d_v}$ is removed and a flexible parameterisation for the gluon density with two extra parameters~\cite{h1zeus:2009wt} is also tried but both variations do not lead to significant fit improvements. The parameterisation procedure also requires for the central fit that all PDFs are positive definite. The best fit is obtained with the extra free parameters $D_{u_v}$ and $E_{u_v}$ % and the valence quark %approximation $d_{v} > \bar{d}$ and $ u_{v} > \bar{u}$ %is satisfied at large $x$. %The values %of the parameters are given in \Tab~\ref{tab:acottab}. %For this fit, resulting in a $\chi^2/\dof = \chacot/\ndfdef$. \FFig~\ref{fig:acotcent} compares the fit result to the low $Q^2$ H1 data. As a consistency check, a fit using the RT heavy flavour scheme is repeated. A similar increase in $\chi^2$ of about $50$ units is observed in this case. \label{sec:dglap} \begin{table} \begin{center} \begin{tabular}{l|cccccc} \hline $\boldsymbol{Q^2_{min}}$ {\bf / GeV}$\boldsymbol{^2}$ & $1.5$ & $2$ & $2.5$ & $3.5$ &$5$ & $7.5$\\ $\boldsymbol{\chi^2/\dof}$ & $824.8/834$ & $777.9/818$ & $748.7/801$ & $\chacot/\ndfdef$ & $677.6/759$ & $626.9/712$ \\ \hline \end{tabular} \end{center} \tablecaption{\label{tab:q2scan}Values of $\chi^2/\dof$ for QCD fits with different $Q^2_{min}$ values.} \end{table} \begin{table} \begin{center} \begin{tabular}{l|cccccc} \hline $\boldsymbol{A_S}$ & $0.2$ & $0.3$ & $0.5$ & $0.7$ &$1.0$ &$1.5$\\ $\boldsymbol{\chi^2/\dof}$ & $709.5/777$ & $696.1/762$ & $643.1/734$ & $617.3/709$ & $594.4/690$ & $554.1/654$ \\ \hline \end{tabular} \end{center} \tablecaption{\label{tab:satscan}Values of $\chi^2/\dof$ for QCD fits with different values of the parameter $A_S$ for saturation-inspired cut on data, see \Eq~\ref{eq:asasas}.} \end{table} The sensitivity of the fit to the inclusion of low $Q^2$ data is studied by varying the $Q^2_{min}$ cut. The variation of the fit quality in terms of $\chi^2/\dof$ is summarised in \Tab~\ref{tab:q2scan}. Increasing the $Q^2_{min}$ cut leads to a steady decrease in the $\chi^2/\dof$, suggesting that the fit has some difficulties to describe the data at low $Q^2$ values. \FFig~\ref{fig:acotf2} compares the structure function $F_2$ with the fits performed using different $Q^2_{min}$ cuts. At low $Q^2$ the shape of the measured structure function $F_2$ as a function of $x$ is somewhat different from those obtained by the DGLAP fits based on the parameterisation described above. The fit obtained with a $Q^2_{min}$ cut of $7.5$~GeV$^2$ falls significantly below the data at small $x$ when extrapolating to the low $Q^2$ region. \FFig~\ref{fig:q2pdfs} shows gluon and sea-quark distributions for different values of $Q^2_{min}$ at the evolution starting scale $Q^2_0=1.9$~GeV$^2$. A change of $Q^2_{min}$ from $1.5$~GeV$^2$ to $7.5$~GeV$^2$ leads to an increase of the gluon distribution while the sea-quark distribution becomes smaller at low $x$. This suppression of the sea-quark contribution at small $x$ when using a $Q^2_{min}$ cut of $7.5$~GeV$^2$ is responsible for the smaller values of $F_2$ obtained by this fit at small $Q^2$ and small $x$. An alternative approach to the $Q^2_{min}$ variation is a saturation-inspired cut on the kinematic region depending on $x$ like \begin{equation} \label{eq:asasas} Q^2 \ge A_S x^{-\lambda_S}, \end{equation} with $\lambda_S = 0.3$ and different values of the parameter $A_S$, as suggested in~\cite{Caola:2009iy}. The dependence of $\chi^2/\dof$ on $A_S$ is given in \Tab~\ref{tab:satscan}. \FFig~\ref{fig:satpdfs} shows gluon and sea-quark distributions for different values of $A_S$. The saturation-inspired cut has an effect similar to the one of the $Q^2_{min}$ variation. The fit quality improves with increasing $A_S$ and the gluon becomes larger while the sea-quark density decreases at low $x$. To facilitate the comparison of the data with dipole model predictions, DGLAP fits are also performed in the kinematic domain $x<0.01$ and $Q^2\ge 3.5$~GeV$^2$, in which both the DGLAP theory and the dipole ansatz can be assumed to hold. The valence quark parameters cannot be determined in this range. Therefore they are fixed to the values obtained by the full phase space fits. There are six non-valence quark parameters, $B_g$, $C_g$, $A_{\bar{D}}$, $B_{\bar{D}}$, $C_{\bar{D}}$ and $C_{\bar{U}}$, as compared to three free parameters of the dipole models discussed below. When restricted to this common kinematic domain, the ACOT fit is of very good quality, with $\chi^2/\dof=\chacotqcut/\ndfdglapqcut$ while the RT fit yields $\chi^2/\dof=\chrtqcut/\ndfdglapqcut$. \subsection{Dipole Model Fits} %\input{dipole} \label{sec:dipole} % At low $x$ and low $Q^2$, virtual photon-proton scattering has been described using the colour dipole model~\cite{Nikolaev:1990ja}. In this model, the scattering process is calculated as a fluctuation of the photon into a quark-antiquark pair (dipole), with a lifetime $\propto 1/x$, which interacts with the proton. Several approaches were developed to phenomenologically describe the dipole-proton interaction cross section, three of which are subsequently applied to the data of this paper. These are the original model version (\gbw)\,\cite{Golec-Biernat:1998js}, a model based on the colour glass condensate approach to the high parton density regime (\iim)\,\cite{Iancu:2003ge}, and a model with the generalised impact parameter dipole saturation (\bsat)\,\cite{Kowalski:2006hc}. In the GBW model the dipole-proton cross section $\hat{\sigma}$ is given by % \begin{equation} \label{eq:gbw} \hat{\sigma}(x,r) = \sigma_0 \left\{1 - \exp \left[-r^2 / \left(4 r_0^2(x)\right) \right] \right\}\,, \end{equation} where $r$ corresponds to the transverse separation between the quark and the antiquark, and $r^2_0$ is an $x$ dependent scale parameter, assumed to have the form % \begin{equation} r_0^2(x) \sim \left(x/x_0\right)^{\lambda} \label{eq:satrad}\,. \end{equation} The parameters of the fit are the cross-section normalisation $\sigma_0$ as well as $x_0$ and $\lambda$. The IIM model has a modified expression for $\hat{\sigma}$ using the parameter $R_{\rm IIM}$ instead of $\sigma_0$. The B-SAT model modifies \Eq~\ref{eq:gbw} by adding effects of the DGLAP evolution. This model uses as an input a gluon density \begin{equation} xg (x, Q_0^2) = A_g x^{-\lambda_g} (1-x)^{5.6} \end{equation} with the starting scale $Q_0^2$, normalisation $A_g$ and low $x$ exponent $\lambda_g$ as free parameters while the other dipole model parameters are kept fixed. The dipole models are applicable at low $x<0.01$ where the gluon and sea quark densities dominate. The models are valid down to the photoproduction limit $Q^2 \approx 0$, therefore no $Q^2$ cut is applied for the central fits. In DGLAP fits it is observed that the contribution of the valence quarks to the $ep$ scattering cross section is sizeable for the whole HERA kinematic range, compared to the data precision. %For the measured data points This contribution varies between $5\%$ and $15\%$ for $x$ varying from $0.0001$ to $0.01$. Modified dipole fits are therefore performed, in which the contribution from the valence quarks to the cross section, as determined by the central DGLAP fit, is added to the dipole model prediction. These fits are performed requiring that $Q^2\ge 3.5$~GeV$^2$, to be consistent with DGLAP analyses. It should be noted that the size of the valence-quark contribution at low $x$ is rather uncertain because it is only indirectly constrained by the HERA data. For $x>0.01$ it is determinedned by the combination of neutral and charged current scattering cross sections measurements. %but At lower $x$ however the valence quark contribution follows from the % by the parameterisation %shape and the fermion number sum rules. The uncertainty can reach $\sim 30\%$ at $x=0.0001$~\cite{h1zeus:2009wt}. %\input{tables/table3} \begin{table} \begin{center} \renewcommand{\arraystretch}{1.1} \begin{small} \begin{tabular}{l|cc|cc|cc} \hline {\bf Parameter} & {\bf Value} & {\bf Uncertainty} & {\bf Value} & {\bf Uncertainty} & {\bf Value} & {\bf Uncertainty} \\ \hline & \multicolumn{2}{c|}{\bf Nominal GBW} & \multicolumn{2}{c|}{\bf $\boldsymbol{Q^2\ge 3.5}$~GeV$^2$ \gbw} & \multicolumn{2}{c}{\bf \gbwdglap} \\ \hline %\input{tables/all_gbw.tex} $\sigma_{0}$ (mb) & $ 21.7$ & $ 0.7$ & $ 18.4$ & $ 0.7$ & $ 17.7$ & $ 0.7$ \\ $\lambda$ & $0.287$ & $0.002$ & $ 0.296$ & $0.003$ & $ 0.336$ & $0.003$ \\ $x_{0}$ & $ 1.76 \times 10^{-4}$ & $ 0.25 \times 10^{-4}$ & $ 3.50 \times 10^{-4}$ & $ 0.60 \times 10^{-4}$ & $ 3.46 \times 10^{-4}$ & $ 0.57 \times 10^{-4}$ \\ \hline & \multicolumn{2}{c|}{\bf Nominal IIM} & \multicolumn{2}{c|}{\bf$\boldsymbol{Q^2\ge 3.5}$~GeV$^2$ \iim} & \multicolumn{2}{c}{\bf \iimdglap} \\ \hline %\input{tables/all_iim.tex} $R_{\rm IIM}$ (fm) & $0.611$ & $0.007$ & $0.595$ & $0.007$ & $0.666$ & $0.009$ \\ $\lambda$ & $0.258$ & $0.004$ & $ 0.260$ & $0.004$ & $0.289$ & $0.005$ \\ $x_{0}$ & $ 0.48 \times 10^{-4}$ & $ 0.06 \times 10^{-4}$ & $ 0.61 \times 10^{-4}$ & $ 0.08 \times 10^{-4}$ & $ 0.15 \times 10^{-4}$ & $ 0.03 \times 10^{-4}$ \\ \hline & \multicolumn{2}{c|}{\bf Nominal B-SAT} & \multicolumn{2}{c|}{\bf $\boldsymbol{Q^2\ge 3.5}$~GeV$^2$ \bsat} & \multicolumn{2}{c}{\bf \bsatdglap} \\ \hline %\input{tables/all_bsat.tex} $A_g$ & $ 2.32$ & $ 0.06$ & $ 2.38$ & $ 0.09$ & $ 1.66$ & $ 0.05$ \\ $\lambda_g$ & $0.088$ & $0.010$ & $ 0.073$ & $0.014$ & $ 0.099$ & $0.011$ \\ $Q^2_0$ (GeV$^2$) & $2.25$ & $0.18$ & $ 2.04 $ & $ 0.20 $ & $ 1.51 $ & $ 0.11 $ \\ \hline \end{tabular} \end{small} \end{center} \renewcommand{\arraystretch}{1.} \tablecaption{\label{tab:dipole} Parameters and total uncertainties for GBW, IIM and B-SAT dipole model fits for various fit conditions described in the text. The $Q^2\ge 3.5$~GeV$^2$ and DGLAP$_{valence}$ fits are performed in a kinematic phase spaces restricted to $Q^2\ge 3.5$~GeV$^2$.} \end{table} Dipole models fits are performed using the same minimisation package as for the DGLAP fit. The values of parameters and their uncertainties are estimated using a Monte Carlo method \cite{Glazov:2010bw}\footnote{The Monte Carlo method is preferred for the estimation of uncertainties compared to the MINUIT error estimation in order to avoid instabilities of numerical integration used in the Dipole codes.}. The parameters of the fits are given in \Tab~\ref{tab:dipole}. The fit qualities are summarised together with the results obtained for DGLAP fits in \Tab~\ref{tab:dipolchi}. Among the dipole models, the \iim\ fit provides the best description of the data. It is shown in \Figs~\ref{fig:iimfit1} and \ref{fig:iimfit2}. The \bsat\ model, which includes some DGLAP evolution, provides a worse fit to the data yet still with an acceptable $\chi^2/\dof$. The \gbw\ model, however, fails to describe the data. This fit agrees with the data well at low $Q^2$, but falls significantly below the data for $Q^2\ge 25$~GeV$^2$, where the DGLAP evolution, neglected in the model, plays an important role. Fits with a DGLAP-based correction for the contribution of the valence quarks are restricted to $Q^2\ge3.5$~GeV$^2$. In order to simplify comparisons, pure dipole model fits with the same $Q^2$ cut are performed too. The addition of the valence-quark contribution allows an acceptable description of the data at high $x$, however, the overall fit quality is reduced. The fitted parameters of the models vary beyond their experimental uncertainties. As an example, a comparison of the reduced cross-section data to the \iimdglap\ fit is given in \Fig~\ref{fig:iimdglap}. Finally, the fits at $x<0.01$ and $Q^2\ge3.5$~GeV$^2$ are compared in terms of $\chi^2/\dof$ for the three dipole and two DGLAP models (\Tab~\ref{tab:dipolchi}). The best description is obtained with the ACOT fit, followed by the pure dipole model \iim\ and \bsat\ fits. The DGLAP RT fit is of similar quality as the \iimdglap\ fit, followed by the \bsatdglap\ fit. The \gbw\ fit fails to describe the data in this kinematic domain. In both the DGLAP and the dipole models the structure function $F_L$ can be calculated once the model parameters are fixed. It is thus of interest to compare the $F_L$ predictions of the different models with the data, %structure function $F_L$, which is illustrated in \Fig~\ref{fig:flave}. For high $Q^2>10$~GeV$^2$, all models agree with the data and with each other well. For lower $Q^2$ values, there is a significant difference between the predictions. The DGLAP fit in the RT scheme predicts low values of $F_L$, while in the DGLAP fit in the ACOT scheme the decrease of $F_L$ occurs at lower values of $Q^2$. %The dipole models considered vary less as a function of $Q^2$. The predictions of the dipol models considered here show only little variation with $Q^2$. All predictions, except the DGLAP RT fit, agree with the data well. The $Q^2$ dependence of $F_L$ is best reproduced by the DGLAP ACOT fit. %-- data mc comparisons -- better high x -- chi2 -- change of the parameters. \begin{table} \begin{center} \begin{tabular}{l|ccc|cc} \hline & \multicolumn{5}{c}{\bf $\rm \boldsymbol{\chi^2/\dof}$ } \\ {\bf Fit Conditions } & {\bf \gbw } & {\bf \iim } & {\bf \bsat } & {\bf ACOT} & {\bf RT}\\ \hline Nominal fit & \gbwchsq & \iimchsq & \bsatchsq & $\chacot/\ndfdef$ & $\chrt/\ndfdef$ \\ $Q^2\ge 3.5$~GeV$^2$ & \gbwqchsq & \iimqchsq & \bsatqchsq\\ DGLAP$_{\rm valence}$ & \gbwqdvchsq & \iimqdvchsq &\bsatqdvchsq & $\chacotqcut/\ndfdglapqcut$ & $\chrtqcut/\ndfdglapqcut$ \\ \hline \end{tabular} \end{center} \tablecaption{\label{tab:dipolchi}Quality of fits in terms of $\chi^2/\dof$ for \gbw, \iim\ and \bsat\ dipole model as well as ACOT and RT DGLAP models for various fit conditions described in the text. The $Q^2\ge 3.5$~GeV$^2$ and DGLAP$_{\rm valence}$ fits are performed in a kinematic phase space restricted to $Q^2\ge 3.5$~GeV$^2$ and $x<0.01$ which is valid for both dipole and DGLAP models. } \end{table} % no discussion ... % \subsection{Discussion of Fit Results} % \input{discussion} %\subsubsection{Framework and Parameterisations} %\input{qcdset} %\subsubsection{Results and Kinematic Cut Variations} %\input{qcdresult} % %\subsection{Discussion} % \section{Summary} \label{sec:conclusion} %\input{summary} A measurement is presented of the inclusive double differential cross section for neutral current deep inelastic $e^{\pm}p$ scattering at small Bjorken~$x$ and low absolute four-momentum transfers squared, $Q^2$. The measurement extends to high values of inelasticity $y$. The data were collected with the H1 detector for the proton beam energy of $E_p=920$~GeV, in the years $2003$ to $2006$, and for $E_p=575$~GeV and $E_p=460$~GeV, in $2007$. The integrated luminosities of the measurements are $103.5$\,\lunit, \lumimer\,\lunit\ and \lumiler\,\lunit\ for the $E_p=920$~GeV, $E_p=575$~GeV and $E_p=460$~GeV data samples, respectively. The data at $E_p=920$~GeV significantly improve the accuracy of the cross-section measurements at high $y$ when compared to the previous H1 data. All data are combined with the HERA-I results to provide a new accurate data sample covering $0.2\le Q^2 \le 150$~GeV$^2$, $5\times10^{-6} < x < 0.15$ and $0.005 10$~GeV$^2$. For lower $Q^2$, however, the RT fit falls significantly below the data while the other models describe the measured $F_L$ well. The present measurement and the combination with all accurate H1 DIS cross section data provide a total cross section uncertainty of about $1$\% at low $Q^2$ and low $x$. The structure function $F_2(x,Q^2)$ rises towards low $x$. The structure function $F_L(x,Q^2)$ is measured directly. Both structure functions agree with pQCD expectations. % \section*{Acknowledgements} \refstepcounter{pdfadd} \pdfbookmark[0]{Acknowledgements}{s:acknowledge} %\begin{theacknowledgments} % We are grateful to the HERA machine group whose outstanding efforts have made this experiment possible. We thank the engineers and technicians for their work in constructing and maintaining the H1 detector, our funding agencies for financial support, the DESY technical staff for continual assistance and the DESY directorate for support and for the hospitality which they extend to the non-DESY members of the collaboration. %\end{theacknowledgments} \bibliography{lowe.bib} \clearpage %\input{tables} \label{sec:tables} \begin{table} \begin{scriptsize} \begin{center} \begin{tabular}{cccccccccccc} \hline \\[-8pt] $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma_r}$ & $\boldsymbol{\delta_{stat}}$ & $\boldsymbol{\delta_{unc}}$& $\boldsymbol{\delta_{tot}}$ & $\boldsymbol{\gamma_{\ee}}$ & $\boldsymbol{\gamma_{\thetae}}$ & $\boldsymbol{\gamma_{had}}$ & $\boldsymbol{\gamma_{noise}}$ & $\boldsymbol{\gamma_{acctag}}$ \\ {\bf GeV}$^2$ & & & & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \%} & {\bf \%} & {\bf \%} & {\bf \% } \\ \hline \\[-8pt] %\input{tables/h1_combbs920pm} $ 2.5$ & $ 2.900\times 10^{-5 } $ & $ 0.85 $& $ 0.828 $ &$ 5.70$ &$ 4.29 $& $ 7.28 $ & $ 1.26 $ & $ -0.15 $ & $ 0.52 $ & $ 0.53 $ & $ 0.00 $ \\ $ 2.5$ & $ 3.290\times 10^{-5 } $ & $ 0.75 $& $ 0.816 $ &$ 3.99$ &$ 3.27 $& $ 5.36 $ & $ 1.13 $ & $ -0.72 $ & $ 0.35 $ & $ 0.42 $ & $ 0.00 $ \\ $ 2.5$ & $ 3.790\times 10^{-5 } $ & $ 0.65 $& $ 0.896 $ &$ 6.91$ &$ 4.76 $& $ 9.20 $ & $ 3.70 $ & $ -0.76 $ & $ -0.05 $ & $ -0.05 $ & $ 0.00 $ \\ $ 3.5$ & $ 4.060\times 10^{-5 } $ & $ 0.85 $& $ 0.809 $ &$ 6.13$ &$ 4.17 $& $ 7.57 $ & $ 1.11 $ & $ 0.96 $ & $ 0.33 $ & $ 0.35 $ & $ 0.00 $ \\ $ 3.5$ & $ 4.600\times 10^{-5 } $ & $ 0.75 $& $ 0.971 $ &$ 3.04$ &$ 2.99 $& $ 4.35 $ & $ 0.42 $ & $ -0.63 $ & $ 0.28 $ & $ 0.35 $ & $ 0.00 $ \\ $ 3.5$ & $ 5.310\times 10^{-5 } $ & $ 0.65 $& $ 0.887 $ &$ 3.09$ &$ 2.64 $& $ 4.12 $ & $ 0.53 $ & $ -0.17 $ & $ 0.21 $ & $ 0.20 $ & $ 0.00 $ \\ $ 3.5$ & $ 8.000\times 10^{-5 } $ & $ 0.43 $& $ 0.952 $ &$ 5.62$ &$ 3.66 $& $ 7.28 $ & $ 1.60 $ & $ -2.00 $ & $ 0.31 $ & $ 0.44 $ & $ 1.07 $ \\ $ 5.0$ & $ 5.800\times 10^{-5 } $ & $ 0.85 $& $ 0.939 $ &$ 6.41$ &$ 4.13 $& $ 7.81 $ & $ 1.46 $ & $ 0.58 $ & $ 0.35 $ & $ 0.47 $ & $ 0.00 $ \\ $ 5.0$ & $ 6.580\times 10^{-5 } $ & $ 0.75 $& $ 1.002 $ &$ 2.84$ &$ 2.87 $& $ 4.15 $ & $ 0.74 $ & $ -0.39 $ & $ 0.32 $ & $ 0.36 $ & $ 0.00 $ \\ $ 5.0$ & $ 7.590\times 10^{-5 } $ & $ 0.65 $& $ 1.094 $ &$ 1.71$ &$ 2.29 $& $ 3.08 $ & $ 1.02 $ & $ -0.39 $ & $ 0.24 $ & $ 0.24 $ & $ 0.00 $ \\ $ 5.0$ & $ 1.300\times 10^{-4 } $ & $ 0.38 $& $ 1.050 $ &$ 3.14$ &$ 2.24 $& $ 4.27 $ & $ 1.40 $ & $ -1.00 $ & $ 0.18 $ & $ 0.26 $ & $ 0.56 $ \\ $ 6.5$ & $ 7.540\times 10^{-5 } $ & $ 0.85 $& $ 1.133 $ &$ 6.23$ &$ 4.15 $& $ 7.55 $ & $ 0.02 $ & $ 0.89 $ & $ 0.29 $ & $ 0.34 $ & $ 0.00 $ \\ $ 6.5$ & $ 8.550\times 10^{-5 } $ & $ 0.75 $& $ 1.077 $ &$ 2.83$ &$ 2.82 $& $ 4.25 $ & $ 1.07 $ & $ 0.85 $ & $ 0.32 $ & $ 0.34 $ & $ 0.00 $ \\ $ 6.5$ & $ 9.860\times 10^{-5 } $ & $ 0.65 $& $ 1.134 $ &$ 2.09$ &$ 2.31 $& $ 3.29 $ & $ 0.89 $ & $ 0.45 $ & $ 0.24 $ & $ 0.23 $ & $ 0.00 $ \\ $ 6.5$ & $ 1.300\times 10^{-4 } $ & $ 0.49 $& $ 1.115 $ &$ 1.51$ &$ 1.86 $& $ 2.55 $ & $ 0.71 $ & $ -0.15 $ & $ 0.17 $ & $ 0.18 $ & $ 0.40 $ \\ $ 6.5$ & $ 2.000\times 10^{-4 } $ & $ 0.32 $& $ 1.082 $ &$ 1.72$ &$ 1.91 $& $ 2.85 $ & $ 0.85 $ & $ -0.89 $ & $ 0.03 $ & $ 0.05 $ & $ 0.07 $ \\ $ 6.5$ & $ 3.200\times 10^{-4 } $ & $ 0.20 $& $ 1.054 $ &$ 3.17$ &$ 2.25 $& $ 4.11 $ & $ 0.94 $ & $ -0.94 $ & $ 0.00 $ & $ 0.00 $ & $ 0.16 $ \\ $ 8.5$ & $ 9.860\times 10^{-5 } $ & $ 0.85 $& $ 1.146 $ &$ 6.46$ &$ 4.05 $& $ 7.71 $ & $ 1.07 $ & $ -0.04 $ & $ 0.37 $ & $ 0.35 $ & $ 0.00 $ \\ $ 8.5$ & $ 1.118\times 10^{-4 } $ & $ 0.75 $& $ 1.102 $ &$ 3.31$ &$ 2.82 $& $ 4.46 $ & $ 0.84 $ & $ 0.43 $ & $ 0.22 $ & $ 0.22 $ & $ 0.00 $ \\ $ 8.5$ & $ 1.290\times 10^{-4 } $ & $ 0.65 $& $ 1.200 $ &$ 1.69$ &$ 2.22 $& $ 3.04 $ & $ 1.11 $ & $ 0.38 $ & $ 0.21 $ & $ 0.21 $ & $ 0.00 $ \\ $ 8.5$ & $ 2.000\times 10^{-4 } $ & $ 0.42 $& $ 1.206 $ &$ 1.24$ &$ 1.80 $& $ 2.29 $ & $ 0.56 $ & $ 0.27 $ & $ 0.13 $ & $ 0.17 $ & $ 0.17 $ \\ $ 8.5$ & $ 3.200\times 10^{-4 } $ & $ 0.26 $& $ 1.118 $ &$ 1.38$ &$ 1.82 $& $ 2.42 $ & $ 0.80 $ & $ 0.03 $ & $ 0.00 $ & $ 0.00 $ & $ 0.04 $ \\ $ 12.0$ & $ 1.392\times 10^{-4 } $ & $ 0.85 $& $ 1.238 $ &$ 5.34$ &$ 3.97 $& $ 6.80 $ & $ 1.36 $ & $ 0.10 $ & $ 0.21 $ & $ 0.25 $ & $ 0.00 $ \\ $ 12.0$ & $ 1.578\times 10^{-4 } $ & $ 0.75 $& $ 1.313 $ &$ 3.41$ &$ 2.82 $& $ 4.47 $ & $ 0.45 $ & $ 0.29 $ & $ 0.23 $ & $ 0.26 $ & $ 0.00 $ \\ $ 12.0$ & $ 1.821\times 10^{-4 } $ & $ 0.65 $& $ 1.244 $ &$ 2.51$ &$ 2.30 $& $ 3.54 $ & $ 0.73 $ & $ 0.54 $ & $ 0.23 $ & $ 0.20 $ & $ 0.00 $ \\ $ 12.0$ & $ 2.000\times 10^{-4 } $ & $ 0.59 $& $ 1.258 $ &$ 1.67$ &$ 2.20 $& $ 2.98 $ & $ 0.94 $ & $ 0.52 $ & $ 0.17 $ & $ 0.19 $ & $ 0.00 $ \\ \hline \end{tabular} \end{center} \end{scriptsize} \tablecaption{\label{tab:bst920} Reduced cross section $\sigma_{r}$, as measured with the {\lqbst} data sample. The uncertainties are quoted in \% relative to $\sigma_r$. $\delta_{\rm stat}$ is the statistical uncertainty, $\delta_{\rm unc}$ represents the uncorrelated systematic uncertainty and $\delta_{\rm tot}$ is the total uncertainty determined as the quadratic sum of systematic and statistical uncertainties. $\gamma_{E_e^{\prime}}$, $\gamma_{\theta_e}$, $\gamma_{had}$, $\gamma_{\rm noise}$ and $\gamma_{\rm acctag}$ are the bin-to-bin correlated systematic uncertainties in the cross section measurement due to uncertainties in the SpaCal electromagnetic energy scale, electron scattering angle, calorimeter hadronic energy scale, LAr calorimeter noise and electron tagger acceptance, respectively. The global normalisation uncertainty of $3$\% is not included in $\delta_{\rm tot}$. } \end{table} \begin{table} \begin{scriptsize} \begin{center} \begin{tabular}{cccccccccccc} \hline \\[-8pt] $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma_r}$ & $\boldsymbol{\delta_{stat}}$ & $\boldsymbol{\delta_{unc}}$& $\boldsymbol{\delta_{tot}}$ & $\boldsymbol{\gamma_{\ee}}$ & $\boldsymbol{\gamma_{\thetae}}$ & $\boldsymbol{\gamma_{had}}$ & $\boldsymbol{\gamma_{noise}}$ & $\boldsymbol{\gamma_{acctag}}$ \\ {\bf GeV}$^2$ & & & & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \%} & {\bf \%} & {\bf \%} & {\bf \% } \\ \hline \\[-8pt] %\input{tables/h1_comb920pm} $ 8.5$ & $ 9.860\times 10^{-5 } $ & $ 0.85 $& $ 1.172 $ &$ 2.22$ &$ 3.75 $& $ 4.44 $ & $ 0.76 $ & $ 0.09 $ & $ 0.29 $ & $ 0.33 $ & $ 0.00 $ \\ $ 12.0$ & $ 1.392\times 10^{-4 } $ & $ 0.85 $& $ 1.304 $ &$ 1.47$ &$ 3.71 $& $ 4.09 $ & $ 0.77 $ & $ 0.06 $ & $ 0.28 $ & $ 0.29 $ & $ 0.00 $ \\ $ 12.0$ & $ 1.578\times 10^{-4 } $ & $ 0.75 $& $ 1.394 $ &$ 1.72$ &$ 2.71 $& $ 3.38 $ & $ 0.98 $ & $ 0.05 $ & $ 0.28 $ & $ 0.25 $ & $ 0.00 $ \\ $ 15.0$ & $ 1.741\times 10^{-4 } $ & $ 0.85 $& $ 1.349 $ &$ 1.37$ &$ 3.71 $& $ 4.06 $ & $ 0.72 $ & $ 0.34 $ & $ 0.31 $ & $ 0.30 $ & $ 0.00 $ \\ $ 15.0$ & $ 1.973\times 10^{-4 } $ & $ 0.75 $& $ 1.400 $ &$ 0.93$ &$ 2.64 $& $ 2.83 $ & $ 0.26 $ & $ 0.10 $ & $ 0.25 $ & $ 0.25 $ & $ 0.00 $ \\ $ 15.0$ & $ 2.276\times 10^{-4 } $ & $ 0.65 $& $ 1.342 $ &$ 1.80$ &$ 2.33 $& $ 2.99 $ & $ 0.37 $ & $ -0.12 $ & $ 0.26 $ & $ 0.20 $ & $ 0.00 $ \\ $ 20.0$ & $ 2.321\times 10^{-4 } $ & $ 0.85 $& $ 1.396 $ &$ 1.52$ &$ 3.73 $& $ 4.12 $ & $ 0.71 $ & $ 0.32 $ & $ 0.28 $ & $ 0.25 $ & $ 0.00 $ \\ $ 20.0$ & $ 2.630\times 10^{-4 } $ & $ 0.75 $& $ 1.439 $ &$ 0.83$ &$ 2.63 $& $ 2.92 $ & $ 0.73 $ & $ 0.50 $ & $ 0.25 $ & $ 0.21 $ & $ 0.00 $ \\ $ 20.0$ & $ 3.035\times 10^{-4 } $ & $ 0.65 $& $ 1.391 $ &$ 0.76$ &$ 2.16 $& $ 2.35 $ & $ 0.41 $ & $ 0.13 $ & $ 0.24 $ & $ 0.19 $ & $ 0.00 $ \\ $ 25.0$ & $ 2.901\times 10^{-4 } $ & $ 0.85 $& $ 1.482 $ &$ 2.46$ &$ 3.86 $& $ 4.64 $ & $ 0.65 $ & $ -0.06 $ & $ 0.32 $ & $ 0.23 $ & $ 0.00 $ \\ $ 25.0$ & $ 3.288\times 10^{-4 } $ & $ 0.75 $& $ 1.450 $ &$ 0.88$ &$ 2.64 $& $ 2.84 $ & $ 0.33 $ & $ 0.31 $ & $ 0.24 $ & $ 0.20 $ & $ 0.00 $ \\ $ 25.0$ & $ 3.794\times 10^{-4 } $ & $ 0.65 $& $ 1.469 $ &$ 0.73$ &$ 2.16 $& $ 2.40 $ & $ 0.55 $ & $ 0.43 $ & $ 0.24 $ & $ 0.19 $ & $ 0.00 $ \\ $ 25.0$ & $ 5.000\times 10^{-4 } $ & $ 0.49 $& $ 1.403 $ &$ 0.69$ &$ 1.77 $& $ 2.12 $ & $ 0.74 $ & $ 0.09 $ & $ 0.22 $ & $ 0.19 $ & $ 0.51 $ \\ $ 25.0$ & $ 8.000\times 10^{-4 } $ & $ 0.31 $& $ 1.281 $ &$ 1.10$ &$ 1.85 $& $ 2.28 $ & $ 0.70 $ & $ 0.19 $ & $ 0.10 $ & $ 0.12 $ & $ 0.08 $ \\ $ 35.0$ & $ 4.603\times 10^{-4 } $ & $ 0.75 $& $ 1.457 $ &$ 1.23$ &$ 2.68 $& $ 3.01 $ & $ 0.33 $ & $ 0.36 $ & $ 0.29 $ & $ 0.21 $ & $ 0.00 $ \\ $ 35.0$ & $ 5.311\times 10^{-4 } $ & $ 0.65 $& $ 1.483 $ &$ 0.66$ &$ 2.15 $& $ 2.34 $ & $ 0.31 $ & $ 0.43 $ & $ 0.26 $ & $ 0.19 $ & $ 0.00 $ \\ $ 35.0$ & $ 8.000\times 10^{-4 } $ & $ 0.43 $& $ 1.404 $ &$ 0.48$ &$ 1.75 $& $ 2.02 $ & $ 0.78 $ & $ 0.29 $ & $ 0.18 $ & $ 0.17 $ & $ 0.16 $ \\ $ 35.0$ & $ 1.300\times 10^{-3 } $ & $ 0.27 $& $ 1.236 $ &$ 0.63$ &$ 1.77 $& $ 1.99 $ & $ 0.64 $ & $ 0.01 $ & $ 0.01 $ & $ 0.02 $ & $ 0.01 $ \\ $ 35.0$ & $ 2.000\times 10^{-3 } $ & $ 0.17 $& $ 1.112 $ &$ 1.42$ &$ 1.93 $& $ 2.73 $ & $ 1.25 $ & $ -0.35 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 45.0$ & $ 6.341\times 10^{-4 } $ & $ 0.70 $& $ 1.470 $ &$ 1.00$ &$ 2.21 $& $ 2.58 $ & $ 0.79 $ & $ 0.28 $ & $ 0.28 $ & $ 0.18 $ & $ 0.00 $ \\ $ 45.0$ & $ 8.000\times 10^{-4 } $ & $ 0.55 $& $ 1.488 $ &$ 0.69$ &$ 2.16 $& $ 2.47 $ & $ 0.85 $ & $ 0.41 $ & $ 0.22 $ & $ 0.19 $ & $ 0.00 $ \\ $ 45.0$ & $ 1.300\times 10^{-3 } $ & $ 0.34 $& $ 1.316 $ &$ 0.45$ &$ 1.75 $& $ 1.94 $ & $ 0.50 $ & $ 0.45 $ & $ 0.08 $ & $ 0.09 $ & $ 0.04 $ \\ $ 45.0$ & $ 2.000\times 10^{-3 } $ & $ 0.22 $& $ 1.182 $ &$ 0.52$ &$ 1.76 $& $ 1.94 $ & $ 0.54 $ & $ 0.30 $ & $ 0.00 $ & $ 0.00 $ & $ 0.03 $ \\ $ 60.0$ & $ 1.302\times 10^{-3 } $ & $ 0.45 $& $ 1.419 $ &$ 0.61$ &$ 1.77 $& $ 1.97 $ & $ 0.42 $ & $ 0.35 $ & $ 0.18 $ & $ 0.14 $ & $ 0.00 $ \\ $ 60.0$ & $ 2.000\times 10^{-3 } $ & $ 0.30 $& $ 1.248 $ &$ 0.50$ &$ 1.76 $& $ 1.95 $ & $ 0.40 $ & $ 0.56 $ & $ 0.02 $ & $ 0.03 $ & $ 0.02 $ \\ $ 60.0$ & $ 3.200\times 10^{-3 } $ & $ 0.18 $& $ 1.102 $ &$ 0.71$ &$ 1.78 $& $ 2.12 $ & $ 0.83 $ & $ 0.33 $ & $ 0.00 $ & $ 0.00 $ & $ 0.02 $ \\ $ 90.0$ & $ 2.004\times 10^{-3 } $ & $ 0.44 $& $ 1.354 $ &$ 0.79$ &$ 1.80 $& $ 2.09 $ & $ 0.56 $ & $ 0.42 $ & $ 0.09 $ & $ 0.08 $ & $ 0.00 $ \\ $ 90.0$ & $ 3.200\times 10^{-3 } $ & $ 0.28 $& $ 1.183 $ &$ 0.60$ &$ 1.77 $& $ 1.95 $ & $ 0.44 $ & $ 0.32 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 90.0$ & $ 5.000\times 10^{-3 } $ & $ 0.18 $& $ 1.018 $ &$ 1.50$ &$ 1.96 $& $ 2.50 $ & $ 0.29 $ & $ 0.33 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ \hline %\hline \end{tabular} \end{center} \end{scriptsize} \tablecaption{\label{tab:cjc920} Reduced cross section $\sigma_{r}$, as measured with the {\hqcjc} data sample. Description of the columns is given in the caption of \Tab~\ref{tab:bst920}. } \end{table} \begin{table} \begin{scriptsize} \begin{center} \begin{tabular}{ccccccccccccc} \hline \\[-8pt] $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma_r}$ & $\boldsymbol{\delta_{stat}}$ & $\boldsymbol{\delta_{unc}}$& $\boldsymbol{\delta_{tot}}$ & $\boldsymbol{\gamma_{\ee}}$ & $\boldsymbol{\gamma_{\thetae}}$ & $\boldsymbol{\gamma_{had}}$ & $\boldsymbol{\gamma_{noise}}$ & $\boldsymbol{\gamma_{\rm asym}}$ & $\boldsymbol{\gamma_{acctag}}$ \\ {\bf GeV}$^2$ & & & & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \%} & {\bf \%} & {\bf \%} & {\bf \% } & {\bf \%} \\ \hline \\[-8pt] %\input{tables/h1_460_p1} $ 1.5$ & $ 3.480\times 10^{-5 } $ & $ 0.850 $& $ 0.520 $ &$ 8.10$ &$ 4.96 $& $ 10.16 $ & $ 0.69 $ & $ 0.08 $ & $ 0.45 $ & $ 0.58 $ & $ 3.47 $ & $ 0.00 $ \\ $ 2.0$ & $ 4.640\times 10^{-5 } $ & $ 0.850 $& $ 0.704 $ &$ 4.57$ &$ 4.31 $& $ 6.89 $ & $ 1.10 $ & $ -0.81 $ & $ 0.49 $ & $ 0.59 $ & $ 2.34 $ & $ 0.00 $ \\ $ 2.0$ & $ 5.260\times 10^{-5 } $ & $ 0.750 $& $ 0.717 $ &$ 4.59$ &$ 3.93 $& $ 6.38 $ & $ 1.64 $ & $ -0.64 $ & $ 0.32 $ & $ 0.45 $ & $ 0.86 $ & $ 0.00 $ \\ $ 2.5$ & $ 5.800\times 10^{-5 } $ & $ 0.850 $& $ 0.777 $ &$ 4.18$ &$ 4.16 $& $ 6.73 $ & $ 2.01 $ & $ -0.31 $ & $ 0.60 $ & $ 0.64 $ & $ 2.36 $ & $ 0.00 $ \\ $ 2.5$ & $ 6.580\times 10^{-5 } $ & $ 0.750 $& $ 0.768 $ &$ 2.64$ &$ 3.03 $& $ 4.24 $ & $ 0.91 $ & $ 0.42 $ & $ 0.42 $ & $ 0.37 $ & $ 0.74 $ & $ 0.00 $ \\ $ 2.5$ & $ 7.590\times 10^{-5 } $ & $ 0.650 $& $ 0.711 $ &$ 4.32$ &$ 3.45 $& $ 5.82 $ & $ 1.33 $ & $ -1.12 $ & $ 0.23 $ & $ 0.33 $ & $ 0.40 $ & $ 0.00 $ \\ $ 3.5$ & $ 8.120\times 10^{-5 } $ & $ 0.850 $& $ 0.794 $ &$ 4.21$ &$ 4.05 $& $ 6.41 $ & $ 0.82 $ & $ 0.62 $ & $ 0.38 $ & $ 0.57 $ & $ 2.32 $ & $ 0.00 $ \\ $ 3.5$ & $ 9.210\times 10^{-5 } $ & $ 0.750 $& $ 0.820 $ &$ 2.22$ &$ 2.86 $& $ 4.09 $ & $ 1.71 $ & $ 0.30 $ & $ 0.31 $ & $ 0.38 $ & $ 0.63 $ & $ 0.00 $ \\ $ 3.5$ & $ 1.062\times 10^{-4 } $ & $ 0.650 $& $ 0.857 $ &$ 2.03$ &$ 2.47 $& $ 3.69 $ & $ 1.73 $ & $ -0.43 $ & $ 0.32 $ & $ 0.32 $ & $ 0.26 $ & $ 0.00 $ \\ $ 3.5$ & $ 1.409\times 10^{-4 } $ & $ 0.490 $& $ 0.797 $ &$ 2.55$ &$ 2.45 $& $ 4.31 $ & $ 1.32 $ & $ -1.66 $ & $ 0.24 $ & $ 0.25 $ & $ 0.00 $ & $ 1.19 $ \\ $ 5.0$ & $ 1.160\times 10^{-4 } $ & $ 0.850 $& $ 0.939 $ &$ 4.19$ &$ 4.01 $& $ 6.60 $ & $ 1.92 $ & $ 0.46 $ & $ 0.45 $ & $ 0.51 $ & $ 2.37 $ & $ 0.00 $ \\ $ 5.0$ & $ 1.315\times 10^{-4 } $ & $ 0.750 $& $ 0.924 $ &$ 2.07$ &$ 2.80 $& $ 3.82 $ & $ 1.28 $ & $ 0.58 $ & $ 0.34 $ & $ 0.37 $ & $ 0.54 $ & $ 0.00 $ \\ $ 5.0$ & $ 1.517\times 10^{-4 } $ & $ 0.650 $& $ 0.966 $ &$ 1.69$ &$ 2.33 $& $ 3.10 $ & $ 1.02 $ & $ -0.25 $ & $ 0.25 $ & $ 0.30 $ & $ 0.21 $ & $ 0.00 $ \\ $ 5.0$ & $ 2.013\times 10^{-4 } $ & $ 0.490 $& $ 0.914 $ &$ 1.16$ &$ 1.87 $& $ 2.48 $ & $ 0.66 $ & $ -0.59 $ & $ 0.19 $ & $ 0.20 $ & $ 0.00 $ & $ 0.65 $ \\ $ 6.5$ & $ 1.509\times 10^{-4 } $ & $ 0.850 $& $ 1.034 $ &$ 4.26$ &$ 4.02 $& $ 6.55 $ & $ 0.94 $ & $ 0.88 $ & $ 0.41 $ & $ 0.50 $ & $ 2.57 $ & $ 0.00 $ \\ $ 6.5$ & $ 1.710\times 10^{-4 } $ & $ 0.750 $& $ 0.958 $ &$ 2.15$ &$ 2.80 $& $ 3.79 $ & $ 0.94 $ & $ 0.65 $ & $ 0.39 $ & $ 0.43 $ & $ 0.51 $ & $ 0.00 $ \\ $ 6.5$ & $ 1.973\times 10^{-4 } $ & $ 0.650 $& $ 1.007 $ &$ 1.60$ &$ 2.30 $& $ 2.92 $ & $ 0.64 $ & $ 0.39 $ & $ 0.23 $ & $ 0.25 $ & $ 0.17 $ & $ 0.00 $ \\ $ 6.5$ & $ 2.617\times 10^{-4 } $ & $ 0.490 $& $ 1.008 $ &$ 0.90$ &$ 1.82 $& $ 2.26 $ & $ 0.83 $ & $ 0.20 $ & $ 0.20 $ & $ 0.22 $ & $ 0.00 $ & $ 0.40 $ \\ $ 6.5$ & $ 4.136\times 10^{-4 } $ & $ 0.310 $& $ 0.962 $ &$ 1.14$ &$ 1.87 $& $ 2.44 $ & $ 1.00 $ & $ -0.39 $ & $ 0.00 $ & $ 0.01 $ & $ 0.00 $ & $ 0.00 $ \\ $ 8.5$ & $ 1.973\times 10^{-4 } $ & $ 0.850 $& $ 0.969 $ &$ 4.68$ &$ 4.01 $& $ 7.05 $ & $ 1.28 $ & $ 0.64 $ & $ 0.40 $ & $ 0.49 $ & $ 3.05 $ & $ 0.00 $ \\ $ 8.5$ & $ 2.236\times 10^{-4 } $ & $ 0.750 $& $ 1.008 $ &$ 2.38$ &$ 2.84 $& $ 3.95 $ & $ 0.92 $ & $ 0.79 $ & $ 0.21 $ & $ 0.26 $ & $ 0.59 $ & $ 0.00 $ \\ $ 8.5$ & $ 2.580\times 10^{-4 } $ & $ 0.650 $& $ 1.087 $ &$ 1.66$ &$ 2.32 $& $ 3.30 $ & $ 1.40 $ & $ 0.80 $ & $ 0.22 $ & $ 0.23 $ & $ 0.15 $ & $ 0.00 $ \\ $ 8.5$ & $ 3.422\times 10^{-4 } $ & $ 0.490 $& $ 1.051 $ &$ 0.85$ &$ 1.81 $& $ 2.25 $ & $ 0.92 $ & $ 0.18 $ & $ 0.19 $ & $ 0.21 $ & $ 0.00 $ & $ 0.31 $ \\ $ 8.5$ & $ 5.409\times 10^{-4 } $ & $ 0.310 $& $ 1.016 $ &$ 0.91$ &$ 1.82 $& $ 2.10 $ & $ 0.44 $ & $ 0.23 $ & $ 0.01 $ & $ 0.01 $ & $ 0.00 $ & $ 0.02 $ \\ $ 8.5$ & $ 8.384\times 10^{-4 } $ & $ 0.200 $& $ 0.939 $ &$ 1.01$ &$ 1.84 $& $ 2.29 $ & $ 0.90 $ & $ 0.14 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 8.5$ & $ 1.397\times 10^{-3 } $ & $ 0.120 $& $ 0.857 $ &$ 1.21$ &$ 1.89 $& $ 2.55 $ & $ 1.11 $ & $ -0.48 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 12.0$ & $ 2.785\times 10^{-4 } $ & $ 0.850 $& $ 1.127 $ &$ 3.90$ &$ 3.98 $& $ 6.07 $ & $ 0.97 $ & $ 0.19 $ & $ 0.34 $ & $ 0.41 $ & $ 2.13 $ & $ 0.00 $ \\ $ 12.0$ & $ 3.156\times 10^{-4 } $ & $ 0.750 $& $ 1.110 $ &$ 2.38$ &$ 2.85 $& $ 3.92 $ & $ 1.00 $ & $ 0.10 $ & $ 0.34 $ & $ 0.33 $ & $ 0.59 $ & $ 0.00 $ \\ $ 12.0$ & $ 3.642\times 10^{-4 } $ & $ 0.650 $& $ 1.095 $ &$ 1.86$ &$ 2.36 $& $ 3.15 $ & $ 0.58 $ & $ 0.67 $ & $ 0.22 $ & $ 0.22 $ & $ 0.18 $ & $ 0.00 $ \\ $ 12.0$ & $ 4.831\times 10^{-4 } $ & $ 0.490 $& $ 1.108 $ &$ 0.89$ &$ 1.81 $& $ 2.25 $ & $ 0.58 $ & $ 0.76 $ & $ 0.15 $ & $ 0.16 $ & $ 0.00 $ & $ 0.17 $ \\ $ 12.0$ & $ 7.636\times 10^{-4 } $ & $ 0.310 $& $ 1.028 $ &$ 0.87$ &$ 1.81 $& $ 2.22 $ & $ 0.79 $ & $ 0.50 $ & $ 0.01 $ & $ 0.01 $ & $ 0.00 $ & $ 0.01 $ \\ $ 12.0$ & $ 1.184\times 10^{-3 } $ & $ 0.200 $& $ 0.972 $ &$ 0.93$ &$ 1.83 $& $ 2.22 $ & $ 0.85 $ & $ 0.06 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 12.0$ & $ 1.973\times 10^{-3 } $ & $ 0.120 $& $ 0.880 $ &$ 1.07$ &$ 1.86 $& $ 2.57 $ & $ 1.37 $ & $ 0.34 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 15.0$ & $ 3.481\times 10^{-4 } $ & $ 0.850 $& $ 1.218 $ &$ 3.90$ &$ 4.06 $& $ 5.91 $ & $ 0.57 $ & $ 0.33 $ & $ 0.29 $ & $ 0.30 $ & $ 1.60 $ & $ 0.00 $ \\ $ 15.0$ & $ 3.945\times 10^{-4 } $ & $ 0.750 $& $ 1.109 $ &$ 2.33$ &$ 2.84 $& $ 3.77 $ & $ 0.30 $ & $ 0.36 $ & $ 0.30 $ & $ 0.31 $ & $ 0.53 $ & $ 0.00 $ \\ $ 15.0$ & $ 4.552\times 10^{-4 } $ & $ 0.650 $& $ 1.138 $ &$ 2.05$ &$ 2.40 $& $ 3.44 $ & $ 1.06 $ & $ 0.78 $ & $ 0.25 $ & $ 0.24 $ & $ 0.24 $ & $ 0.00 $ \\ $ 15.0$ & $ 6.039\times 10^{-4 } $ & $ 0.490 $& $ 1.161 $ &$ 0.96$ &$ 1.83 $& $ 2.31 $ & $ 0.87 $ & $ 0.45 $ & $ 0.20 $ & $ 0.18 $ & $ 0.00 $ & $ 0.13 $ \\ $ 15.0$ & $ 9.545\times 10^{-4 } $ & $ 0.310 $& $ 1.049 $ &$ 0.91$ &$ 1.82 $& $ 2.21 $ & $ 0.52 $ & $ 0.68 $ & $ 0.00 $ & $ 0.01 $ & $ 0.00 $ & $ 0.04 $ \\ $ 15.0$ & $ 1.479\times 10^{-3 } $ & $ 0.200 $& $ 0.939 $ &$ 0.95$ &$ 1.83 $& $ 2.28 $ & $ 0.81 $ & $ 0.55 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 15.0$ & $ 2.466\times 10^{-3 } $ & $ 0.120 $& $ 0.859 $ &$ 1.06$ &$ 1.85 $& $ 2.68 $ & $ 1.61 $ & $ 0.17 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ \hline %\hline \end{tabular} \end{center} \end{scriptsize} \tablecaption{\label{tab:ler1} Reduced cross section $\sigma_{r}$, as measured with the {\ler} data sample. The uncertainties are quoted in \% relative to $\sigma_r$. $\delta_{\rm stat}$ is the statistical uncertainty. $\delta_{\rm unc}$ represents the uncorrelated systematic uncertainty. $\delta_{\rm tot}$ is the total uncertainty determined as the quadratic sum of systematic and statistical uncertainties. $\gamma_{E_e^{\prime}}$, $\gamma_{\theta_e}$, $\gamma_{had}$, $\gamma_{\rm noise}$, $\gamma_{asym}$ and $\gamma_{\rm acctag}$ are the bin-to-bin correlated systematic uncertainties in the cross section measurement due to uncertainties in the SpaCal electromagnetic energy scale, electron scattering angle, calorimeter hadronic energy scale, LAr calorimeter noise, background charge asymmetry and electron tagger acceptance, respectively. The global normalisation uncertainty of $4$\% is not included in $\delta_{\rm tot}$. } \end{table} \begin{table} \begin{scriptsize} \begin{center} \begin{tabular}{ccccccccccccc} %\hline \hline \\[-8pt] $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma_r}$ & $\boldsymbol{\delta_{stat}}$ & $\boldsymbol{\delta_{unc}}$& $\boldsymbol{\delta_{tot}}$ & $\boldsymbol{\gamma_{\ee}}$ & $\boldsymbol{\gamma_{\thetae}}$ & $\boldsymbol{\gamma_{had}}$ & $\boldsymbol{\gamma_{noise}}$ & $\boldsymbol{\gamma_{\rm asym}}$ & $\boldsymbol{\gamma_{acctag}}$ \\ {\bf GeV}$^2$ & & & & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \%} & {\bf \%} & {\bf \%} & {\bf \% } & {\bf \%} \\ \hline \\[-8pt] %\input{tables/h1_460_p2} $ 20.0$ & $ 4.642\times 10^{-4 } $ & $ 0.850 $& $ 1.003 $ &$ 5.34$ &$ 4.21 $& $ 7.12 $ & $ 1.20 $ & $ 0.59 $ & $ 0.46 $ & $ 0.46 $ & $ 1.47 $ & $ 0.00 $ \\ $ 20.0$ & $ 5.261\times 10^{-4 } $ & $ 0.750 $& $ 1.200 $ &$ 2.27$ &$ 2.87 $& $ 3.80 $ & $ 0.88 $ & $ 0.02 $ & $ 0.28 $ & $ 0.26 $ & $ 0.36 $ & $ 0.00 $ \\ $ 20.0$ & $ 6.070\times 10^{-4 } $ & $ 0.650 $& $ 1.177 $ &$ 1.97$ &$ 2.39 $& $ 3.15 $ & $ 0.22 $ & $ 0.36 $ & $ 0.23 $ & $ 0.20 $ & $ 0.18 $ & $ 0.00 $ \\ $ 20.0$ & $ 8.052\times 10^{-4 } $ & $ 0.490 $& $ 1.166 $ &$ 1.06$ &$ 1.85 $& $ 2.45 $ & $ 0.93 $ & $ 0.69 $ & $ 0.13 $ & $ 0.14 $ & $ 0.00 $ & $ 0.25 $ \\ $ 20.0$ & $ 1.273\times 10^{-3 } $ & $ 0.310 $& $ 1.089 $ &$ 1.00$ &$ 1.84 $& $ 2.31 $ & $ 0.72 $ & $ 0.65 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.01 $ \\ $ 20.0$ & $ 1.973\times 10^{-3 } $ & $ 0.200 $& $ 0.987 $ &$ 1.02$ &$ 1.85 $& $ 2.25 $ & $ 0.56 $ & $ 0.56 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.03 $ \\ $ 20.0$ & $ 3.288\times 10^{-3 } $ & $ 0.120 $& $ 0.875 $ &$ 1.14$ &$ 1.87 $& $ 2.49 $ & $ 0.88 $ & $ 0.78 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 25.0$ & $ 6.165\times 10^{-4 } $ & $ 0.800 $& $ 1.207 $ &$ 2.42$ &$ 2.94 $& $ 3.96 $ & $ 0.23 $ & $ 0.92 $ & $ 0.33 $ & $ 0.23 $ & $ 0.36 $ & $ 0.00 $ \\ $ 25.0$ & $ 7.587\times 10^{-4 } $ & $ 0.650 $& $ 1.237 $ &$ 2.00$ &$ 2.43 $& $ 3.24 $ & $ -0.17 $ & $ 0.70 $ & $ 0.19 $ & $ 0.15 $ & $ 0.11 $ & $ 0.00 $ \\ $ 25.0$ & $ 1.007\times 10^{-3 } $ & $ 0.490 $& $ 1.190 $ &$ 1.10$ &$ 1.86 $& $ 2.42 $ & $ 0.84 $ & $ 0.61 $ & $ 0.19 $ & $ 0.18 $ & $ 0.00 $ & $ 0.26 $ \\ $ 25.0$ & $ 1.591\times 10^{-3 } $ & $ 0.310 $& $ 1.079 $ &$ 1.12$ &$ 1.87 $& $ 2.39 $ & $ 0.74 $ & $ 0.63 $ & $ 0.00 $ & $ 0.01 $ & $ 0.00 $ & $ 0.00 $ \\ $ 25.0$ & $ 2.466\times 10^{-3 } $ & $ 0.200 $& $ 0.989 $ &$ 1.15$ &$ 1.88 $& $ 2.47 $ & $ 0.64 $ & $ 0.91 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.02 $ \\ $ 25.0$ & $ 4.110\times 10^{-3 } $ & $ 0.120 $& $ 0.854 $ &$ 1.30$ &$ 1.91 $& $ 2.60 $ & $ 0.75 $ & $ 0.92 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 35.0$ & $ 9.206\times 10^{-4 } $ & $ 0.750 $& $ 1.106 $ &$ 3.84$ &$ 3.32 $& $ 5.32 $ & $ 1.47 $ & $ -0.25 $ & $ 0.46 $ & $ 0.28 $ & $ 0.19 $ & $ 0.00 $ \\ $ 35.0$ & $ 1.062\times 10^{-3 } $ & $ 0.650 $& $ 1.225 $ &$ 2.23$ &$ 2.50 $& $ 3.57 $ & $ 0.93 $ & $ 0.77 $ & $ 0.19 $ & $ 0.13 $ & $ 0.07 $ & $ 0.00 $ \\ $ 35.0$ & $ 1.409\times 10^{-3 } $ & $ 0.490 $& $ 1.195 $ &$ 1.14$ &$ 1.87 $& $ 2.37 $ & $ 0.60 $ & $ 0.59 $ & $ 0.20 $ & $ 0.16 $ & $ 0.00 $ & $ 0.20 $ \\ $ 35.0$ & $ 2.227\times 10^{-3 } $ & $ 0.310 $& $ 1.085 $ &$ 1.16$ &$ 1.88 $& $ 2.31 $ & $ 0.13 $ & $ 0.67 $ & $ 0.00 $ & $ 0.01 $ & $ 0.00 $ & $ 0.02 $ \\ $ 35.0$ & $ 3.452\times 10^{-3 } $ & $ 0.200 $& $ 0.984 $ &$ 1.27$ &$ 1.91 $& $ 2.45 $ & $ -0.05 $ & $ 0.85 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 35.0$ & $ 5.754\times 10^{-3 } $ & $ 0.120 $& $ 0.847 $ &$ 1.46$ &$ 1.96 $& $ 2.94 $ & $ 1.29 $ & $ 1.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 45.0$ & $ 1.366\times 10^{-3 } $ & $ 0.650 $& $ 1.258 $ &$ 3.13$ &$ 2.84 $& $ 4.27 $ & $ -0.15 $ & $ 0.56 $ & $ 0.19 $ & $ 0.13 $ & $ 0.06 $ & $ 0.00 $ \\ $ 45.0$ & $ 1.812\times 10^{-3 } $ & $ 0.490 $& $ 1.186 $ &$ 1.29$ &$ 1.91 $& $ 2.50 $ & $ 0.86 $ & $ 0.38 $ & $ 0.16 $ & $ 0.16 $ & $ 0.00 $ & $ 0.05 $ \\ $ 45.0$ & $ 2.864\times 10^{-3 } $ & $ 0.310 $& $ 1.081 $ &$ 1.22$ &$ 1.89 $& $ 2.30 $ & $ 0.23 $ & $ 0.40 $ & $ 0.00 $ & $ 0.01 $ & $ 0.00 $ & $ 0.00 $ \\ $ 45.0$ & $ 4.439\times 10^{-3 } $ & $ 0.200 $& $ 0.951 $ &$ 1.29$ &$ 1.91 $& $ 2.47 $ & $ 0.69 $ & $ 0.52 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 45.0$ & $ 7.398\times 10^{-3 } $ & $ 0.120 $& $ 0.806 $ &$ 1.52$ &$ 1.97 $& $ 2.84 $ & $ 1.28 $ & $ 0.48 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 60.0$ & $ 2.416\times 10^{-3 } $ & $ 0.490 $& $ 1.201 $ &$ 1.63$ &$ 2.01 $& $ 2.77 $ & $ 0.91 $ & $ 0.24 $ & $ 0.20 $ & $ 0.14 $ & $ 0.00 $ & $ 0.08 $ \\ $ 60.0$ & $ 3.818\times 10^{-3 } $ & $ 0.310 $& $ 1.038 $ &$ 1.40$ &$ 1.94 $& $ 2.45 $ & $ -0.01 $ & $ 0.55 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 60.0$ & $ 5.918\times 10^{-3 } $ & $ 0.200 $& $ 0.929 $ &$ 1.44$ &$ 1.96 $& $ 2.51 $ & $ 0.06 $ & $ 0.63 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 60.0$ & $ 9.864\times 10^{-3 } $ & $ 0.120 $& $ 0.795 $ &$ 1.63$ &$ 2.02 $& $ 2.85 $ & $ 1.00 $ & $ 0.63 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 90.0$ & $ 3.623\times 10^{-3 } $ & $ 0.490 $& $ 1.097 $ &$ 3.36$ &$ 2.72 $& $ 4.47 $ & $ 1.03 $ & $ 0.40 $ & $ 0.20 $ & $ 0.13 $ & $ 0.00 $ & $ 0.00 $ \\ $ 90.0$ & $ 5.727\times 10^{-3 } $ & $ 0.310 $& $ 0.975 $ &$ 1.76$ &$ 2.05 $& $ 2.73 $ & $ 0.23 $ & $ 0.33 $ & $ 0.01 $ & $ 0.01 $ & $ 0.00 $ & $ 0.00 $ \\ $ 90.0$ & $ 8.877\times 10^{-3 } $ & $ 0.200 $& $ 0.835 $ &$ 1.71$ &$ 2.03 $& $ 2.79 $ & $ 0.73 $ & $ 0.44 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 90.0$ & $ 1.480\times 10^{-2 } $ & $ 0.120 $& $ 0.717 $ &$ 1.90$ &$ 2.10 $& $ 2.96 $ & $ 0.68 $ & $ 0.54 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ \hline %\hline \end{tabular} \end{center} \end{scriptsize} \tablecaption{\label{tab:460p2} Continuation of \Tab~\ref{tab:ler1} } \end{table} \begin{table} \begin{scriptsize} \begin{center} \begin{tabular}{ccccccccccccc} %\hline \hline \\[-8pt] $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma_r}$ & $\boldsymbol{\delta_{stat}}$ & $\boldsymbol{\delta_{unc}}$& $\boldsymbol{\delta_{tot}}$ & $\boldsymbol{\gamma_{\ee}}$ & $\boldsymbol{\gamma_{\thetae}}$ & $\boldsymbol{\gamma_{had}}$ & $\boldsymbol{\gamma_{noise}}$ & $\boldsymbol{\gamma_{\rm asym}}$ & $\boldsymbol{\gamma_{acctag}}$ \\ {\bf GeV}$^2$ & & & & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \%} & {\bf \%} & {\bf \%} & {\bf \% } & {\bf \%} \\ \hline \\[-8pt] %\input{tables/h1_575_p1} $ 1.5$ & $ 2.790\times 10^{-5 } $ & $ 0.848 $& $ 0.662 $ &$ 9.36$ &$ 4.94 $& $ 11.36 $ & $ 2.78 $ & $ -1.16 $ & $ 0.36 $ & $ 0.53 $ & $ 2.73 $ & $ 0.00 $ \\ $ 2.0$ & $ 3.720\times 10^{-5 } $ & $ 0.848 $& $ 0.760 $ &$ 6.37$ &$ 4.34 $& $ 8.32 $ & $ 1.81 $ & $ -0.49 $ & $ 0.56 $ & $ 0.60 $ & $ 2.38 $ & $ 0.00 $ \\ $ 2.0$ & $ 4.150\times 10^{-5 } $ & $ 0.760 $& $ 0.663 $ &$ 7.43$ &$ 3.97 $& $ 8.82 $ & $ 0.86 $ & $ -2.16 $ & $ 0.26 $ & $ 0.29 $ & $ 1.10 $ & $ 0.00 $ \\ $ 2.5$ & $ 4.650\times 10^{-5 } $ & $ 0.848 $& $ 0.829 $ &$ 5.43$ &$ 4.12 $& $ 7.51 $ & $ 2.26 $ & $ 0.15 $ & $ 0.34 $ & $ 0.40 $ & $ 2.15 $ & $ 0.00 $ \\ $ 2.5$ & $ 5.190\times 10^{-5 } $ & $ 0.760 $& $ 0.837 $ &$ 3.85$ &$ 3.10 $& $ 5.20 $ & $ 1.19 $ & $ 0.59 $ & $ 0.38 $ & $ 0.46 $ & $ 0.69 $ & $ 0.00 $ \\ $ 2.5$ & $ 5.800\times 10^{-5 } $ & $ 0.680 $& $ 0.768 $ &$ 4.98$ &$ 3.14 $& $ 5.92 $ & $ 0.44 $ & $ 0.15 $ & $ 0.15 $ & $ 0.10 $ & $ 0.36 $ & $ 0.00 $ \\ $ 3.5$ & $ 6.510\times 10^{-5 } $ & $ 0.848 $& $ 0.871 $ &$ 5.56$ &$ 4.05 $& $ 7.61 $ & $ 2.33 $ & $ -0.19 $ & $ 0.50 $ & $ 0.55 $ & $ 2.13 $ & $ 0.00 $ \\ $ 3.5$ & $ 7.270\times 10^{-5 } $ & $ 0.760 $& $ 0.873 $ &$ 3.51$ &$ 2.92 $& $ 4.96 $ & $ 1.74 $ & $ 0.00 $ & $ 0.30 $ & $ 0.33 $ & $ 0.69 $ & $ 0.00 $ \\ $ 3.5$ & $ 8.120\times 10^{-5 } $ & $ 0.680 $& $ 0.869 $ &$ 3.15$ &$ 2.49 $& $ 4.54 $ & $ 1.83 $ & $ -0.89 $ & $ 0.27 $ & $ 0.26 $ & $ 0.36 $ & $ 0.00 $ \\ $ 3.5$ & $ 9.210\times 10^{-5 } $ & $ 0.600 $& $ 0.939 $ &$ 3.36$ &$ 2.66 $& $ 4.34 $ & $ 0.30 $ & $ -0.47 $ & $ 0.30 $ & $ 0.26 $ & $ 0.12 $ & $ 0.00 $ \\ $ 3.5$ & $ 1.062\times 10^{-4 } $ & $ 0.520 $& $ 0.957 $ &$ 5.39$ &$ 3.27 $& $ 6.67 $ & $ 1.22 $ & $ -1.56 $ & $ 0.07 $ & $ 0.19 $ & $ 0.00 $ & $ 0.87 $ \\ $ 5.0$ & $ 9.310\times 10^{-5 } $ & $ 0.848 $& $ 0.849 $ &$ 6.48$ &$ 3.99 $& $ 8.24 $ & $ 1.58 $ & $ 0.08 $ & $ 0.46 $ & $ 0.55 $ & $ 2.65 $ & $ 0.00 $ \\ $ 5.0$ & $ 1.038\times 10^{-4 } $ & $ 0.760 $& $ 0.883 $ &$ 3.52$ &$ 2.84 $& $ 4.68 $ & $ 0.83 $ & $ 0.05 $ & $ 0.32 $ & $ 0.39 $ & $ 0.68 $ & $ 0.00 $ \\ $ 5.0$ & $ 1.160\times 10^{-4 } $ & $ 0.680 $& $ 1.006 $ &$ 2.66$ &$ 2.37 $& $ 3.77 $ & $ 1.17 $ & $ -0.08 $ & $ 0.19 $ & $ 0.23 $ & $ 0.28 $ & $ 0.00 $ \\ $ 5.0$ & $ 1.315\times 10^{-4 } $ & $ 0.600 $& $ 0.946 $ &$ 2.60$ &$ 2.37 $& $ 3.78 $ & $ 1.35 $ & $ -0.08 $ & $ 0.20 $ & $ 0.20 $ & $ 0.14 $ & $ 0.00 $ \\ $ 5.0$ & $ 1.517\times 10^{-4 } $ & $ 0.520 $& $ 1.011 $ &$ 2.43$ &$ 2.04 $& $ 3.34 $ & $ 0.86 $ & $ -0.34 $ & $ 0.18 $ & $ 0.25 $ & $ 0.00 $ & $ 0.37 $ \\ $ 5.0$ & $ 2.013\times 10^{-4 } $ & $ 0.392 $& $ 0.940 $ &$ 2.58$ &$ 2.06 $& $ 3.50 $ & $ 0.76 $ & $ -0.82 $ & $ 0.17 $ & $ 0.23 $ & $ 0.00 $ & $ 0.00 $ \\ $ 6.5$ & $ 1.210\times 10^{-4 } $ & $ 0.848 $& $ 0.903 $ &$ 7.18$ &$ 4.03 $& $ 8.91 $ & $ 0.65 $ & $ 0.62 $ & $ 0.35 $ & $ 0.40 $ & $ 3.25 $ & $ 0.00 $ \\ $ 6.5$ & $ 1.350\times 10^{-4 } $ & $ 0.760 $& $ 0.992 $ &$ 3.48$ &$ 2.85 $& $ 4.72 $ & $ 0.98 $ & $ 0.67 $ & $ 0.29 $ & $ 0.37 $ & $ 0.56 $ & $ 0.00 $ \\ $ 6.5$ & $ 1.509\times 10^{-4 } $ & $ 0.680 $& $ 1.069 $ &$ 2.56$ &$ 2.35 $& $ 3.70 $ & $ 1.04 $ & $ 0.57 $ & $ 0.31 $ & $ 0.35 $ & $ 0.21 $ & $ 0.00 $ \\ $ 6.5$ & $ 1.710\times 10^{-4 } $ & $ 0.600 $& $ 1.048 $ &$ 2.30$ &$ 2.32 $& $ 3.40 $ & $ 0.75 $ & $ -0.46 $ & $ 0.19 $ & $ 0.19 $ & $ 0.11 $ & $ 0.00 $ \\ $ 6.5$ & $ 1.973\times 10^{-4 } $ & $ 0.520 $& $ 1.106 $ &$ 2.05$ &$ 1.96 $& $ 2.97 $ & $ 0.81 $ & $ 0.12 $ & $ 0.19 $ & $ 0.19 $ & $ 0.00 $ & $ 0.26 $ \\ $ 6.5$ & $ 2.617\times 10^{-4 } $ & $ 0.392 $& $ 1.001 $ &$ 1.38$ &$ 1.83 $& $ 2.50 $ & $ 0.95 $ & $ -0.17 $ & $ 0.10 $ & $ 0.12 $ & $ 0.00 $ & $ 0.20 $ \\ $ 8.5$ & $ 1.582\times 10^{-4 } $ & $ 0.848 $& $ 0.976 $ &$ 7.10$ &$ 4.00 $& $ 9.20 $ & $ 2.37 $ & $ 0.47 $ & $ 0.32 $ & $ 0.34 $ & $ 3.49 $ & $ 0.00 $ \\ $ 8.5$ & $ 1.765\times 10^{-4 } $ & $ 0.760 $& $ 1.072 $ &$ 3.81$ &$ 2.90 $& $ 4.92 $ & $ -0.12 $ & $ 0.87 $ & $ 0.29 $ & $ 0.28 $ & $ 0.62 $ & $ 0.00 $ \\ $ 8.5$ & $ 1.973\times 10^{-4 } $ & $ 0.680 $& $ 1.092 $ &$ 2.80$ &$ 2.39 $& $ 3.93 $ & $ 1.27 $ & $ 0.37 $ & $ 0.26 $ & $ 0.26 $ & $ 0.19 $ & $ 0.00 $ \\ $ 8.5$ & $ 2.236\times 10^{-4 } $ & $ 0.600 $& $ 1.103 $ &$ 2.32$ &$ 2.33 $& $ 3.41 $ & $ 0.60 $ & $ 0.65 $ & $ 0.19 $ & $ 0.18 $ & $ 0.09 $ & $ 0.00 $ \\ $ 8.5$ & $ 2.580\times 10^{-4 } $ & $ 0.520 $& $ 1.033 $ &$ 2.03$ &$ 1.93 $& $ 3.14 $ & $ 1.08 $ & $ 0.33 $ & $ 0.19 $ & $ 0.22 $ & $ 0.00 $ & $ 0.81 $ \\ $ 8.5$ & $ 3.422\times 10^{-4 } $ & $ 0.392 $& $ 1.087 $ &$ 1.20$ &$ 1.81 $& $ 2.29 $ & $ 0.71 $ & $ -0.01 $ & $ 0.09 $ & $ 0.11 $ & $ 0.00 $ & $ 0.02 $ \\ $ 8.5$ & $ 5.409\times 10^{-4 } $ & $ 0.248 $& $ 1.015 $ &$ 1.32$ &$ 1.83 $& $ 2.35 $ & $ 0.57 $ & $ 0.35 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 8.5$ & $ 8.384\times 10^{-4 } $ & $ 0.160 $& $ 0.941 $ &$ 1.47$ &$ 1.85 $& $ 2.56 $ & $ 0.92 $ & $ -0.33 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 8.5$ & $ 1.397\times 10^{-3 } $ & $ 0.096 $& $ 0.818 $ &$ 2.58$ &$ 2.07 $& $ 3.50 $ & $ 1.11 $ & $ -0.16 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.10 $ \\ $ 12.0$ & $ 2.233\times 10^{-4 } $ & $ 0.848 $& $ 1.238 $ &$ 5.51$ &$ 4.00 $& $ 7.51 $ & $ 2.15 $ & $ 0.15 $ & $ 0.47 $ & $ 0.34 $ & $ 2.24 $ & $ 0.00 $ \\ $ 12.0$ & $ 2.492\times 10^{-4 } $ & $ 0.760 $& $ 1.083 $ &$ 4.06$ &$ 2.91 $& $ 5.19 $ & $ 1.15 $ & $ 0.15 $ & $ 0.25 $ & $ 0.24 $ & $ 0.76 $ & $ 0.00 $ \\ $ 12.0$ & $ 2.785\times 10^{-4 } $ & $ 0.680 $& $ 1.167 $ &$ 3.07$ &$ 2.43 $& $ 4.09 $ & $ 0.29 $ & $ 1.07 $ & $ 0.26 $ & $ 0.28 $ & $ 0.24 $ & $ 0.00 $ \\ $ 12.0$ & $ 3.156\times 10^{-4 } $ & $ 0.600 $& $ 1.188 $ &$ 2.55$ &$ 2.37 $& $ 3.70 $ & $ 0.76 $ & $ 0.97 $ & $ 0.22 $ & $ 0.19 $ & $ 0.11 $ & $ 0.00 $ \\ $ 12.0$ & $ 3.642\times 10^{-4 } $ & $ 0.520 $& $ 1.175 $ &$ 2.12$ &$ 1.96 $& $ 3.03 $ & $ 0.43 $ & $ 0.64 $ & $ 0.21 $ & $ 0.20 $ & $ 0.00 $ & $ 0.40 $ \\ $ 12.0$ & $ 4.831\times 10^{-4 } $ & $ 0.392 $& $ 1.127 $ &$ 1.19$ &$ 1.81 $& $ 2.33 $ & $ 0.71 $ & $ 0.50 $ & $ 0.06 $ & $ 0.08 $ & $ 0.00 $ & $ 0.04 $ \\ $ 12.0$ & $ 7.636\times 10^{-4 } $ & $ 0.248 $& $ 1.053 $ &$ 1.23$ &$ 1.82 $& $ 2.31 $ & $ 0.64 $ & $ 0.31 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.05 $ \\ $ 12.0$ & $ 1.184\times 10^{-3 } $ & $ 0.160 $& $ 1.017 $ &$ 1.29$ &$ 1.83 $& $ 2.39 $ & $ 0.77 $ & $ 0.30 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 12.0$ & $ 1.973\times 10^{-3 } $ & $ 0.096 $& $ 0.871 $ &$ 2.25$ &$ 2.00 $& $ 3.36 $ & $ 1.48 $ & $ -0.04 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 15.0$ & $ 2.792\times 10^{-4 } $ & $ 0.848 $& $ 1.110 $ &$ 6.31$ &$ 4.04 $& $ 7.92 $ & $ 1.47 $ & $ 0.34 $ & $ 0.37 $ & $ 0.36 $ & $ 2.01 $ & $ 0.00 $ \\ $ 15.0$ & $ 3.115\times 10^{-4 } $ & $ 0.760 $& $ 1.294 $ &$ 3.40$ &$ 2.90 $& $ 4.56 $ & $ 0.47 $ & $ 0.38 $ & $ 0.33 $ & $ 0.31 $ & $ 0.48 $ & $ 0.00 $ \\ $ 15.0$ & $ 3.481\times 10^{-4 } $ & $ 0.680 $& $ 1.226 $ &$ 3.18$ &$ 2.47 $& $ 4.05 $ & $ 0.24 $ & $ 0.28 $ & $ 0.16 $ & $ 0.17 $ & $ 0.24 $ & $ 0.00 $ \\ $ 15.0$ & $ 3.945\times 10^{-4 } $ & $ 0.600 $& $ 1.156 $ &$ 2.97$ &$ 2.43 $& $ 3.96 $ & $ 0.39 $ & $ 0.81 $ & $ 0.25 $ & $ 0.21 $ & $ 0.15 $ & $ 0.00 $ \\ $ 15.0$ & $ 4.552\times 10^{-4 } $ & $ 0.520 $& $ 1.255 $ &$ 2.33$ &$ 2.01 $& $ 3.23 $ & $ 0.69 $ & $ 0.60 $ & $ 0.20 $ & $ 0.18 $ & $ 0.00 $ & $ 0.26 $ \\ $ 15.0$ & $ 6.039\times 10^{-4 } $ & $ 0.392 $& $ 1.162 $ &$ 1.29$ &$ 1.82 $& $ 2.53 $ & $ 0.95 $ & $ 0.72 $ & $ 0.08 $ & $ 0.11 $ & $ 0.00 $ & $ 0.03 $ \\ $ 15.0$ & $ 9.545\times 10^{-4 } $ & $ 0.248 $& $ 1.044 $ &$ 1.28$ &$ 1.82 $& $ 2.30 $ & $ 0.37 $ & $ 0.43 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 15.0$ & $ 1.479\times 10^{-3 } $ & $ 0.160 $& $ 0.973 $ &$ 1.32$ &$ 1.83 $& $ 2.58 $ & $ 0.99 $ & $ 0.78 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 15.0$ & $ 2.466\times 10^{-3 } $ & $ 0.096 $& $ 0.856 $ &$ 2.17$ &$ 1.98 $& $ 3.36 $ & $ 1.31 $ & $ 0.94 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.07 $ \\ \hline %\hline \end{tabular} \end{center} \end{scriptsize} \tablecaption{\label{tab:mer} Reduced cross section $\sigma_{r}$, as measured with the {\mer} data sample. Description of the columns is given in the caption of \Tab~\ref{tab:ler1}. } \end{table} \begin{table} \begin{scriptsize} \begin{center} \begin{tabular}{ccccccccccccc} %\hline \hline \\[-8pt] $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma_r}$ & $\boldsymbol{\delta_{stat}}$ & $\boldsymbol{\delta_{unc}}$& $\boldsymbol{\delta_{tot}}$ & $\boldsymbol{\gamma_{\ee}}$ & $\boldsymbol{\gamma_{\thetae}}$ & $\boldsymbol{\gamma_{had}}$ & $\boldsymbol{\gamma_{noise}}$ & $\boldsymbol{\gamma_{\rm asym}}$ & $\boldsymbol{\gamma_{acctag}}$ \\ {\bf GeV}$^2$ & & & & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \% } & {\bf \%} & {\bf \%} & {\bf \%} & {\bf \% } & {\bf \%} \\ \hline \\[-8pt] %\input{tables/h1_575_p2} $ 20.0$ & $ 3.722\times 10^{-4 } $ & $ 0.848 $& $ 1.287 $ &$ 6.59$ &$ 4.25 $& $ 8.28 $ & $ 2.28 $ & $ -0.09 $ & $ 0.32 $ & $ 0.35 $ & $ 1.27 $ & $ 0.00 $ \\ $ 20.0$ & $ 4.153\times 10^{-4 } $ & $ 0.760 $& $ 1.246 $ &$ 3.65$ &$ 2.93 $& $ 4.80 $ & $ 0.89 $ & $ 0.17 $ & $ 0.28 $ & $ 0.24 $ & $ 0.42 $ & $ 0.00 $ \\ $ 20.0$ & $ 4.642\times 10^{-4 } $ & $ 0.680 $& $ 1.293 $ &$ 3.04$ &$ 2.46 $& $ 3.95 $ & $ 0.20 $ & $ 0.47 $ & $ 0.19 $ & $ 0.17 $ & $ 0.18 $ & $ 0.00 $ \\ $ 20.0$ & $ 5.261\times 10^{-4 } $ & $ 0.600 $& $ 1.135 $ &$ 3.17$ &$ 2.46 $& $ 4.16 $ & $ 0.73 $ & $ 0.67 $ & $ 0.27 $ & $ 0.24 $ & $ 0.17 $ & $ 0.00 $ \\ $ 20.0$ & $ 6.070\times 10^{-4 } $ & $ 0.520 $& $ 1.224 $ &$ 2.57$ &$ 2.06 $& $ 3.64 $ & $ 0.65 $ & $ 1.27 $ & $ 0.21 $ & $ 0.19 $ & $ 0.00 $ & $ 0.52 $ \\ $ 20.0$ & $ 8.052\times 10^{-4 } $ & $ 0.392 $& $ 1.212 $ &$ 1.41$ &$ 1.84 $& $ 2.50 $ & $ 0.44 $ & $ 0.80 $ & $ 0.10 $ & $ 0.10 $ & $ 0.00 $ & $ 0.03 $ \\ $ 20.0$ & $ 1.273\times 10^{-3 } $ & $ 0.248 $& $ 1.093 $ &$ 1.39$ &$ 1.84 $& $ 2.53 $ & $ 0.53 $ & $ 0.89 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 20.0$ & $ 1.973\times 10^{-3 } $ & $ 0.160 $& $ 0.981 $ &$ 1.44$ &$ 1.85 $& $ 2.63 $ & $ 0.87 $ & $ 0.84 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 20.0$ & $ 3.288\times 10^{-3 } $ & $ 0.096 $& $ 0.853 $ &$ 2.39$ &$ 2.03 $& $ 3.41 $ & $ 1.28 $ & $ 0.43 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 25.0$ & $ 4.932\times 10^{-4 } $ & $ 0.800 $& $ 1.264 $ &$ 3.94$ &$ 3.02 $& $ 5.02 $ & $ 0.44 $ & $ 0.12 $ & $ 0.30 $ & $ 0.27 $ & $ 0.47 $ & $ 0.00 $ \\ $ 25.0$ & $ 6.165\times 10^{-4 } $ & $ 0.640 $& $ 1.272 $ &$ 2.19$ &$ 2.46 $& $ 3.35 $ & $ 0.41 $ & $ 0.37 $ & $ 0.27 $ & $ 0.18 $ & $ 0.12 $ & $ 0.00 $ \\ $ 25.0$ & $ 7.587\times 10^{-4 } $ & $ 0.520 $& $ 1.220 $ &$ 2.61$ &$ 2.06 $& $ 3.49 $ & $ 0.92 $ & $ 0.33 $ & $ 0.20 $ & $ 0.15 $ & $ 0.00 $ & $ 0.31 $ \\ $ 25.0$ & $ 1.007\times 10^{-3 } $ & $ 0.392 $& $ 1.228 $ &$ 1.54$ &$ 1.86 $& $ 2.58 $ & $ 0.48 $ & $ 0.74 $ & $ 0.07 $ & $ 0.10 $ & $ 0.00 $ & $ 0.11 $ \\ $ 25.0$ & $ 1.591\times 10^{-3 } $ & $ 0.248 $& $ 1.131 $ &$ 1.55$ &$ 1.87 $& $ 2.51 $ & $ 0.39 $ & $ 0.52 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.04 $ \\ $ 25.0$ & $ 2.466\times 10^{-3 } $ & $ 0.160 $& $ 1.015 $ &$ 1.58$ &$ 1.88 $& $ 2.93 $ & $ 1.22 $ & $ 1.04 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 25.0$ & $ 4.110\times 10^{-3 } $ & $ 0.096 $& $ 0.896 $ &$ 2.63$ &$ 2.11 $& $ 3.57 $ & $ 0.34 $ & $ 1.11 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 35.0$ & $ 7.268\times 10^{-4 } $ & $ 0.760 $& $ 1.438 $ &$ 6.27$ &$ 3.72 $& $ 7.52 $ & $ -1.72 $ & $ -0.48 $ & $ 0.28 $ & $ 0.19 $ & $ 0.22 $ & $ 0.00 $ \\ $ 35.0$ & $ 8.123\times 10^{-4 } $ & $ 0.680 $& $ 1.364 $ &$ 3.51$ &$ 2.60 $& $ 4.54 $ & $ 1.03 $ & $ 0.56 $ & $ 0.29 $ & $ 0.24 $ & $ 0.08 $ & $ 0.00 $ \\ $ 35.0$ & $ 9.206\times 10^{-4 } $ & $ 0.600 $& $ 1.343 $ &$ 3.12$ &$ 2.52 $& $ 4.09 $ & $ 0.31 $ & $ 0.68 $ & $ 0.26 $ & $ 0.18 $ & $ 0.06 $ & $ 0.00 $ \\ $ 35.0$ & $ 1.062\times 10^{-3 } $ & $ 0.520 $& $ 1.314 $ &$ 2.73$ &$ 2.11 $& $ 3.62 $ & $ 0.86 $ & $ 0.65 $ & $ 0.16 $ & $ 0.15 $ & $ 0.00 $ & $ 0.11 $ \\ $ 35.0$ & $ 1.409\times 10^{-3 } $ & $ 0.392 $& $ 1.254 $ &$ 1.55$ &$ 1.87 $& $ 2.55 $ & $ 0.54 $ & $ 0.54 $ & $ 0.08 $ & $ 0.11 $ & $ 0.00 $ & $ 0.00 $ \\ $ 35.0$ & $ 2.227\times 10^{-3 } $ & $ 0.248 $& $ 1.111 $ &$ 1.68$ &$ 1.89 $& $ 2.68 $ & $ 0.62 $ & $ 0.63 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 35.0$ & $ 3.452\times 10^{-3 } $ & $ 0.160 $& $ 0.967 $ &$ 1.83$ &$ 1.91 $& $ 2.77 $ & $ 0.32 $ & $ 0.75 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 35.0$ & $ 5.754\times 10^{-3 } $ & $ 0.096 $& $ 0.851 $ &$ 3.01$ &$ 2.20 $& $ 4.23 $ & $ 1.90 $ & $ 0.60 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 45.0$ & $ 1.044\times 10^{-3 } $ & $ 0.680 $& $ 1.274 $ &$ 6.36$ &$ 3.42 $& $ 7.23 $ & $ 0.24 $ & $ 0.30 $ & $ 0.17 $ & $ 0.09 $ & $ 0.06 $ & $ 0.00 $ \\ $ 45.0$ & $ 1.184\times 10^{-3 } $ & $ 0.600 $& $ 1.266 $ &$ 3.80$ &$ 2.68 $& $ 4.71 $ & $ 0.32 $ & $ 0.54 $ & $ 0.31 $ & $ 0.22 $ & $ 0.04 $ & $ 0.00 $ \\ $ 45.0$ & $ 1.366\times 10^{-3 } $ & $ 0.520 $& $ 1.291 $ &$ 3.08$ &$ 2.20 $& $ 3.81 $ & $ 0.29 $ & $ 0.11 $ & $ 0.20 $ & $ 0.13 $ & $ 0.00 $ & $ 0.14 $ \\ $ 45.0$ & $ 1.812\times 10^{-3 } $ & $ 0.392 $& $ 1.193 $ &$ 1.70$ &$ 1.89 $& $ 2.64 $ & $ 0.40 $ & $ 0.56 $ & $ 0.09 $ & $ 0.10 $ & $ 0.00 $ & $ 0.04 $ \\ $ 45.0$ & $ 2.864\times 10^{-3 } $ & $ 0.248 $& $ 1.106 $ &$ 1.71$ &$ 1.90 $& $ 2.64 $ & $ 0.29 $ & $ 0.60 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 45.0$ & $ 4.439\times 10^{-3 } $ & $ 0.160 $& $ 0.942 $ &$ 1.87$ &$ 1.92 $& $ 2.86 $ & $ 0.48 $ & $ 0.89 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 45.0$ & $ 7.398\times 10^{-3 } $ & $ 0.096 $& $ 0.822 $ &$ 3.15$ &$ 2.23 $& $ 4.33 $ & $ 1.63 $ & $ 1.11 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 60.0$ & $ 1.578\times 10^{-3 } $ & $ 0.600 $& $ 1.286 $ &$ 8.41$ &$ 4.22 $& $ 9.57 $ & $ 1.69 $ & $ 0.28 $ & $ 0.00 $ & $ 0.07 $ & $ 0.04 $ & $ 0.00 $ \\ $ 60.0$ & $ 1.821\times 10^{-3 } $ & $ 0.520 $& $ 1.263 $ &$ 4.23$ &$ 2.54 $& $ 4.98 $ & $ 0.23 $ & $ 0.63 $ & $ 0.10 $ & $ 0.12 $ & $ 0.00 $ & $ 0.00 $ \\ $ 60.0$ & $ 2.416\times 10^{-3 } $ & $ 0.392 $& $ 1.167 $ &$ 1.96$ &$ 1.94 $& $ 2.78 $ & $ 0.28 $ & $ 0.18 $ & $ 0.06 $ & $ 0.06 $ & $ 0.00 $ & $ 0.00 $ \\ $ 60.0$ & $ 3.818\times 10^{-3 } $ & $ 0.248 $& $ 1.018 $ &$ 1.98$ &$ 1.94 $& $ 2.84 $ & $ 0.35 $ & $ 0.50 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.06 $ \\ $ 60.0$ & $ 5.918\times 10^{-3 } $ & $ 0.160 $& $ 0.992 $ &$ 1.97$ &$ 1.96 $& $ 2.93 $ & $ 0.75 $ & $ 0.53 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 60.0$ & $ 9.864\times 10^{-3 } $ & $ 0.096 $& $ 0.777 $ &$ 3.38$ &$ 2.30 $& $ 4.23 $ & $ 0.14 $ & $ 1.07 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 90.0$ & $ 3.623\times 10^{-3 } $ & $ 0.392 $& $ 1.147 $ &$ 2.91$ &$ 2.17 $& $ 3.67 $ & $ -0.05 $ & $ 0.51 $ & $ 0.07 $ & $ 0.09 $ & $ 0.00 $ & $ 0.00 $ \\ $ 90.0$ & $ 5.727\times 10^{-3 } $ & $ 0.248 $& $ 0.921 $ &$ 2.37$ &$ 2.01 $& $ 3.16 $ & $ 0.55 $ & $ 0.18 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 90.0$ & $ 8.877\times 10^{-3 } $ & $ 0.160 $& $ 0.869 $ &$ 2.31$ &$ 2.02 $& $ 3.20 $ & $ 0.78 $ & $ 0.49 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ $ 90.0$ & $ 1.480\times 10^{-2 } $ & $ 0.096 $& $ 0.755 $ &$ 3.84$ &$ 2.47 $& $ 4.63 $ & $ 0.68 $ & $ 0.34 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ & $ 0.00 $ \\ \hline %\hline \end{tabular} \end{center} \end{scriptsize} \tablecaption{ Continuation of \Tab~\ref{tab:mer} \label{tab:h1575last}} \end{table} \begin{table} \begin{tiny} \begin{center} %\input{tabhead} \begin{tabular}{l|cccccccccc} \hline \\[-6pt] {\bf Bin} & $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma^{\rm ave}_{r}}$ & $\boldsymbol{F_2^{\rm ave}}$ & $\boldsymbol{\delta_{\rm ave,stat}}$ & $\boldsymbol{\delta_{\rm ave,uncor}}$ & $\boldsymbol{\delta_{\rm ave,cor}}$ & $\boldsymbol{\delta_{\rm ave,tot}}$ & $\boldsymbol{\sqrt{s}}$\\ $\boldsymbol{\#}$ & {\bf GeV}$\boldsymbol{^2}$ & & & & & {\bf \%} & {\bf \%} & \% & {\bf \%} & {\bf GeV} \\ \hline \\[-7pt] %\input{tables/p_1_615} $ 1 $ &$ 0.2 $ &$ 0.398 \times 10^{-4}$ & $ 0.050 $ &$ 0.232 $ &$ 0.232 $ &$ 14.27 $ &$ 11.96 $ &$ 6.97 $ &$19.88$ & $ 319$ \\ $ 2 $ &$ 0.2 $ &$ 0.251 \times 10^{-3}$ & $ 0.008 $ &$ 0.190 $ &$ 0.190 $ &$ 13.12 $ &$ 6.18 $ &$ 3.89 $ &$15.01$ & $ 319$ \\ $ 3 $ &$ 0.25 $ &$ 0.398 \times 10^{-4}$ & $ 0.062 $ &$ 0.302 $ &$ 0.302 $ &$ 9.79 $ &$ 11.26 $ &$ 7.48 $ &$16.69$ & $ 319$ \\ $ 4 $ &$ 0.25 $ &$ 0.251 \times 10^{-3}$ & $ 0.010 $ &$ 0.191 $ &$ 0.191 $ &$ 10.00 $ &$ 4.70 $ &$ 4.78 $ &$12.03$ & $ 319$ \\ $ 5 $ &$ 0.25 $ &$ 0.158 \times 10^{-2}$ & $ 0.002 $ &$ 0.204 $ &$ 0.204 $ &$ 10.84 $ &$ 5.29 $ &$ 2.69 $ &$12.35$ & $ 319$ \\ $ 6 $ &$ 0.35 $ &$ 0.511 \times 10^{-5}$ & $ 0.675 $ &$ 0.452 $ &$ 0.494 $ &$ 21.67 $ &$ 12.79 $ &$ 2.28 $ &$25.27$ & $ 319$ \\ $ 7 $ &$ 0.35 $ &$ 0.611 \times 10^{-5}$ & $ 0.634 $ &$ 0.359 $ &$ 0.387 $ &$ 5.73 $ &$ 11.03 $ &$ 5.25 $ &$13.49$ & $ 301$ \\ $ 8 $ &$ 0.35 $ &$ 0.320 \times 10^{-4}$ & $ 0.108 $ &$ 0.416 $ &$ 0.416 $ &$ 9.06 $ &$ 11.10 $ &$ 14.08 $ &$20.09$ & $ 319$ \\ $ 9 $ &$ 0.35 $ &$ 0.130 \times 10^{-3}$ & $ 0.027 $ &$ 0.266 $ &$ 0.266 $ &$ 9.59 $ &$ 4.38 $ &$ 2.94 $ &$10.95$ & $ 319$ \\ $ 10 $ &$ 0.35 $ &$ 0.500 \times 10^{-3}$ & $ 0.007 $ &$ 0.237 $ &$ 0.237 $ &$ 8.80 $ &$ 4.19 $ &$ 2.51 $ &$10.06$ & $ 319$ \\ $ 11 $ &$ 0.35 $ &$ 0.251 \times 10^{-2}$ & $ 0.001 $ &$ 0.205 $ &$ 0.205 $ &$ 9.91 $ &$ 4.55 $ &$ 1.82 $ &$11.06$ & $ 319$ \\ $ 12 $ &$ 0.5 $ &$ 0.731 \times 10^{-5}$ & $ 0.675 $ &$ 0.453 $ &$ 0.495 $ &$ 5.40 $ &$ 5.74 $ &$ 4.97 $ &$ 9.32$ & $ 319$ \\ $ 13 $ &$ 0.5 $ &$ 0.860 \times 10^{-5}$ & $ 0.650 $ &$ 0.444 $ &$ 0.481 $ &$ 3.74 $ &$ 9.17 $ &$ 4.01 $ &$10.68$ & $ 301$ \\ $ 14 $ &$ 0.5 $ &$ 0.158 \times 10^{-4}$ & $ 0.312 $ &$ 0.463 $ &$ 0.470 $ &$ 18.93 $ &$ 9.84 $ &$ 3.07 $ &$21.56$ & $ 319$ \\ $ 15 $ &$ 0.5 $ &$ 0.398 \times 10^{-4}$ & $ 0.124 $ &$ 0.484 $ &$ 0.485 $ &$ 10.08 $ &$ 6.07 $ &$ 10.88 $ &$16.03$ & $ 319$ \\ $ 16 $ &$ 0.5 $ &$ 0.100 \times 10^{-3}$ & $ 0.049 $ &$ 0.412 $ &$ 0.412 $ &$ 8.83 $ &$ 4.87 $ &$ 3.09 $ &$10.55$ & $ 319$ \\ $ 17 $ &$ 0.5 $ &$ 0.251 \times 10^{-3}$ & $ 0.020 $ &$ 0.297 $ &$ 0.297 $ &$ 8.33 $ &$ 4.25 $ &$ 2.61 $ &$ 9.71$ & $ 319$ \\ $ 18 $ &$ 0.5 $ &$ 0.800 \times 10^{-3}$ & $ 0.006 $ &$ 0.281 $ &$ 0.281 $ &$ 5.88 $ &$ 3.49 $ &$ 1.69 $ &$ 7.04$ & $ 319$ \\ $ 19 $ &$ 0.5 $ &$ 0.320 \times 10^{-2}$ & $ 0.002 $ &$ 0.183 $ &$ 0.183 $ &$ 11.37 $ &$ 6.39 $ &$ 1.37 $ &$13.11$ & $ 319$ \\ $ 20 $ &$ 0.65 $ &$ 0.950 \times 10^{-5}$ & $ 0.675 $ &$ 0.482 $ &$ 0.527 $ &$ 3.95 $ &$ 2.90 $ &$ 3.02 $ &$ 5.76$ & $ 319$ \\ $ 21 $ &$ 0.65 $ &$ 0.112 \times 10^{-4}$ & $ 0.650 $ &$ 0.506 $ &$ 0.549 $ &$ 3.73 $ &$ 8.21 $ &$ 4.04 $ &$ 9.88$ & $ 301$ \\ $ 22 $ &$ 0.65 $ &$ 0.158 \times 10^{-4}$ & $ 0.406 $ &$ 0.468 $ &$ 0.480 $ &$ 3.08 $ &$ 5.44 $ &$ 1.70 $ &$ 6.48$ & $ 319$ \\ $ 23 $ &$ 0.65 $ &$ 0.164 \times 10^{-4}$ & $ 0.439 $ &$ 0.512 $ &$ 0.528 $ &$ 3.01 $ &$ 7.28 $ &$ 2.66 $ &$ 8.31$ & $ 301$ \\ $ 24 $ &$ 0.65 $ &$ 0.398 \times 10^{-4}$ & $ 0.161 $ &$ 0.681 $ &$ 0.683 $ &$ 17.43 $ &$ 11.16 $ &$ 4.24 $ &$21.13$ & $ 319$ \\ $ 25 $ &$ 0.65 $ &$ 0.100 \times 10^{-3}$ & $ 0.064 $ &$ 0.501 $ &$ 0.501 $ &$ 5.14 $ &$ 5.84 $ &$ 7.32 $ &$10.68$ & $ 319$ \\ $ 26 $ &$ 0.65 $ &$ 0.251 \times 10^{-3}$ & $ 0.026 $ &$ 0.378 $ &$ 0.378 $ &$ 6.78 $ &$ 3.48 $ &$ 2.25 $ &$ 7.94$ & $ 319$ \\ $ 27 $ &$ 0.65 $ &$ 0.800 \times 10^{-3}$ & $ 0.008 $ &$ 0.309 $ &$ 0.309 $ &$ 4.91 $ &$ 3.06 $ &$ 2.09 $ &$ 6.15$ & $ 319$ \\ $ 28 $ &$ 0.65 $ &$ 0.320 \times 10^{-2}$ & $ 0.002 $ &$ 0.226 $ &$ 0.226 $ &$ 5.79 $ &$ 3.19 $ &$ 1.35 $ &$ 6.75$ & $ 319$ \\ $ 29 $ &$ 0.85 $ &$ 0.124 \times 10^{-4}$ & $ 0.675 $ &$ 0.569 $ &$ 0.621 $ &$ 2.54 $ &$ 2.52 $ &$ 2.56 $ &$ 4.40$ & $ 319$ \\ $ 30 $ &$ 0.85 $ &$ 0.138 \times 10^{-4}$ & $ 0.675 $ &$ 0.617 $ &$ 0.675 $ &$ 5.19 $ &$ 9.45 $ &$ 5.62 $ &$12.16$ & $ 301$ \\ $ 31 $ &$ 0.85 $ &$ 0.200 \times 10^{-4}$ & $ 0.470 $ &$ 0.598 $ &$ 0.620 $ &$ 2.64 $ &$ 4.98 $ &$ 2.72 $ &$ 6.26$ & $ 301$ \\ $ 32 $ &$ 0.85 $ &$ 0.200 \times 10^{-4}$ & $ 0.419 $ &$ 0.614 $ &$ 0.631 $ &$ 1.95 $ &$ 5.36 $ &$ 1.75 $ &$ 5.97$ & $ 319$ \\ $ 33 $ &$ 0.85 $ &$ 0.398 \times 10^{-4}$ & $ 0.211 $ &$ 0.569 $ &$ 0.572 $ &$ 1.58 $ &$ 3.49 $ &$ 1.61 $ &$ 4.15$ & $ 319$ \\ $ 34 $ &$ 0.85 $ &$ 0.500 \times 10^{-4}$ & $ 0.168 $ &$ 0.548 $ &$ 0.550 $ &$ 2.91 $ &$ 4.52 $ &$ 2.54 $ &$ 5.95$ & $ 319$ \\ $ 35 $ &$ 0.85 $ &$ 0.100 \times 10^{-3}$ & $ 0.084 $ &$ 0.501 $ &$ 0.502 $ &$ 2.65 $ &$ 3.78 $ &$ 3.72 $ &$ 5.93$ & $ 319$ \\ $ 36 $ &$ 0.85 $ &$ 0.251 \times 10^{-3}$ & $ 0.033 $ &$ 0.415 $ &$ 0.415 $ &$ 5.88 $ &$ 2.98 $ &$ 3.08 $ &$ 7.28$ & $ 319$ \\ $ 37 $ &$ 0.85 $ &$ 0.800 \times 10^{-3}$ & $ 0.010 $ &$ 0.352 $ &$ 0.352 $ &$ 4.59 $ &$ 2.67 $ &$ 1.66 $ &$ 5.56$ & $ 319$ \\ $ 38 $ &$ 0.85 $ &$ 0.320 \times 10^{-2}$ & $ 0.003 $ &$ 0.308 $ &$ 0.308 $ &$ 4.54 $ &$ 2.83 $ &$ 1.14 $ &$ 5.47$ & $ 301$ \\ $ 39 $ &$ 1.2 $ &$ 0.176 \times 10^{-4}$ & $ 0.675 $ &$ 0.613 $ &$ 0.670 $ &$ 2.51 $ &$ 2.16 $ &$ 2.90 $ &$ 4.40$ & $ 319$ \\ $ 40 $ &$ 1.2 $ &$ 0.200 \times 10^{-4}$ & $ 0.675 $ &$ 0.744 $ &$ 0.813 $ &$ 3.59 $ &$ 8.36 $ &$ 4.07 $ &$ 9.97$ & $ 301$ \\ $ 41 $ &$ 1.2 $ &$ 0.200 \times 10^{-4}$ & $ 0.592 $ &$ 0.675 $ &$ 0.719 $ &$ 2.61 $ &$ 2.51 $ &$ 1.45 $ &$ 3.90$ & $ 319$ \\ $ 42 $ &$ 1.2 $ &$ 0.320 \times 10^{-4}$ & $ 0.415 $ &$ 0.708 $ &$ 0.727 $ &$ 2.67 $ &$ 4.55 $ &$ 2.44 $ &$ 5.81$ & $ 301$ \\ $ 43 $ &$ 1.2 $ &$ 0.320 \times 10^{-4}$ & $ 0.370 $ &$ 0.692 $ &$ 0.706 $ &$ 1.67 $ &$ 2.73 $ &$ 1.45 $ &$ 3.51$ & $ 319$ \\ $ 44 $ &$ 1.2 $ &$ 0.631 \times 10^{-4}$ & $ 0.188 $ &$ 0.649 $ &$ 0.652 $ &$ 1.18 $ &$ 2.27 $ &$ 1.71 $ &$ 3.08$ & $ 319$ \\ $ 45 $ &$ 1.2 $ &$ 0.800 \times 10^{-4}$ & $ 0.148 $ &$ 0.596 $ &$ 0.598 $ &$ 2.18 $ &$ 4.03 $ &$ 2.52 $ &$ 5.22$ & $ 319$ \\ $ 46 $ &$ 1.2 $ &$ 0.130 \times 10^{-3}$ & $ 0.091 $ &$ 0.544 $ &$ 0.545 $ &$ 2.42 $ &$ 4.97 $ &$ 1.64 $ &$ 5.76$ & $ 319$ \\ $ 47 $ &$ 1.2 $ &$ 0.158 \times 10^{-3}$ & $ 0.075 $ &$ 0.506 $ &$ 0.506 $ &$ 1.54 $ &$ 2.35 $ &$ 1.46 $ &$ 3.17$ & $ 319$ \\ $ 48 $ &$ 1.2 $ &$ 0.398 \times 10^{-3}$ & $ 0.030 $ &$ 0.503 $ &$ 0.503 $ &$ 2.09 $ &$ 3.37 $ &$ 1.63 $ &$ 4.29$ & $ 319$ \\ $ 49 $ &$ 1.2 $ &$ 0.130 \times 10^{-2}$ & $ 0.009 $ &$ 0.375 $ &$ 0.375 $ &$ 3.54 $ &$ 2.67 $ &$ 1.61 $ &$ 4.72$ & $ 319$ \\ $ 50 $ &$ 1.2 $ &$ 0.500 \times 10^{-2}$ & $ 0.002 $ &$ 0.298 $ &$ 0.298 $ &$ 4.50 $ &$ 2.61 $ &$ 1.64 $ &$ 5.46$ & $ 319$ \\ $ 51 $ &$ 1.5 $ &$ 0.185 \times 10^{-4}$ & $ 0.800 $ &$ 0.621 $ &$ 0.711 $ &$ 3.14 $ &$ 3.48 $ &$ 4.33 $ &$ 6.38$ & $ 319$ \\ $ 52 $ &$ 1.5 $ &$ 0.219 \times 10^{-4}$ & $ 0.675 $ &$ 0.707 $ &$ 0.773 $ &$ 1.93 $ &$ 1.79 $ &$ 1.60 $ &$ 3.08$ & $ 319$ \\ $ 53 $ &$ 1.5 $ &$ 0.320 \times 10^{-4}$ & $ 0.519 $ &$ 0.805 $ &$ 0.843 $ &$ 1.19 $ &$ 3.20 $ &$ 2.85 $ &$ 4.45$ & $ 301$ \\ $ 54 $ &$ 1.5 $ &$ 0.320 \times 10^{-4}$ & $ 0.462 $ &$ 0.759 $ &$ 0.786 $ &$ 1.73 $ &$ 2.15 $ &$ 1.24 $ &$ 3.02$ & $ 319$ \\ $ 55 $ &$ 1.5 $ &$ 0.500 \times 10^{-4}$ & $ 0.296 $ &$ 0.762 $ &$ 0.772 $ &$ 1.04 $ &$ 1.98 $ &$ 1.29 $ &$ 2.58$ & $ 319$ \\ $ 56 $ &$ 1.5 $ &$ 0.800 \times 10^{-4}$ & $ 0.185 $ &$ 0.702 $ &$ 0.705 $ &$ 1.26 $ &$ 2.15 $ &$ 1.52 $ &$ 2.92$ & $ 319$ \\ $ 57 $ &$ 1.5 $ &$ 0.130 \times 10^{-3}$ & $ 0.114 $ &$ 0.645 $ &$ 0.646 $ &$ 1.46 $ &$ 2.43 $ &$ 1.68 $ &$ 3.29$ & $ 319$ \\ $ 58 $ &$ 1.5 $ &$ 0.200 \times 10^{-3}$ & $ 0.074 $ &$ 0.617 $ &$ 0.618 $ &$ 2.07 $ &$ 2.86 $ &$ 1.78 $ &$ 3.95$ & $ 319$ \\ $ 59 $ &$ 1.5 $ &$ 0.320 \times 10^{-3}$ & $ 0.046 $ &$ 0.586 $ &$ 0.586 $ &$ 1.48 $ &$ 2.26 $ &$ 1.85 $ &$ 3.27$ & $ 319$ \\ $ 60 $ &$ 1.5 $ &$ 0.500 \times 10^{-3}$ & $ 0.030 $ &$ 0.550 $ &$ 0.550 $ &$ 2.51 $ &$ 7.05 $ &$ 1.94 $ &$ 7.73$ & $ 319$ \\ $ 61 $ &$ 1.5 $ &$ 0.800 \times 10^{-3}$ & $ 0.018 $ &$ 0.497 $ &$ 0.497 $ &$ 2.35 $ &$ 2.47 $ &$ 1.63 $ &$ 3.78$ & $ 319$ \\ $ 62 $ &$ 1.5 $ &$ 0.100 \times 10^{-2}$ & $ 0.015 $ &$ 0.465 $ &$ 0.465 $ &$ 5.21 $ &$ 3.74 $ &$ 1.50 $ &$ 6.58$ & $ 319$ \\ $ 63 $ &$ 1.5 $ &$ 0.320 \times 10^{-2}$ & $ 0.005 $ &$ 0.410 $ &$ 0.410 $ &$ 2.31 $ &$ 2.04 $ &$ 1.59 $ &$ 3.47$ & $ 301$ \\ $ 64 $ &$ 1.5 $ &$ 0.130 \times 10^{-1}$ & $ 0.001 $ &$ 0.327 $ &$ 0.327 $ &$ 3.99 $ &$ 2.49 $ &$ 5.17 $ &$ 6.99$ & $ 319$ \\ \hline \end{tabular} \end{center} \end{tiny} \tablecaption{\label{tab615a1} %\small Combined reduced cross section $\sigma_{r}$ for $E_p=920$~GeV and $E_p=820$~GeV. $F_2^{\rm ave}$ represents the structure function $F_2$ calculated from $\sigma^{\rm ave}_{r}$ by using $R=0.26$. $\delta_{\rm ave,stat}$, $\delta_{\rm ave,uncor}$, $\delta_{\rm ave,cor}$ and $\delta_{\rm ave,tot}$ represent the statistical, uncorrelated systematic, correlated systematic and total experimental uncertainty, respectively. The uncertainties are quoted in percent relative to $\sigma^{\rm ave}_{r}$. The overall normalisation uncertainty of $0.5\%$ is not included. } \end{table} \begin{table} \begin{tiny} \begin{center} %\input{tabhead} \begin{tabular}{l|cccccccccc} \hline \\[-6pt] {\bf Bin} & $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma^{\rm ave}_{r}}$ & $\boldsymbol{F_2^{\rm ave}}$ & $\boldsymbol{\delta_{\rm ave,stat}}$ & $\boldsymbol{\delta_{\rm ave,uncor}}$ & $\boldsymbol{\delta_{\rm ave,cor}}$ & $\boldsymbol{\delta_{\rm ave,tot}}$ & $\boldsymbol{\sqrt{s}}$\\ $\boldsymbol{\#}$ & {\bf GeV}$\boldsymbol{^2}$ & & & & & {\bf \%} & {\bf \%} & \% & {\bf \%} & {\bf GeV} \\ \hline \\[-7pt] %\input{tables/p_2_615} $ 65 $ &$ 2. $ &$ 0.247 \times 10^{-4}$ & $ 0.800 $ &$ 0.788 $ &$ 0.903 $ &$ 2.30 $ &$ 2.70 $ &$ 3.33 $ &$ 4.86$ & $ 319$ \\ $ 66 $ &$ 2. $ &$ 0.295 \times 10^{-4}$ & $ 0.675 $ &$ 0.798 $ &$ 0.872 $ &$ 1.48 $ &$ 1.65 $ &$ 1.43 $ &$ 2.64$ & $ 319$ \\ $ 67 $ &$ 2. $ &$ 0.328 \times 10^{-4}$ & $ 0.675 $ &$ 0.843 $ &$ 0.922 $ &$ 1.40 $ &$ 5.32 $ &$ 3.10 $ &$ 6.32$ & $ 301$ \\ $ 68 $ &$ 2. $ &$ 0.500 \times 10^{-4}$ & $ 0.443 $ &$ 0.860 $ &$ 0.887 $ &$ 0.80 $ &$ 2.49 $ &$ 1.41 $ &$ 2.97$ & $ 301$ \\ $ 69 $ &$ 2. $ &$ 0.500 \times 10^{-4}$ & $ 0.395 $ &$ 0.828 $ &$ 0.848 $ &$ 1.52 $ &$ 1.94 $ &$ 1.05 $ &$ 2.67$ & $ 319$ \\ $ 70 $ &$ 2. $ &$ 0.800 \times 10^{-4}$ & $ 0.247 $ &$ 0.771 $ &$ 0.778 $ &$ 0.80 $ &$ 1.70 $ &$ 1.06 $ &$ 2.16$ & $ 319$ \\ $ 71 $ &$ 2. $ &$ 0.130 \times 10^{-3}$ & $ 0.152 $ &$ 0.729 $ &$ 0.731 $ &$ 0.98 $ &$ 1.73 $ &$ 1.13 $ &$ 2.29$ & $ 319$ \\ $ 72 $ &$ 2. $ &$ 0.200 \times 10^{-3}$ & $ 0.099 $ &$ 0.681 $ &$ 0.682 $ &$ 0.95 $ &$ 1.85 $ &$ 1.36 $ &$ 2.48$ & $ 319$ \\ $ 73 $ &$ 2. $ &$ 0.320 \times 10^{-3}$ & $ 0.062 $ &$ 0.635 $ &$ 0.636 $ &$ 1.00 $ &$ 1.65 $ &$ 1.52 $ &$ 2.46$ & $ 319$ \\ $ 74 $ &$ 2. $ &$ 0.500 \times 10^{-3}$ & $ 0.039 $ &$ 0.580 $ &$ 0.580 $ &$ 1.17 $ &$ 2.04 $ &$ 1.54 $ &$ 2.81$ & $ 319$ \\ $ 75 $ &$ 2. $ &$ 0.100 \times 10^{-2}$ & $ 0.020 $ &$ 0.511 $ &$ 0.511 $ &$ 0.98 $ &$ 1.79 $ &$ 1.23 $ &$ 2.39$ & $ 319$ \\ $ 76 $ &$ 2. $ &$ 0.320 \times 10^{-2}$ & $ 0.006 $ &$ 0.425 $ &$ 0.425 $ &$ 1.07 $ &$ 1.90 $ &$ 1.66 $ &$ 2.74$ & $ 319$ \\ $ 77 $ &$ 2. $ &$ 0.130 \times 10^{-1}$ & $ 0.002 $ &$ 0.361 $ &$ 0.361 $ &$ 2.38 $ &$ 2.13 $ &$ 4.27 $ &$ 5.33$ & $ 319$ \\ $ 78 $ &$ 2.5 $ &$ 0.309 \times 10^{-4}$ & $ 0.800 $ &$ 0.836 $ &$ 0.958 $ &$ 1.98 $ &$ 1.89 $ &$ 1.72 $ &$ 3.23$ & $ 319$ \\ $ 79 $ &$ 2.5 $ &$ 0.379 \times 10^{-4}$ & $ 0.650 $ &$ 0.871 $ &$ 0.944 $ &$ 2.17 $ &$ 2.09 $ &$ 1.32 $ &$ 3.29$ & $ 319$ \\ $ 80 $ &$ 2.5 $ &$ 0.410 \times 10^{-4}$ & $ 0.675 $ &$ 0.925 $ &$ 1.011 $ &$ 1.56 $ &$ 6.21 $ &$ 2.73 $ &$ 6.96$ & $ 301$ \\ $ 81 $ &$ 2.5 $ &$ 0.500 \times 10^{-4}$ & $ 0.553 $ &$ 0.899 $ &$ 0.949 $ &$ 1.19 $ &$ 2.09 $ &$ 1.95 $ &$ 3.10$ & $ 301$ \\ $ 82 $ &$ 2.5 $ &$ 0.500 \times 10^{-4}$ & $ 0.493 $ &$ 0.866 $ &$ 0.902 $ &$ 1.50 $ &$ 1.65 $ &$ 0.99 $ &$ 2.44$ & $ 319$ \\ $ 83 $ &$ 2.5 $ &$ 0.800 \times 10^{-4}$ & $ 0.308 $ &$ 0.859 $ &$ 0.871 $ &$ 0.66 $ &$ 1.19 $ &$ 0.97 $ &$ 1.67$ & $ 319$ \\ $ 84 $ &$ 2.5 $ &$ 0.130 \times 10^{-3}$ & $ 0.190 $ &$ 0.798 $ &$ 0.802 $ &$ 0.70 $ &$ 1.16 $ &$ 1.01 $ &$ 1.69$ & $ 319$ \\ $ 85 $ &$ 2.5 $ &$ 0.200 \times 10^{-3}$ & $ 0.123 $ &$ 0.760 $ &$ 0.761 $ &$ 0.76 $ &$ 1.61 $ &$ 1.03 $ &$ 2.06$ & $ 319$ \\ $ 86 $ &$ 2.5 $ &$ 0.320 \times 10^{-3}$ & $ 0.077 $ &$ 0.673 $ &$ 0.674 $ &$ 0.79 $ &$ 1.75 $ &$ 1.17 $ &$ 2.25$ & $ 319$ \\ $ 87 $ &$ 2.5 $ &$ 0.500 \times 10^{-3}$ & $ 0.049 $ &$ 0.631 $ &$ 0.632 $ &$ 0.76 $ &$ 1.47 $ &$ 1.20 $ &$ 2.05$ & $ 319$ \\ $ 88 $ &$ 2.5 $ &$ 0.800 \times 10^{-3}$ & $ 0.031 $ &$ 0.580 $ &$ 0.580 $ &$ 0.87 $ &$ 1.84 $ &$ 1.00 $ &$ 2.27$ & $ 319$ \\ $ 89 $ &$ 2.5 $ &$ 0.158 \times 10^{-2}$ & $ 0.016 $ &$ 0.536 $ &$ 0.536 $ &$ 0.68 $ &$ 1.63 $ &$ 1.12 $ &$ 2.09$ & $ 319$ \\ $ 90 $ &$ 2.5 $ &$ 0.500 \times 10^{-2}$ & $ 0.005 $ &$ 0.440 $ &$ 0.440 $ &$ 0.74 $ &$ 1.82 $ &$ 1.63 $ &$ 2.55$ & $ 319$ \\ $ 91 $ &$ 2.5 $ &$ 0.200 \times 10^{-1}$ & $ 0.001 $ &$ 0.342 $ &$ 0.342 $ &$ 2.52 $ &$ 2.45 $ &$ 7.94 $ &$ 8.68$ & $ 319$ \\ $ 92 $ &$ 3.5 $ &$ 0.432 \times 10^{-4}$ & $ 0.800 $ &$ 0.917 $ &$ 1.050 $ &$ 2.03 $ &$ 1.87 $ &$ 1.64 $ &$ 3.22$ & $ 319$ \\ $ 93 $ &$ 3.5 $ &$ 0.512 \times 10^{-4}$ & $ 0.675 $ &$ 0.928 $ &$ 1.015 $ &$ 1.77 $ &$ 1.72 $ &$ 1.15 $ &$ 2.72$ & $ 319$ \\ $ 94 $ &$ 3.5 $ &$ 0.574 \times 10^{-4}$ & $ 0.675 $ &$ 0.935 $ &$ 1.022 $ &$ 1.99 $ &$ 6.18 $ &$ 2.39 $ &$ 6.92$ & $ 301$ \\ $ 95 $ &$ 3.5 $ &$ 0.800 \times 10^{-4}$ & $ 0.484 $ &$ 0.953 $ &$ 0.991 $ &$ 1.00 $ &$ 1.76 $ &$ 1.70 $ &$ 2.64$ & $ 301$ \\ $ 96 $ &$ 3.5 $ &$ 0.800 \times 10^{-4}$ & $ 0.432 $ &$ 0.958 $ &$ 0.986 $ &$ 1.25 $ &$ 1.55 $ &$ 0.91 $ &$ 2.19$ & $ 319$ \\ $ 97 $ &$ 3.5 $ &$ 0.130 \times 10^{-3}$ & $ 0.266 $ &$ 0.921 $ &$ 0.930 $ &$ 0.65 $ &$ 1.06 $ &$ 0.91 $ &$ 1.54$ & $ 319$ \\ $ 98 $ &$ 3.5 $ &$ 0.200 \times 10^{-3}$ & $ 0.173 $ &$ 0.863 $ &$ 0.866 $ &$ 0.69 $ &$ 1.07 $ &$ 0.94 $ &$ 1.58$ & $ 319$ \\ $ 99 $ &$ 3.5 $ &$ 0.320 \times 10^{-3}$ & $ 0.108 $ &$ 0.803 $ &$ 0.804 $ &$ 0.73 $ &$ 1.13 $ &$ 0.95 $ &$ 1.65$ & $ 319$ \\ $ 100 $ &$ 3.5 $ &$ 0.500 \times 10^{-3}$ & $ 0.069 $ &$ 0.762 $ &$ 0.762 $ &$ 0.82 $ &$ 1.33 $ &$ 1.02 $ &$ 1.86$ & $ 319$ \\ $ 101 $ &$ 3.5 $ &$ 0.800 \times 10^{-3}$ & $ 0.043 $ &$ 0.663 $ &$ 0.664 $ &$ 0.67 $ &$ 1.17 $ &$ 0.97 $ &$ 1.65$ & $ 319$ \\ $ 102 $ &$ 3.5 $ &$ 0.130 \times 10^{-2}$ & $ 0.027 $ &$ 0.628 $ &$ 0.628 $ &$ 0.86 $ &$ 1.38 $ &$ 1.06 $ &$ 1.94$ & $ 319$ \\ $ 103 $ &$ 3.5 $ &$ 0.251 \times 10^{-2}$ & $ 0.014 $ &$ 0.558 $ &$ 0.558 $ &$ 0.62 $ &$ 1.12 $ &$ 1.00 $ &$ 1.63$ & $ 319$ \\ $ 104 $ &$ 3.5 $ &$ 0.800 \times 10^{-2}$ & $ 0.004 $ &$ 0.449 $ &$ 0.449 $ &$ 0.68 $ &$ 1.56 $ &$ 1.51 $ &$ 2.28$ & $ 319$ \\ $ 105 $ &$ 5. $ &$ 0.618 \times 10^{-4}$ & $ 0.800 $ &$ 1.000 $ &$ 1.146 $ &$ 1.99 $ &$ 1.85 $ &$ 1.60 $ &$ 3.15$ & $ 319$ \\ $ 106 $ &$ 5. $ &$ 0.732 \times 10^{-4}$ & $ 0.675 $ &$ 1.082 $ &$ 1.183 $ &$ 1.16 $ &$ 1.59 $ &$ 1.03 $ &$ 2.22$ & $ 319$ \\ $ 107 $ &$ 5. $ &$ 0.819 \times 10^{-4}$ & $ 0.675 $ &$ 1.052 $ &$ 1.149 $ &$ 2.07 $ &$ 4.85 $ &$ 2.96 $ &$ 6.05$ & $ 301$ \\ $ 108 $ &$ 5. $ &$ 0.130 \times 10^{-3}$ & $ 0.426 $ &$ 1.057 $ &$ 1.088 $ &$ 1.02 $ &$ 1.68 $ &$ 1.07 $ &$ 2.24$ & $ 301$ \\ $ 109 $ &$ 5. $ &$ 0.130 \times 10^{-3}$ & $ 0.379 $ &$ 1.066 $ &$ 1.089 $ &$ 1.33 $ &$ 1.67 $ &$ 0.94 $ &$ 2.33$ & $ 319$ \\ $ 110 $ &$ 5. $ &$ 0.200 \times 10^{-3}$ & $ 0.247 $ &$ 1.015 $ &$ 1.023 $ &$ 0.73 $ &$ 1.20 $ &$ 0.95 $ &$ 1.69$ & $ 319$ \\ $ 111 $ &$ 5. $ &$ 0.320 \times 10^{-3}$ & $ 0.154 $ &$ 0.934 $ &$ 0.937 $ &$ 0.79 $ &$ 1.29 $ &$ 0.89 $ &$ 1.75$ & $ 319$ \\ $ 112 $ &$ 5. $ &$ 0.500 \times 10^{-3}$ & $ 0.099 $ &$ 0.842 $ &$ 0.843 $ &$ 0.80 $ &$ 1.29 $ &$ 0.91 $ &$ 1.77$ & $ 319$ \\ $ 113 $ &$ 5. $ &$ 0.800 \times 10^{-3}$ & $ 0.062 $ &$ 0.755 $ &$ 0.756 $ &$ 0.82 $ &$ 1.29 $ &$ 0.93 $ &$ 1.79$ & $ 319$ \\ $ 114 $ &$ 5. $ &$ 0.130 \times 10^{-2}$ & $ 0.038 $ &$ 0.698 $ &$ 0.698 $ &$ 0.85 $ &$ 1.31 $ &$ 1.05 $ &$ 1.88$ & $ 319$ \\ $ 115 $ &$ 5. $ &$ 0.200 \times 10^{-2}$ & $ 0.025 $ &$ 0.642 $ &$ 0.642 $ &$ 0.88 $ &$ 1.31 $ &$ 0.95 $ &$ 1.84$ & $ 319$ \\ $ 116 $ &$ 5. $ &$ 0.398 \times 10^{-2}$ & $ 0.012 $ &$ 0.571 $ &$ 0.571 $ &$ 0.67 $ &$ 1.23 $ &$ 1.06 $ &$ 1.75$ & $ 319$ \\ $ 117 $ &$ 5. $ &$ 0.130 \times 10^{-1}$ & $ 0.004 $ &$ 0.439 $ &$ 0.439 $ &$ 0.71 $ &$ 1.86 $ &$ 1.62 $ &$ 2.56$ & $ 319$ \\ $ 118 $ &$ 6.5 $ &$ 0.803 \times 10^{-4}$ & $ 0.800 $ &$ 1.092 $ &$ 1.251 $ &$ 1.98 $ &$ 1.80 $ &$ 1.39 $ &$ 3.02$ & $ 319$ \\ $ 119 $ &$ 6.5 $ &$ 0.951 \times 10^{-4}$ & $ 0.675 $ &$ 1.110 $ &$ 1.213 $ &$ 1.72 $ &$ 1.65 $ &$ 1.16 $ &$ 2.66$ & $ 319$ \\ $ 120 $ &$ 6.5 $ &$ 0.130 \times 10^{-3}$ & $ 0.553 $ &$ 1.129 $ &$ 1.192 $ &$ 1.53 $ &$ 1.73 $ &$ 1.91 $ &$ 2.99$ & $ 301$ \\ $ 121 $ &$ 6.5 $ &$ 0.130 \times 10^{-3}$ & $ 0.493 $ &$ 1.125 $ &$ 1.172 $ &$ 1.12 $ &$ 1.43 $ &$ 0.99 $ &$ 2.07$ & $ 319$ \\ $ 122 $ &$ 6.5 $ &$ 0.200 \times 10^{-3}$ & $ 0.360 $ &$ 1.122 $ &$ 1.143 $ &$ 1.09 $ &$ 1.62 $ &$ 1.02 $ &$ 2.20$ & $ 301$ \\ $ 123 $ &$ 6.5 $ &$ 0.200 \times 10^{-3}$ & $ 0.321 $ &$ 1.109 $ &$ 1.125 $ &$ 1.05 $ &$ 1.46 $ &$ 0.99 $ &$ 2.05$ & $ 319$ \\ $ 124 $ &$ 6.5 $ &$ 0.320 \times 10^{-3}$ & $ 0.200 $ &$ 1.016 $ &$ 1.021 $ &$ 0.81 $ &$ 1.08 $ &$ 0.87 $ &$ 1.61$ & $ 319$ \\ $ 125 $ &$ 6.5 $ &$ 0.500 \times 10^{-3}$ & $ 0.128 $ &$ 0.939 $ &$ 0.941 $ &$ 0.84 $ &$ 1.28 $ &$ 0.94 $ &$ 1.79$ & $ 319$ \\ $ 126 $ &$ 6.5 $ &$ 0.800 \times 10^{-3}$ & $ 0.080 $ &$ 0.858 $ &$ 0.859 $ &$ 0.86 $ &$ 1.28 $ &$ 1.00 $ &$ 1.83$ & $ 319$ \\ $ 127 $ &$ 6.5 $ &$ 0.130 \times 10^{-2}$ & $ 0.049 $ &$ 0.760 $ &$ 0.760 $ &$ 0.89 $ &$ 1.28 $ &$ 0.94 $ &$ 1.82$ & $ 319$ \\ $ 128 $ &$ 6.5 $ &$ 0.200 \times 10^{-2}$ & $ 0.032 $ &$ 0.696 $ &$ 0.696 $ &$ 0.91 $ &$ 1.30 $ &$ 0.95 $ &$ 1.84$ & $ 319$ \\ $ 129 $ &$ 6.5 $ &$ 0.398 \times 10^{-2}$ & $ 0.016 $ &$ 0.618 $ &$ 0.618 $ &$ 0.67 $ &$ 1.21 $ &$ 1.02 $ &$ 1.71$ & $ 319$ \\ $ 130 $ &$ 6.5 $ &$ 0.130 \times 10^{-1}$ & $ 0.005 $ &$ 0.483 $ &$ 0.483 $ &$ 0.68 $ &$ 1.82 $ &$ 1.40 $ &$ 2.39$ & $ 319$ \\ \hline \end{tabular} \end{center} \end{tiny} \tablecaption{\label{tab615a2}Continuation of \Tab~\ref{tab615a1}} %\small \end{table} \begin{table} \begin{tiny} \begin{center} %\input{tabhead} \begin{tabular}{l|cccccccccc} \hline \\[-6pt] {\bf Bin} & $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma^{\rm ave}_{r}}$ & $\boldsymbol{F_2^{\rm ave}}$ & $\boldsymbol{\delta_{\rm ave,stat}}$ & $\boldsymbol{\delta_{\rm ave,uncor}}$ & $\boldsymbol{\delta_{\rm ave,cor}}$ & $\boldsymbol{\delta_{\rm ave,tot}}$ & $\boldsymbol{\sqrt{s}}$\\ $\boldsymbol{\#}$ & {\bf GeV}$\boldsymbol{^2}$ & & & & & {\bf \%} & {\bf \%} & \% & {\bf \%} & {\bf GeV} \\ \hline \\[-7pt] %\input{tables/p_3_615} $ 131 $ &$ 8.5 $ &$ 0.986 \times 10^{-4}$ & $ 0.850 $ &$ 1.158 $ &$ 1.355 $ &$ 2.32 $ &$ 2.99 $ &$ 0.96 $ &$ 3.90$ & $ 319$ \\ $ 132 $ &$ 8.5 $ &$ 0.105 \times 10^{-3}$ & $ 0.800 $ &$ 1.143 $ &$ 1.310 $ &$ 2.47 $ &$ 2.00 $ &$ 1.27 $ &$ 3.42$ & $ 319$ \\ $ 133 $ &$ 8.5 $ &$ 0.124 \times 10^{-3}$ & $ 0.675 $ &$ 1.214 $ &$ 1.326 $ &$ 1.36 $ &$ 1.60 $ &$ 1.07 $ &$ 2.36$ & $ 319$ \\ $ 134 $ &$ 8.5 $ &$ 0.139 \times 10^{-3}$ & $ 0.675 $ &$ 1.140 $ &$ 1.246 $ &$ 2.06 $ &$ 1.82 $ &$ 3.58 $ &$ 4.51$ & $ 301$ \\ $ 135 $ &$ 8.5 $ &$ 0.200 \times 10^{-3}$ & $ 0.470 $ &$ 1.186 $ &$ 1.230 $ &$ 1.38 $ &$ 1.64 $ &$ 1.40 $ &$ 2.56$ & $ 301$ \\ $ 136 $ &$ 8.5 $ &$ 0.200 \times 10^{-3}$ & $ 0.419 $ &$ 1.203 $ &$ 1.237 $ &$ 0.96 $ &$ 1.40 $ &$ 0.99 $ &$ 1.96$ & $ 319$ \\ $ 137 $ &$ 8.5 $ &$ 0.320 \times 10^{-3}$ & $ 0.262 $ &$ 1.120 $ &$ 1.130 $ &$ 0.75 $ &$ 1.04 $ &$ 0.89 $ &$ 1.56$ & $ 319$ \\ $ 138 $ &$ 8.5 $ &$ 0.500 \times 10^{-3}$ & $ 0.168 $ &$ 1.037 $ &$ 1.041 $ &$ 0.91 $ &$ 1.21 $ &$ 0.90 $ &$ 1.76$ & $ 319$ \\ $ 139 $ &$ 8.5 $ &$ 0.800 \times 10^{-3}$ & $ 0.105 $ &$ 0.954 $ &$ 0.955 $ &$ 0.93 $ &$ 1.30 $ &$ 0.91 $ &$ 1.84$ & $ 319$ \\ $ 140 $ &$ 8.5 $ &$ 0.130 \times 10^{-2}$ & $ 0.064 $ &$ 0.844 $ &$ 0.844 $ &$ 0.97 $ &$ 1.31 $ &$ 0.96 $ &$ 1.89$ & $ 319$ \\ $ 141 $ &$ 8.5 $ &$ 0.200 \times 10^{-2}$ & $ 0.042 $ &$ 0.775 $ &$ 0.775 $ &$ 0.98 $ &$ 1.32 $ &$ 0.93 $ &$ 1.89$ & $ 319$ \\ $ 142 $ &$ 8.5 $ &$ 0.320 \times 10^{-2}$ & $ 0.026 $ &$ 0.665 $ &$ 0.665 $ &$ 1.03 $ &$ 1.33 $ &$ 0.98 $ &$ 1.94$ & $ 319$ \\ $ 143 $ &$ 8.5 $ &$ 0.631 \times 10^{-2}$ & $ 0.013 $ &$ 0.606 $ &$ 0.606 $ &$ 0.76 $ &$ 1.25 $ &$ 0.99 $ &$ 1.77$ & $ 319$ \\ $ 144 $ &$ 8.5 $ &$ 0.200 \times 10^{-1}$ & $ 0.004 $ &$ 0.457 $ &$ 0.457 $ &$ 0.83 $ &$ 1.85 $ &$ 1.70 $ &$ 2.64$ & $ 319$ \\ $ 145 $ &$ 12. $ &$ 0.139 \times 10^{-3}$ & $ 0.850 $ &$ 1.278 $ &$ 1.497 $ &$ 1.78 $ &$ 2.91 $ &$ 0.95 $ &$ 3.55$ & $ 319$ \\ $ 146 $ &$ 12. $ &$ 0.158 \times 10^{-3}$ & $ 0.750 $ &$ 1.360 $ &$ 1.526 $ &$ 1.63 $ &$ 2.02 $ &$ 0.90 $ &$ 2.75$ & $ 319$ \\ $ 147 $ &$ 12. $ &$ 0.161 \times 10^{-3}$ & $ 0.825 $ &$ 1.229 $ &$ 1.423 $ &$ 4.12 $ &$ 3.78 $ &$ 1.13 $ &$ 5.70$ & $ 301$ \\ $ 148 $ &$ 12. $ &$ 0.200 \times 10^{-3}$ & $ 0.675 $ &$ 1.271 $ &$ 1.389 $ &$ 0.88 $ &$ 2.15 $ &$ 2.53 $ &$ 3.44$ & $ 301$ \\ $ 149 $ &$ 12. $ &$ 0.200 \times 10^{-3}$ & $ 0.592 $ &$ 1.281 $ &$ 1.365 $ &$ 0.95 $ &$ 0.71 $ &$ 1.50 $ &$ 1.92$ & $ 319$ \\ $ 150 $ &$ 12. $ &$ 0.320 \times 10^{-3}$ & $ 0.415 $ &$ 1.228 $ &$ 1.261 $ &$ 0.57 $ &$ 1.73 $ &$ 1.10 $ &$ 2.13$ & $ 301$ \\ $ 151 $ &$ 12. $ &$ 0.320 \times 10^{-3}$ & $ 0.370 $ &$ 1.228 $ &$ 1.253 $ &$ 0.86 $ &$ 0.68 $ &$ 0.89 $ &$ 1.42$ & $ 319$ \\ $ 152 $ &$ 12. $ &$ 0.500 \times 10^{-3}$ & $ 0.237 $ &$ 1.158 $ &$ 1.166 $ &$ 0.54 $ &$ 0.76 $ &$ 0.88 $ &$ 1.28$ & $ 319$ \\ $ 153 $ &$ 12. $ &$ 0.800 \times 10^{-3}$ & $ 0.148 $ &$ 1.058 $ &$ 1.061 $ &$ 0.72 $ &$ 0.63 $ &$ 0.78 $ &$ 1.23$ & $ 319$ \\ $ 154 $ &$ 12. $ &$ 0.130 \times 10^{-2}$ & $ 0.091 $ &$ 0.925 $ &$ 0.926 $ &$ 1.08 $ &$ 1.32 $ &$ 0.91 $ &$ 1.93$ & $ 319$ \\ $ 155 $ &$ 12. $ &$ 0.200 \times 10^{-2}$ & $ 0.059 $ &$ 0.863 $ &$ 0.864 $ &$ 1.09 $ &$ 1.35 $ &$ 0.90 $ &$ 1.96$ & $ 319$ \\ $ 156 $ &$ 12. $ &$ 0.320 \times 10^{-2}$ & $ 0.037 $ &$ 0.759 $ &$ 0.759 $ &$ 1.12 $ &$ 1.36 $ &$ 0.90 $ &$ 1.98$ & $ 319$ \\ $ 157 $ &$ 12. $ &$ 0.631 \times 10^{-2}$ & $ 0.019 $ &$ 0.648 $ &$ 0.648 $ &$ 0.85 $ &$ 1.26 $ &$ 0.98 $ &$ 1.81$ & $ 319$ \\ $ 158 $ &$ 12. $ &$ 0.200 \times 10^{-1}$ & $ 0.006 $ &$ 0.491 $ &$ 0.491 $ &$ 0.90 $ &$ 1.85 $ &$ 1.39 $ &$ 2.48$ & $ 319$ \\ $ 159 $ &$ 15. $ &$ 0.174 \times 10^{-3}$ & $ 0.850 $ &$ 1.335 $ &$ 1.563 $ &$ 1.38 $ &$ 3.71 $ &$ 1.07 $ &$ 4.10$ & $ 319$ \\ $ 160 $ &$ 15. $ &$ 0.197 \times 10^{-3}$ & $ 0.750 $ &$ 1.387 $ &$ 1.557 $ &$ 0.93 $ &$ 2.64 $ &$ 1.06 $ &$ 3.00$ & $ 319$ \\ $ 161 $ &$ 15. $ &$ 0.201 \times 10^{-3}$ & $ 0.825 $ &$ 1.262 $ &$ 1.461 $ &$ 3.20 $ &$ 3.61 $ &$ 1.13 $ &$ 4.96$ & $ 301$ \\ $ 162 $ &$ 15. $ &$ 0.228 \times 10^{-3}$ & $ 0.650 $ &$ 1.329 $ &$ 1.440 $ &$ 1.81 $ &$ 2.33 $ &$ 1.07 $ &$ 3.14$ & $ 319$ \\ $ 163 $ &$ 15. $ &$ 0.247 \times 10^{-3}$ & $ 0.675 $ &$ 1.361 $ &$ 1.488 $ &$ 0.92 $ &$ 2.17 $ &$ 1.67 $ &$ 2.89$ & $ 301$ \\ $ 164 $ &$ 15. $ &$ 0.320 \times 10^{-3}$ & $ 0.519 $ &$ 1.300 $ &$ 1.362 $ &$ 0.68 $ &$ 1.97 $ &$ 1.28 $ &$ 2.45$ & $ 301$ \\ $ 165 $ &$ 15. $ &$ 0.320 \times 10^{-3}$ & $ 0.462 $ &$ 1.312 $ &$ 1.358 $ &$ 0.85 $ &$ 0.70 $ &$ 1.16 $ &$ 1.60$ & $ 319$ \\ $ 166 $ &$ 15. $ &$ 0.500 \times 10^{-3}$ & $ 0.296 $ &$ 1.219 $ &$ 1.233 $ &$ 0.45 $ &$ 0.74 $ &$ 0.86 $ &$ 1.22$ & $ 319$ \\ $ 167 $ &$ 15. $ &$ 0.800 \times 10^{-3}$ & $ 0.185 $ &$ 1.113 $ &$ 1.118 $ &$ 0.46 $ &$ 0.70 $ &$ 0.88 $ &$ 1.22$ & $ 319$ \\ $ 168 $ &$ 15. $ &$ 0.130 \times 10^{-2}$ & $ 0.114 $ &$ 0.987 $ &$ 0.988 $ &$ 0.49 $ &$ 0.74 $ &$ 0.96 $ &$ 1.31$ & $ 319$ \\ $ 169 $ &$ 15. $ &$ 0.200 \times 10^{-2}$ & $ 0.074 $ &$ 0.879 $ &$ 0.880 $ &$ 0.51 $ &$ 0.75 $ &$ 1.07 $ &$ 1.40$ & $ 319$ \\ $ 170 $ &$ 15. $ &$ 0.320 \times 10^{-2}$ & $ 0.046 $ &$ 0.794 $ &$ 0.794 $ &$ 0.56 $ &$ 0.78 $ &$ 0.98 $ &$ 1.37$ & $ 319$ \\ $ 171 $ &$ 15. $ &$ 0.500 \times 10^{-2}$ & $ 0.030 $ &$ 0.725 $ &$ 0.725 $ &$ 0.59 $ &$ 0.79 $ &$ 0.99 $ &$ 1.40$ & $ 319$ \\ $ 172 $ &$ 15. $ &$ 0.100 \times 10^{-1}$ & $ 0.015 $ &$ 0.607 $ &$ 0.607 $ &$ 0.50 $ &$ 0.72 $ &$ 0.94 $ &$ 1.29$ & $ 319$ \\ $ 173 $ &$ 15. $ &$ 0.251 \times 10^{-1}$ & $ 0.006 $ &$ 0.503 $ &$ 0.503 $ &$ 0.67 $ &$ 1.77 $ &$ 1.71 $ &$ 2.56$ & $ 319$ \\ $ 174 $ &$ 20. $ &$ 0.232 \times 10^{-3}$ & $ 0.850 $ &$ 1.382 $ &$ 1.618 $ &$ 1.53 $ &$ 3.73 $ &$ 1.05 $ &$ 4.16$ & $ 319$ \\ $ 175 $ &$ 20. $ &$ 0.263 \times 10^{-3}$ & $ 0.750 $ &$ 1.425 $ &$ 1.600 $ &$ 0.83 $ &$ 2.63 $ &$ 1.07 $ &$ 2.96$ & $ 319$ \\ $ 176 $ &$ 20. $ &$ 0.268 \times 10^{-3}$ & $ 0.825 $ &$ 1.327 $ &$ 1.536 $ &$ 3.25 $ &$ 3.67 $ &$ 1.12 $ &$ 5.03$ & $ 301$ \\ $ 177 $ &$ 20. $ &$ 0.304 \times 10^{-3}$ & $ 0.650 $ &$ 1.377 $ &$ 1.493 $ &$ 0.76 $ &$ 2.16 $ &$ 1.03 $ &$ 2.51$ & $ 319$ \\ $ 178 $ &$ 20. $ &$ 0.329 \times 10^{-3}$ & $ 0.675 $ &$ 1.401 $ &$ 1.531 $ &$ 1.04 $ &$ 2.10 $ &$ 1.41 $ &$ 2.74$ & $ 301$ \\ $ 179 $ &$ 20. $ &$ 0.500 \times 10^{-3}$ & $ 0.443 $ &$ 1.315 $ &$ 1.357 $ &$ 0.64 $ &$ 1.71 $ &$ 1.01 $ &$ 2.09$ & $ 301$ \\ $ 180 $ &$ 20. $ &$ 0.500 \times 10^{-3}$ & $ 0.395 $ &$ 1.309 $ &$ 1.341 $ &$ 0.74 $ &$ 0.70 $ &$ 0.88 $ &$ 1.34$ & $ 319$ \\ $ 181 $ &$ 20. $ &$ 0.800 \times 10^{-3}$ & $ 0.247 $ &$ 1.203 $ &$ 1.213 $ &$ 0.44 $ &$ 0.68 $ &$ 0.86 $ &$ 1.18$ & $ 319$ \\ $ 182 $ &$ 20. $ &$ 0.130 \times 10^{-2}$ & $ 0.152 $ &$ 1.081 $ &$ 1.084 $ &$ 0.46 $ &$ 0.68 $ &$ 0.89 $ &$ 1.21$ & $ 319$ \\ $ 183 $ &$ 20. $ &$ 0.200 \times 10^{-2}$ & $ 0.099 $ &$ 0.974 $ &$ 0.976 $ &$ 0.49 $ &$ 0.70 $ &$ 0.98 $ &$ 1.30$ & $ 319$ \\ $ 184 $ &$ 20. $ &$ 0.320 \times 10^{-2}$ & $ 0.062 $ &$ 0.860 $ &$ 0.860 $ &$ 0.52 $ &$ 0.71 $ &$ 0.95 $ &$ 1.29$ & $ 319$ \\ $ 185 $ &$ 20. $ &$ 0.500 \times 10^{-2}$ & $ 0.039 $ &$ 0.771 $ &$ 0.771 $ &$ 0.55 $ &$ 0.73 $ &$ 0.93 $ &$ 1.30$ & $ 319$ \\ $ 186 $ &$ 20. $ &$ 0.100 \times 10^{-1}$ & $ 0.020 $ &$ 0.650 $ &$ 0.650 $ &$ 0.45 $ &$ 0.66 $ &$ 0.99 $ &$ 1.27$ & $ 319$ \\ $ 187 $ &$ 20. $ &$ 0.251 \times 10^{-1}$ & $ 0.008 $ &$ 0.522 $ &$ 0.522 $ &$ 0.55 $ &$ 1.76 $ &$ 1.38 $ &$ 2.30$ & $ 319$ \\ $ 188 $ &$ 25. $ &$ 0.290 \times 10^{-3}$ & $ 0.850 $ &$ 1.466 $ &$ 1.716 $ &$ 2.47 $ &$ 3.86 $ &$ 1.06 $ &$ 4.71$ & $ 319$ \\ $ 189 $ &$ 25. $ &$ 0.329 \times 10^{-3}$ & $ 0.750 $ &$ 1.436 $ &$ 1.612 $ &$ 0.88 $ &$ 2.64 $ &$ 1.04 $ &$ 2.97$ & $ 319$ \\ $ 190 $ &$ 25. $ &$ 0.335 \times 10^{-3}$ & $ 0.825 $ &$ 1.399 $ &$ 1.620 $ &$ 4.10 $ &$ 3.92 $ &$ 1.11 $ &$ 5.78$ & $ 301$ \\ $ 191 $ &$ 25. $ &$ 0.379 \times 10^{-3}$ & $ 0.650 $ &$ 1.455 $ &$ 1.577 $ &$ 0.73 $ &$ 2.16 $ &$ 1.04 $ &$ 2.51$ & $ 319$ \\ $ 192 $ &$ 25. $ &$ 0.411 \times 10^{-3}$ & $ 0.675 $ &$ 1.401 $ &$ 1.531 $ &$ 1.16 $ &$ 2.10 $ &$ 1.34 $ &$ 2.75$ & $ 301$ \\ $ 193 $ &$ 25. $ &$ 0.500 \times 10^{-3}$ & $ 0.553 $ &$ 1.370 $ &$ 1.446 $ &$ 1.04 $ &$ 1.88 $ &$ 1.08 $ &$ 2.40$ & $ 301$ \\ $ 194 $ &$ 25. $ &$ 0.500 \times 10^{-3}$ & $ 0.493 $ &$ 1.390 $ &$ 1.447 $ &$ 0.70 $ &$ 0.74 $ &$ 0.94 $ &$ 1.39$ & $ 319$ \\ $ 195 $ &$ 25. $ &$ 0.800 \times 10^{-3}$ & $ 0.308 $ &$ 1.271 $ &$ 1.289 $ &$ 0.44 $ &$ 0.67 $ &$ 0.85 $ &$ 1.16$ & $ 319$ \\ $ 196 $ &$ 25. $ &$ 0.130 \times 10^{-2}$ & $ 0.190 $ &$ 1.138 $ &$ 1.143 $ &$ 0.47 $ &$ 0.69 $ &$ 0.87 $ &$ 1.20$ & $ 319$ \\ $ 197 $ &$ 25. $ &$ 0.200 \times 10^{-2}$ & $ 0.123 $ &$ 1.029 $ &$ 1.031 $ &$ 0.51 $ &$ 0.69 $ &$ 0.91 $ &$ 1.25$ & $ 319$ \\ $ 198 $ &$ 25. $ &$ 0.320 \times 10^{-2}$ & $ 0.077 $ &$ 0.910 $ &$ 0.910 $ &$ 0.52 $ &$ 0.70 $ &$ 0.97 $ &$ 1.31$ & $ 319$ \\ $ 199 $ &$ 25. $ &$ 0.500 \times 10^{-2}$ & $ 0.049 $ &$ 0.797 $ &$ 0.797 $ &$ 0.54 $ &$ 0.70 $ &$ 0.96 $ &$ 1.30$ & $ 319$ \\ $ 200 $ &$ 25. $ &$ 0.800 \times 10^{-2}$ & $ 0.031 $ &$ 0.703 $ &$ 0.703 $ &$ 0.58 $ &$ 0.71 $ &$ 0.94 $ &$ 1.31$ & $ 319$ \\ $ 201 $ &$ 25. $ &$ 0.130 \times 10^{-1}$ & $ 0.019 $ &$ 0.636 $ &$ 0.636 $ &$ 0.55 $ &$ 0.73 $ &$ 1.05 $ &$ 1.39$ & $ 319$ \\ $ 202 $ &$ 25. $ &$ 0.200 \times 10^{-1}$ & $ 0.012 $ &$ 0.581 $ &$ 0.581 $ &$ 0.84 $ &$ 0.77 $ &$ 1.20 $ &$ 1.66$ & $ 319$ \\ $ 203 $ &$ 25. $ &$ 0.398 \times 10^{-1}$ & $ 0.006 $ &$ 0.498 $ &$ 0.498 $ &$ 0.62 $ &$ 1.78 $ &$ 1.82 $ &$ 2.62$ & $ 319$ \\ \hline \end{tabular} \end{center} \end{tiny} \tablecaption{\label{tab615a3}Continuation of \Tab~\ref{tab615a1}.} %\small \end{table} \begin{table} \begin{tiny} \begin{center} %\input{tabhead} \begin{tabular}{l|cccccccccc} \hline \\[-6pt] {\bf Bin} & $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma^{\rm ave}_{r}}$ & $\boldsymbol{F_2^{\rm ave}}$ & $\boldsymbol{\delta_{\rm ave,stat}}$ & $\boldsymbol{\delta_{\rm ave,uncor}}$ & $\boldsymbol{\delta_{\rm ave,cor}}$ & $\boldsymbol{\delta_{\rm ave,tot}}$ & $\boldsymbol{\sqrt{s}}$\\ $\boldsymbol{\#}$ & {\bf GeV}$\boldsymbol{^2}$ & & & & & {\bf \%} & {\bf \%} & \% & {\bf \%} & {\bf GeV} \\ \hline \\[-7pt] %\input{tables/p_4_615} $ 204 $ &$ 35. $ &$ 0.460 \times 10^{-3}$ & $ 0.750 $ &$ 1.444 $ &$ 1.621 $ &$ 1.24 $ &$ 2.68 $ &$ 1.05 $ &$ 3.13$ & $ 319$ \\ $ 205 $ &$ 35. $ &$ 0.531 \times 10^{-3}$ & $ 0.650 $ &$ 1.469 $ &$ 1.593 $ &$ 0.66 $ &$ 2.15 $ &$ 1.06 $ &$ 2.49$ & $ 319$ \\ $ 206 $ &$ 35. $ &$ 0.575 \times 10^{-3}$ & $ 0.675 $ &$ 1.512 $ &$ 1.652 $ &$ 1.36 $ &$ 2.01 $ &$ 1.15 $ &$ 2.69$ & $ 301$ \\ $ 207 $ &$ 35. $ &$ 0.800 \times 10^{-3}$ & $ 0.484 $ &$ 1.389 $ &$ 1.444 $ &$ 0.88 $ &$ 1.75 $ &$ 1.02 $ &$ 2.20$ & $ 301$ \\ $ 208 $ &$ 35. $ &$ 0.800 \times 10^{-3}$ & $ 0.432 $ &$ 1.391 $ &$ 1.433 $ &$ 0.62 $ &$ 0.72 $ &$ 0.88 $ &$ 1.29$ & $ 319$ \\ $ 209 $ &$ 35. $ &$ 0.130 \times 10^{-2}$ & $ 0.266 $ &$ 1.227 $ &$ 1.239 $ &$ 0.45 $ &$ 0.66 $ &$ 0.85 $ &$ 1.16$ & $ 319$ \\ $ 210 $ &$ 35. $ &$ 0.200 \times 10^{-2}$ & $ 0.173 $ &$ 1.098 $ &$ 1.102 $ &$ 0.50 $ &$ 0.67 $ &$ 0.87 $ &$ 1.21$ & $ 319$ \\ $ 211 $ &$ 35. $ &$ 0.320 \times 10^{-2}$ & $ 0.108 $ &$ 0.975 $ &$ 0.976 $ &$ 0.59 $ &$ 0.72 $ &$ 0.96 $ &$ 1.33$ & $ 319$ \\ $ 212 $ &$ 35. $ &$ 0.500 \times 10^{-2}$ & $ 0.069 $ &$ 0.854 $ &$ 0.855 $ &$ 0.60 $ &$ 0.72 $ &$ 0.96 $ &$ 1.34$ & $ 319$ \\ $ 213 $ &$ 35. $ &$ 0.800 \times 10^{-2}$ & $ 0.043 $ &$ 0.758 $ &$ 0.759 $ &$ 0.62 $ &$ 0.72 $ &$ 0.96 $ &$ 1.35$ & $ 319$ \\ $ 214 $ &$ 35. $ &$ 0.130 \times 10^{-1}$ & $ 0.027 $ &$ 0.670 $ &$ 0.670 $ &$ 0.68 $ &$ 0.74 $ &$ 0.97 $ &$ 1.40$ & $ 319$ \\ $ 215 $ &$ 35. $ &$ 0.200 \times 10^{-1}$ & $ 0.017 $ &$ 0.607 $ &$ 0.607 $ &$ 0.67 $ &$ 0.74 $ &$ 1.15 $ &$ 1.53$ & $ 319$ \\ $ 216 $ &$ 35. $ &$ 0.398 \times 10^{-1}$ & $ 0.009 $ &$ 0.511 $ &$ 0.511 $ &$ 0.76 $ &$ 2.14 $ &$ 1.37 $ &$ 2.66$ & $ 319$ \\ $ 217 $ &$ 35. $ &$ 0.800 \times 10^{-1}$ & $ 0.004 $ &$ 0.451 $ &$ 0.451 $ &$ 1.78 $ &$ 3.54 $ &$ 2.85 $ &$ 4.88$ & $ 319$ \\ $ 218 $ &$ 45. $ &$ 0.634 \times 10^{-3}$ & $ 0.700 $ &$ 1.455 $ &$ 1.603 $ &$ 1.01 $ &$ 2.21 $ &$ 1.05 $ &$ 2.64$ & $ 319$ \\ $ 219 $ &$ 45. $ &$ 0.800 \times 10^{-3}$ & $ 0.555 $ &$ 1.466 $ &$ 1.548 $ &$ 0.94 $ &$ 0.94 $ &$ 0.89 $ &$ 1.60$ & $ 319$ \\ $ 220 $ &$ 45. $ &$ 0.130 \times 10^{-2}$ & $ 0.383 $ &$ 1.326 $ &$ 1.356 $ &$ 0.92 $ &$ 1.75 $ &$ 0.92 $ &$ 2.18$ & $ 301$ \\ $ 221 $ &$ 45. $ &$ 0.130 \times 10^{-2}$ & $ 0.341 $ &$ 1.311 $ &$ 1.334 $ &$ 0.63 $ &$ 0.74 $ &$ 0.85 $ &$ 1.29$ & $ 319$ \\ $ 222 $ &$ 45. $ &$ 0.200 \times 10^{-2}$ & $ 0.222 $ &$ 1.163 $ &$ 1.171 $ &$ 0.49 $ &$ 0.69 $ &$ 0.85 $ &$ 1.20$ & $ 319$ \\ $ 223 $ &$ 45. $ &$ 0.320 \times 10^{-2}$ & $ 0.139 $ &$ 1.016 $ &$ 1.018 $ &$ 0.65 $ &$ 0.73 $ &$ 0.89 $ &$ 1.32$ & $ 319$ \\ $ 224 $ &$ 45. $ &$ 0.500 \times 10^{-2}$ & $ 0.089 $ &$ 0.898 $ &$ 0.899 $ &$ 0.69 $ &$ 0.73 $ &$ 0.96 $ &$ 1.39$ & $ 319$ \\ $ 225 $ &$ 45. $ &$ 0.800 \times 10^{-2}$ & $ 0.055 $ &$ 0.787 $ &$ 0.787 $ &$ 0.71 $ &$ 0.75 $ &$ 0.93 $ &$ 1.39$ & $ 319$ \\ $ 226 $ &$ 45. $ &$ 0.130 \times 10^{-1}$ & $ 0.034 $ &$ 0.691 $ &$ 0.691 $ &$ 0.75 $ &$ 0.75 $ &$ 0.94 $ &$ 1.42$ & $ 319$ \\ $ 227 $ &$ 45. $ &$ 0.200 \times 10^{-1}$ & $ 0.022 $ &$ 0.611 $ &$ 0.611 $ &$ 0.75 $ &$ 0.77 $ &$ 1.16 $ &$ 1.58$ & $ 319$ \\ $ 228 $ &$ 45. $ &$ 0.320 \times 10^{-1}$ & $ 0.014 $ &$ 0.540 $ &$ 0.540 $ &$ 1.09 $ &$ 0.85 $ &$ 1.03 $ &$ 1.72$ & $ 319$ \\ $ 229 $ &$ 45. $ &$ 0.631 \times 10^{-1}$ & $ 0.007 $ &$ 0.457 $ &$ 0.457 $ &$ 0.92 $ &$ 1.82 $ &$ 2.10 $ &$ 2.93$ & $ 319$ \\ $ 230 $ &$ 60. $ &$ 0.130 \times 10^{-2}$ & $ 0.455 $ &$ 1.398 $ &$ 1.446 $ &$ 0.80 $ &$ 0.90 $ &$ 0.87 $ &$ 1.48$ & $ 319$ \\ $ 231 $ &$ 60. $ &$ 0.200 \times 10^{-2}$ & $ 0.296 $ &$ 1.252 $ &$ 1.267 $ &$ 0.54 $ &$ 0.74 $ &$ 0.85 $ &$ 1.25$ & $ 319$ \\ $ 232 $ &$ 60. $ &$ 0.320 \times 10^{-2}$ & $ 0.185 $ &$ 1.087 $ &$ 1.092 $ &$ 0.58 $ &$ 0.71 $ &$ 0.86 $ &$ 1.26$ & $ 319$ \\ $ 233 $ &$ 60. $ &$ 0.500 \times 10^{-2}$ & $ 0.118 $ &$ 0.964 $ &$ 0.965 $ &$ 0.79 $ &$ 0.78 $ &$ 0.93 $ &$ 1.45$ & $ 319$ \\ $ 234 $ &$ 60. $ &$ 0.800 \times 10^{-2}$ & $ 0.074 $ &$ 0.829 $ &$ 0.829 $ &$ 0.82 $ &$ 0.79 $ &$ 0.95 $ &$ 1.48$ & $ 319$ \\ $ 235 $ &$ 60. $ &$ 0.130 \times 10^{-1}$ & $ 0.046 $ &$ 0.716 $ &$ 0.716 $ &$ 0.86 $ &$ 0.80 $ &$ 0.98 $ &$ 1.53$ & $ 319$ \\ $ 236 $ &$ 60. $ &$ 0.200 \times 10^{-1}$ & $ 0.030 $ &$ 0.648 $ &$ 0.648 $ &$ 0.94 $ &$ 0.82 $ &$ 1.06 $ &$ 1.63$ & $ 319$ \\ $ 237 $ &$ 60. $ &$ 0.320 \times 10^{-1}$ & $ 0.018 $ &$ 0.563 $ &$ 0.563 $ &$ 1.00 $ &$ 0.83 $ &$ 1.10 $ &$ 1.70$ & $ 319$ \\ $ 238 $ &$ 60. $ &$ 0.631 \times 10^{-1}$ & $ 0.009 $ &$ 0.465 $ &$ 0.465 $ &$ 1.14 $ &$ 2.18 $ &$ 2.02 $ &$ 3.18$ & $ 319$ \\ $ 239 $ &$ 60. $ &$ 0.130 $ & $ 0.005 $ &$ 0.399 $ &$ 0.399 $ &$ 2.93 $ &$ 3.88 $ &$ 2.45 $ &$ 5.45$ & $ 301$ \\ $ 240 $ &$ 90. $ &$ 0.200 \times 10^{-2}$ & $ 0.444 $ &$ 1.324 $ &$ 1.367 $ &$ 0.94 $ &$ 1.06 $ &$ 0.88 $ &$ 1.67$ & $ 319$ \\ $ 241 $ &$ 90. $ &$ 0.320 \times 10^{-2}$ & $ 0.277 $ &$ 1.169 $ &$ 1.181 $ &$ 0.64 $ &$ 0.82 $ &$ 0.86 $ &$ 1.35$ & $ 319$ \\ $ 242 $ &$ 90. $ &$ 0.500 \times 10^{-2}$ & $ 0.178 $ &$ 1.027 $ &$ 1.031 $ &$ 0.75 $ &$ 0.76 $ &$ 0.87 $ &$ 1.38$ & $ 319$ \\ $ 243 $ &$ 90. $ &$ 0.800 \times 10^{-2}$ & $ 0.111 $ &$ 0.880 $ &$ 0.881 $ &$ 0.96 $ &$ 0.84 $ &$ 0.98 $ &$ 1.61$ & $ 319$ \\ $ 244 $ &$ 90. $ &$ 0.130 \times 10^{-1}$ & $ 0.068 $ &$ 0.758 $ &$ 0.759 $ &$ 0.99 $ &$ 0.85 $ &$ 1.00 $ &$ 1.65$ & $ 319$ \\ $ 245 $ &$ 90. $ &$ 0.200 \times 10^{-1}$ & $ 0.044 $ &$ 0.664 $ &$ 0.664 $ &$ 1.06 $ &$ 0.87 $ &$ 1.07 $ &$ 1.74$ & $ 319$ \\ $ 246 $ &$ 90. $ &$ 0.320 \times 10^{-1}$ & $ 0.028 $ &$ 0.569 $ &$ 0.569 $ &$ 1.11 $ &$ 0.88 $ &$ 1.10 $ &$ 1.79$ & $ 319$ \\ $ 247 $ &$ 90. $ &$ 0.500 \times 10^{-1}$ & $ 0.018 $ &$ 0.492 $ &$ 0.492 $ &$ 1.59 $ &$ 1.02 $ &$ 1.41 $ &$ 2.35$ & $ 319$ \\ $ 248 $ &$ 90. $ &$ 0.100 $ & $ 0.009 $ &$ 0.402 $ &$ 0.402 $ &$ 1.50 $ &$ 1.65 $ &$ 2.10 $ &$ 3.06$ & $ 319$ \\ $ 249 $ &$ 120. $ &$ 0.500 \times 10^{-2}$ & $ 0.237 $ &$ 1.032 $ &$ 1.040 $ &$ 1.58 $ &$ 1.15 $ &$ 0.96 $ &$ 2.18$ & $ 319$ \\ $ 250 $ &$ 120. $ &$ 0.800 \times 10^{-2}$ & $ 0.148 $ &$ 0.897 $ &$ 0.899 $ &$ 1.31 $ &$ 1.02 $ &$ 0.95 $ &$ 1.91$ & $ 319$ \\ $ 251 $ &$ 120. $ &$ 0.130 \times 10^{-1}$ & $ 0.091 $ &$ 0.787 $ &$ 0.788 $ &$ 1.32 $ &$ 1.02 $ &$ 1.08 $ &$ 1.99$ & $ 319$ \\ $ 252 $ &$ 120. $ &$ 0.200 \times 10^{-1}$ & $ 0.059 $ &$ 0.662 $ &$ 0.662 $ &$ 1.34 $ &$ 1.01 $ &$ 1.11 $ &$ 2.01$ & $ 319$ \\ $ 253 $ &$ 120. $ &$ 0.320 \times 10^{-1}$ & $ 0.037 $ &$ 0.580 $ &$ 0.580 $ &$ 1.47 $ &$ 1.03 $ &$ 1.21 $ &$ 2.16$ & $ 319$ \\ $ 254 $ &$ 120. $ &$ 0.500 \times 10^{-1}$ & $ 0.024 $ &$ 0.498 $ &$ 0.498 $ &$ 1.55 $ &$ 1.05 $ &$ 1.30 $ &$ 2.28$ & $ 319$ \\ $ 255 $ &$ 120. $ &$ 0.100 $ & $ 0.012 $ &$ 0.404 $ &$ 0.404 $ &$ 1.91 $ &$ 1.12 $ &$ 2.68 $ &$ 3.48$ & $ 319$ \\ $ 256 $ &$ 120. $ &$ 0.200 $ & $ 0.006 $ &$ 0.342 $ &$ 0.342 $ &$ 4.61 $ &$ 4.81 $ &$ 2.94 $ &$ 7.29$ & $ 319$ \\ $ 257 $ &$ 150. $ &$ 0.130 \times 10^{-1}$ & $ 0.114 $ &$ 0.748 $ &$ 0.749 $ &$ 5.47 $ &$ 2.73 $ &$ 1.22 $ &$ 6.24$ & $ 319$ \\ $ 258 $ &$ 150. $ &$ 0.200 \times 10^{-1}$ & $ 0.074 $ &$ 0.722 $ &$ 0.722 $ &$ 3.16 $ &$ 2.19 $ &$ 1.46 $ &$ 4.12$ & $ 319$ \\ $ 259 $ &$ 150. $ &$ 0.320 \times 10^{-1}$ & $ 0.046 $ &$ 0.605 $ &$ 0.605 $ &$ 2.99 $ &$ 1.92 $ &$ 2.17 $ &$ 4.17$ & $ 319$ \\ $ 260 $ &$ 150. $ &$ 0.500 \times 10^{-1}$ & $ 0.030 $ &$ 0.503 $ &$ 0.503 $ &$ 3.02 $ &$ 1.87 $ &$ 1.83 $ &$ 3.99$ & $ 319$ \\ $ 261 $ &$ 150. $ &$ 0.100 $ & $ 0.015 $ &$ 0.429 $ &$ 0.429 $ &$ 3.43 $ &$ 1.80 $ &$ 2.60 $ &$ 4.67$ & $ 319$ \\ $ 262 $ &$ 150. $ &$ 0.200 $ & $ 0.007 $ &$ 0.330 $ &$ 0.330 $ &$ 8.06 $ &$ 7.13 $ &$ 1.99 $ &$10.94$ & $ 319$ \\ \hline \end{tabular} \end{center} \end{tiny} \tablecaption{\label{tab615a4}Continuation of \Tab~\ref{tab615a1}.} %\small \end{table} \begin{table} \begin{tiny} \begin{center} %\input{tabhead} \begin{tabular}{l|cccccccccc} \hline \\[-6pt] {\bf Bin} & $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma^{\rm ave}_{r}}$ & $\boldsymbol{F_2^{\rm ave}}$ & $\boldsymbol{\delta_{\rm ave,stat}}$ & $\boldsymbol{\delta_{\rm ave,uncor}}$ & $\boldsymbol{\delta_{\rm ave,cor}}$ & $\boldsymbol{\delta_{\rm ave,tot}}$ & $\boldsymbol{\sqrt{s}}$\\ $\boldsymbol{\#}$ & {\bf GeV}$\boldsymbol{^2}$ & & & & & {\bf \%} & {\bf \%} & \% & {\bf \%} & {\bf GeV} \\ \hline \\[-7pt] %\input{tables/p_1_lowe} $ 1 $ &$ 1.5 $ &$ 0.279 \times 10^{-4}$ & $ 0.848 $ &$ 0.661 $ &$ 0.773 $ &$ 9.37 $ &$ 4.94 $ &$ 4.80 $ &$11.63$ & $ 252$ \\ $ 2 $ &$ 1.5 $ &$ 0.348 \times 10^{-4}$ & $ 0.850 $ &$ 0.521 $ &$ 0.610 $ &$ 8.09 $ &$ 4.96 $ &$ 4.60 $ &$10.54$ & $ 225$ \\ $ 3 $ &$ 2. $ &$ 0.372 \times 10^{-4}$ & $ 0.848 $ &$ 0.758 $ &$ 0.887 $ &$ 6.38 $ &$ 4.34 $ &$ 4.14 $ &$ 8.76$ & $ 252$ \\ $ 4 $ &$ 2. $ &$ 0.415 \times 10^{-4}$ & $ 0.761 $ &$ 0.663 $ &$ 0.747 $ &$ 7.43 $ &$ 3.97 $ &$ 3.73 $ &$ 9.21$ & $ 252$ \\ $ 5 $ &$ 2. $ &$ 0.464 \times 10^{-4}$ & $ 0.850 $ &$ 0.707 $ &$ 0.828 $ &$ 4.56 $ &$ 4.31 $ &$ 3.97 $ &$ 7.42$ & $ 225$ \\ $ 6 $ &$ 2. $ &$ 0.526 \times 10^{-4}$ & $ 0.750 $ &$ 0.720 $ &$ 0.808 $ &$ 4.58 $ &$ 3.93 $ &$ 3.43 $ &$ 6.94$ & $ 225$ \\ $ 7 $ &$ 2.5 $ &$ 0.465 \times 10^{-4}$ & $ 0.848 $ &$ 0.826 $ &$ 0.966 $ &$ 5.44 $ &$ 4.12 $ &$ 4.13 $ &$ 7.98$ & $ 252$ \\ $ 8 $ &$ 2.5 $ &$ 0.519 \times 10^{-4}$ & $ 0.760 $ &$ 0.834 $ &$ 0.940 $ &$ 3.86 $ &$ 3.10 $ &$ 3.21 $ &$ 5.90$ & $ 252$ \\ $ 9 $ &$ 2.5 $ &$ 0.580 \times 10^{-4}$ & $ 0.850 $ &$ 0.780 $ &$ 0.913 $ &$ 4.17 $ &$ 4.16 $ &$ 4.24 $ &$ 7.26$ & $ 225$ \\ $ 10 $ &$ 2.5 $ &$ 0.580 \times 10^{-4}$ & $ 0.680 $ &$ 0.765 $ &$ 0.838 $ &$ 4.99 $ &$ 3.14 $ &$ 2.90 $ &$ 6.57$ & $ 252$ \\ $ 11 $ &$ 2.5 $ &$ 0.658 \times 10^{-4}$ & $ 0.750 $ &$ 0.770 $ &$ 0.864 $ &$ 2.64 $ &$ 3.03 $ &$ 3.15 $ &$ 5.11$ & $ 225$ \\ $ 12 $ &$ 2.5 $ &$ 0.759 \times 10^{-4}$ & $ 0.650 $ &$ 0.714 $ &$ 0.774 $ &$ 4.31 $ &$ 3.45 $ &$ 3.30 $ &$ 6.43$ & $ 225$ \\ $ 13 $ &$ 3.5 $ &$ 0.651 \times 10^{-4}$ & $ 0.848 $ &$ 0.868 $ &$ 1.016 $ &$ 5.57 $ &$ 4.05 $ &$ 4.18 $ &$ 8.05$ & $ 252$ \\ $ 14 $ &$ 3.5 $ &$ 0.727 \times 10^{-4}$ & $ 0.760 $ &$ 0.870 $ &$ 0.981 $ &$ 3.52 $ &$ 2.92 $ &$ 3.34 $ &$ 5.66$ & $ 252$ \\ $ 15 $ &$ 3.5 $ &$ 0.812 \times 10^{-4}$ & $ 0.850 $ &$ 0.796 $ &$ 0.932 $ &$ 4.20 $ &$ 4.05 $ &$ 3.87 $ &$ 7.01$ & $ 225$ \\ $ 16 $ &$ 3.5 $ &$ 0.812 \times 10^{-4}$ & $ 0.680 $ &$ 0.867 $ &$ 0.949 $ &$ 3.15 $ &$ 2.49 $ &$ 3.40 $ &$ 5.26$ & $ 252$ \\ $ 17 $ &$ 3.5 $ &$ 0.921 \times 10^{-4}$ & $ 0.750 $ &$ 0.822 $ &$ 0.923 $ &$ 2.22 $ &$ 2.86 $ &$ 3.38 $ &$ 4.95$ & $ 225$ \\ $ 18 $ &$ 3.5 $ &$ 0.921 \times 10^{-4}$ & $ 0.600 $ &$ 0.936 $ &$ 1.000 $ &$ 3.36 $ &$ 2.66 $ &$ 2.92 $ &$ 5.19$ & $ 252$ \\ $ 19 $ &$ 3.5 $ &$ 0.106 \times 10^{-3}$ & $ 0.650 $ &$ 0.860 $ &$ 0.932 $ &$ 2.03 $ &$ 2.47 $ &$ 3.33 $ &$ 4.61$ & $ 225$ \\ $ 20 $ &$ 3.5 $ &$ 0.106 \times 10^{-3}$ & $ 0.520 $ &$ 0.956 $ &$ 1.001 $ &$ 5.39 $ &$ 3.27 $ &$ 3.46 $ &$ 7.20$ & $ 252$ \\ $ 21 $ &$ 3.5 $ &$ 0.141 \times 10^{-3}$ & $ 0.490 $ &$ 0.800 $ &$ 0.833 $ &$ 2.54 $ &$ 2.45 $ &$ 3.65 $ &$ 5.08$ & $ 225$ \\ $ 22 $ &$ 5. $ &$ 0.931 \times 10^{-4}$ & $ 0.848 $ &$ 0.846 $ &$ 0.990 $ &$ 6.49 $ &$ 3.99 $ &$ 4.19 $ &$ 8.70$ & $ 252$ \\ $ 23 $ &$ 5. $ &$ 0.104 \times 10^{-3}$ & $ 0.760 $ &$ 0.880 $ &$ 0.992 $ &$ 3.53 $ &$ 2.84 $ &$ 3.05 $ &$ 5.46$ & $ 252$ \\ $ 24 $ &$ 5. $ &$ 0.116 \times 10^{-3}$ & $ 0.850 $ &$ 0.942 $ &$ 1.103 $ &$ 4.18 $ &$ 4.01 $ &$ 4.20 $ &$ 7.16$ & $ 225$ \\ $ 25 $ &$ 5. $ &$ 0.116 \times 10^{-3}$ & $ 0.680 $ &$ 1.002 $ &$ 1.098 $ &$ 2.66 $ &$ 2.37 $ &$ 3.05 $ &$ 4.69$ & $ 252$ \\ $ 26 $ &$ 5. $ &$ 0.131 \times 10^{-3}$ & $ 0.750 $ &$ 0.927 $ &$ 1.040 $ &$ 2.07 $ &$ 2.80 $ &$ 3.24 $ &$ 4.76$ & $ 225$ \\ $ 27 $ &$ 5. $ &$ 0.131 \times 10^{-3}$ & $ 0.600 $ &$ 0.943 $ &$ 1.008 $ &$ 2.60 $ &$ 2.37 $ &$ 3.10 $ &$ 4.69$ & $ 252$ \\ $ 28 $ &$ 5. $ &$ 0.152 \times 10^{-3}$ & $ 0.650 $ &$ 0.970 $ &$ 1.051 $ &$ 1.69 $ &$ 2.33 $ &$ 3.05 $ &$ 4.19$ & $ 225$ \\ $ 29 $ &$ 5. $ &$ 0.152 \times 10^{-3}$ & $ 0.520 $ &$ 1.009 $ &$ 1.056 $ &$ 2.43 $ &$ 2.04 $ &$ 2.99 $ &$ 4.36$ & $ 252$ \\ $ 30 $ &$ 5. $ &$ 0.201 \times 10^{-3}$ & $ 0.490 $ &$ 0.917 $ &$ 0.955 $ &$ 1.16 $ &$ 1.87 $ &$ 3.05 $ &$ 3.76$ & $ 225$ \\ $ 31 $ &$ 5. $ &$ 0.201 \times 10^{-3}$ & $ 0.392 $ &$ 0.938 $ &$ 0.960 $ &$ 2.58 $ &$ 2.06 $ &$ 3.02 $ &$ 4.48$ & $ 252$ \\ $ 32 $ &$ 6.5 $ &$ 0.121 \times 10^{-3}$ & $ 0.848 $ &$ 0.900 $ &$ 1.052 $ &$ 7.19 $ &$ 4.03 $ &$ 4.42 $ &$ 9.36$ & $ 252$ \\ $ 33 $ &$ 6.5 $ &$ 0.135 \times 10^{-3}$ & $ 0.760 $ &$ 0.988 $ &$ 1.114 $ &$ 3.49 $ &$ 2.85 $ &$ 3.12 $ &$ 5.48$ & $ 252$ \\ $ 34 $ &$ 6.5 $ &$ 0.151 \times 10^{-3}$ & $ 0.850 $ &$ 1.037 $ &$ 1.214 $ &$ 4.26 $ &$ 4.02 $ &$ 4.09 $ &$ 7.14$ & $ 225$ \\ $ 35 $ &$ 6.5 $ &$ 0.151 \times 10^{-3}$ & $ 0.680 $ &$ 1.065 $ &$ 1.166 $ &$ 2.56 $ &$ 2.35 $ &$ 3.08 $ &$ 4.64$ & $ 252$ \\ $ 36 $ &$ 6.5 $ &$ 0.171 \times 10^{-3}$ & $ 0.750 $ &$ 0.960 $ &$ 1.078 $ &$ 2.15 $ &$ 2.80 $ &$ 3.16 $ &$ 4.74$ & $ 225$ \\ $ 37 $ &$ 6.5 $ &$ 0.171 \times 10^{-3}$ & $ 0.600 $ &$ 1.045 $ &$ 1.117 $ &$ 2.30 $ &$ 2.32 $ &$ 2.96 $ &$ 4.41$ & $ 252$ \\ $ 38 $ &$ 6.5 $ &$ 0.197 \times 10^{-3}$ & $ 0.650 $ &$ 1.010 $ &$ 1.095 $ &$ 1.60 $ &$ 2.30 $ &$ 2.97 $ &$ 4.08$ & $ 225$ \\ $ 39 $ &$ 6.5 $ &$ 0.197 \times 10^{-3}$ & $ 0.520 $ &$ 1.102 $ &$ 1.154 $ &$ 2.05 $ &$ 1.96 $ &$ 2.95 $ &$ 4.10$ & $ 252$ \\ $ 40 $ &$ 6.5 $ &$ 0.262 \times 10^{-3}$ & $ 0.490 $ &$ 1.011 $ &$ 1.052 $ &$ 0.90 $ &$ 1.82 $ &$ 3.01 $ &$ 3.63$ & $ 225$ \\ $ 41 $ &$ 6.5 $ &$ 0.262 \times 10^{-3}$ & $ 0.392 $ &$ 0.998 $ &$ 1.022 $ &$ 1.38 $ &$ 1.83 $ &$ 2.97 $ &$ 3.76$ & $ 252$ \\ $ 42 $ &$ 6.5 $ &$ 0.414 \times 10^{-3}$ & $ 0.248 $ &$ 0.973 $ &$ 0.981 $ &$ 1.13 $ &$ 1.86 $ &$ 3.00 $ &$ 3.70$ & $ 252$ \\ $ 43 $ &$ 8.5 $ &$ 0.158 \times 10^{-3}$ & $ 0.848 $ &$ 0.972 $ &$ 1.137 $ &$ 7.11 $ &$ 4.00 $ &$ 5.02 $ &$ 9.58$ & $ 252$ \\ $ 44 $ &$ 8.5 $ &$ 0.177 \times 10^{-3}$ & $ 0.760 $ &$ 1.067 $ &$ 1.203 $ &$ 3.82 $ &$ 2.90 $ &$ 3.04 $ &$ 5.68$ & $ 252$ \\ $ 45 $ &$ 8.5 $ &$ 0.197 \times 10^{-3}$ & $ 0.850 $ &$ 0.972 $ &$ 1.137 $ &$ 4.67 $ &$ 4.01 $ &$ 4.44 $ &$ 7.59$ & $ 225$ \\ $ 46 $ &$ 8.5 $ &$ 0.197 \times 10^{-3}$ & $ 0.680 $ &$ 1.088 $ &$ 1.192 $ &$ 2.80 $ &$ 2.39 $ &$ 3.10 $ &$ 4.82$ & $ 252$ \\ $ 47 $ &$ 8.5 $ &$ 0.224 \times 10^{-3}$ & $ 0.750 $ &$ 1.010 $ &$ 1.134 $ &$ 2.38 $ &$ 2.84 $ &$ 3.16 $ &$ 4.87$ & $ 225$ \\ $ 48 $ &$ 8.5 $ &$ 0.224 \times 10^{-3}$ & $ 0.600 $ &$ 1.099 $ &$ 1.174 $ &$ 2.32 $ &$ 2.33 $ &$ 2.96 $ &$ 4.43$ & $ 252$ \\ $ 49 $ &$ 8.5 $ &$ 0.258 \times 10^{-3}$ & $ 0.650 $ &$ 1.090 $ &$ 1.182 $ &$ 1.66 $ &$ 2.32 $ &$ 3.26 $ &$ 4.33$ & $ 225$ \\ $ 50 $ &$ 8.5 $ &$ 0.258 \times 10^{-3}$ & $ 0.520 $ &$ 1.030 $ &$ 1.078 $ &$ 2.03 $ &$ 1.93 $ &$ 3.13 $ &$ 4.20$ & $ 252$ \\ $ 51 $ &$ 8.5 $ &$ 0.342 \times 10^{-3}$ & $ 0.490 $ &$ 1.054 $ &$ 1.097 $ &$ 0.85 $ &$ 1.81 $ &$ 3.02 $ &$ 3.62$ & $ 225$ \\ $ 52 $ &$ 8.5 $ &$ 0.342 \times 10^{-3}$ & $ 0.392 $ &$ 1.083 $ &$ 1.109 $ &$ 1.20 $ &$ 1.81 $ &$ 2.91 $ &$ 3.63$ & $ 252$ \\ $ 53 $ &$ 8.5 $ &$ 0.541 \times 10^{-3}$ & $ 0.248 $ &$ 1.020 $ &$ 1.028 $ &$ 0.77 $ &$ 1.29 $ &$ 2.87 $ &$ 3.24$ & $ 252$ \\ $ 54 $ &$ 8.5 $ &$ 0.838 \times 10^{-3}$ & $ 0.160 $ &$ 0.941 $ &$ 0.944 $ &$ 0.86 $ &$ 1.31 $ &$ 2.94 $ &$ 3.33$ & $ 252$ \\ $ 55 $ &$ 8.5 $ &$ 0.140 \times 10^{-2}$ & $ 0.096 $ &$ 0.846 $ &$ 0.847 $ &$ 1.16 $ &$ 1.44 $ &$ 3.02 $ &$ 3.55$ & $ 252$ \\ $ 56 $ &$ 12. $ &$ 0.223 \times 10^{-3}$ & $ 0.848 $ &$ 1.234 $ &$ 1.443 $ &$ 5.52 $ &$ 4.00 $ &$ 4.14 $ &$ 7.97$ & $ 252$ \\ $ 57 $ &$ 12. $ &$ 0.249 \times 10^{-3}$ & $ 0.760 $ &$ 1.079 $ &$ 1.217 $ &$ 4.07 $ &$ 2.91 $ &$ 3.13 $ &$ 5.90$ & $ 252$ \\ $ 58 $ &$ 12. $ &$ 0.278 \times 10^{-3}$ & $ 0.850 $ &$ 1.130 $ &$ 1.323 $ &$ 3.89 $ &$ 3.98 $ &$ 3.72 $ &$ 6.70$ & $ 225$ \\ $ 59 $ &$ 12. $ &$ 0.278 \times 10^{-3}$ & $ 0.680 $ &$ 1.162 $ &$ 1.272 $ &$ 3.08 $ &$ 2.43 $ &$ 3.05 $ &$ 4.97$ & $ 252$ \\ $ 60 $ &$ 12. $ &$ 0.316 \times 10^{-3}$ & $ 0.750 $ &$ 1.114 $ &$ 1.250 $ &$ 2.38 $ &$ 2.85 $ &$ 3.10 $ &$ 4.84$ & $ 225$ \\ $ 61 $ &$ 12. $ &$ 0.316 \times 10^{-3}$ & $ 0.600 $ &$ 1.183 $ &$ 1.264 $ &$ 2.56 $ &$ 2.37 $ &$ 3.07 $ &$ 4.64$ & $ 252$ \\ $ 62 $ &$ 12. $ &$ 0.364 \times 10^{-3}$ & $ 0.650 $ &$ 1.098 $ &$ 1.190 $ &$ 1.86 $ &$ 2.36 $ &$ 3.01 $ &$ 4.25$ & $ 225$ \\ $ 63 $ &$ 12. $ &$ 0.364 \times 10^{-3}$ & $ 0.520 $ &$ 1.171 $ &$ 1.226 $ &$ 2.12 $ &$ 1.96 $ &$ 2.97 $ &$ 4.14$ & $ 252$ \\ $ 64 $ &$ 12. $ &$ 0.483 \times 10^{-3}$ & $ 0.490 $ &$ 1.111 $ &$ 1.156 $ &$ 0.89 $ &$ 1.81 $ &$ 3.02 $ &$ 3.63$ & $ 225$ \\ $ 65 $ &$ 12. $ &$ 0.483 \times 10^{-3}$ & $ 0.392 $ &$ 1.123 $ &$ 1.150 $ &$ 1.19 $ &$ 1.81 $ &$ 2.95 $ &$ 3.66$ & $ 252$ \\ $ 66 $ &$ 12. $ &$ 0.764 \times 10^{-3}$ & $ 0.248 $ &$ 1.044 $ &$ 1.052 $ &$ 0.73 $ &$ 1.28 $ &$ 2.92 $ &$ 3.27$ & $ 252$ \\ $ 67 $ &$ 12. $ &$ 0.118 \times 10^{-2}$ & $ 0.160 $ &$ 0.994 $ &$ 0.997 $ &$ 0.78 $ &$ 1.30 $ &$ 2.93 $ &$ 3.29$ & $ 252$ \\ $ 68 $ &$ 12. $ &$ 0.197 \times 10^{-2}$ & $ 0.096 $ &$ 0.878 $ &$ 0.879 $ &$ 1.04 $ &$ 1.40 $ &$ 3.12 $ &$ 3.58$ & $ 252$ \\ \hline \end{tabular} \end{center} \end{tiny} \tablecaption{\label{tablowea1} %\small Combined reduced cross section $\sigma_{r}$ for $E_p=460$~GeV and $E_p=575$~GeV. Description of the columns is given in the caption of \Tab~\ref{tab615a1}. } \end{table} \begin{table} \begin{tiny} \begin{center} %\input{tabhead} \begin{tabular}{l|cccccccccc} \hline \\[-6pt] {\bf Bin} & $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{y}$ & $\boldsymbol{\sigma^{\rm ave}_{r}}$ & $\boldsymbol{F_2^{\rm ave}}$ & $\boldsymbol{\delta_{\rm ave,stat}}$ & $\boldsymbol{\delta_{\rm ave,uncor}}$ & $\boldsymbol{\delta_{\rm ave,cor}}$ & $\boldsymbol{\delta_{\rm ave,tot}}$ & $\boldsymbol{\sqrt{s}}$\\ $\boldsymbol{\#}$ & {\bf GeV}$\boldsymbol{^2}$ & & & & & {\bf \%} & {\bf \%} & \% & {\bf \%} & {\bf GeV} \\ \hline \\[-7pt] %\input{tables/p_2_lowe} $ 69 $ &$ 15. $ &$ 0.279 \times 10^{-3}$ & $ 0.848 $ &$ 1.106 $ &$ 1.294 $ &$ 6.32 $ &$ 4.04 $ &$ 3.77 $ &$ 8.39$ & $ 252$ \\ $ 70 $ &$ 15. $ &$ 0.312 \times 10^{-3}$ & $ 0.760 $ &$ 1.290 $ &$ 1.453 $ &$ 3.41 $ &$ 2.90 $ &$ 2.97 $ &$ 5.37$ & $ 252$ \\ $ 71 $ &$ 15. $ &$ 0.348 \times 10^{-3}$ & $ 0.850 $ &$ 1.222 $ &$ 1.430 $ &$ 3.89 $ &$ 4.06 $ &$ 3.36 $ &$ 6.55$ & $ 225$ \\ $ 72 $ &$ 15. $ &$ 0.348 \times 10^{-3}$ & $ 0.680 $ &$ 1.222 $ &$ 1.338 $ &$ 3.19 $ &$ 2.47 $ &$ 2.88 $ &$ 4.95$ & $ 252$ \\ $ 73 $ &$ 15. $ &$ 0.395 \times 10^{-3}$ & $ 0.750 $ &$ 1.112 $ &$ 1.249 $ &$ 2.33 $ &$ 2.84 $ &$ 2.97 $ &$ 4.72$ & $ 225$ \\ $ 74 $ &$ 15. $ &$ 0.395 \times 10^{-3}$ & $ 0.600 $ &$ 1.152 $ &$ 1.231 $ &$ 2.98 $ &$ 2.43 $ &$ 2.98 $ &$ 4.86$ & $ 252$ \\ $ 75 $ &$ 15. $ &$ 0.455 \times 10^{-3}$ & $ 0.650 $ &$ 1.141 $ &$ 1.237 $ &$ 2.05 $ &$ 2.40 $ &$ 3.15 $ &$ 4.46$ & $ 225$ \\ $ 76 $ &$ 15. $ &$ 0.455 \times 10^{-3}$ & $ 0.520 $ &$ 1.250 $ &$ 1.310 $ &$ 2.33 $ &$ 2.01 $ &$ 2.98 $ &$ 4.29$ & $ 252$ \\ $ 77 $ &$ 15. $ &$ 0.604 \times 10^{-3}$ & $ 0.490 $ &$ 1.165 $ &$ 1.212 $ &$ 0.96 $ &$ 1.83 $ &$ 3.02 $ &$ 3.66$ & $ 225$ \\ $ 78 $ &$ 15. $ &$ 0.604 \times 10^{-3}$ & $ 0.392 $ &$ 1.158 $ &$ 1.185 $ &$ 1.29 $ &$ 1.82 $ &$ 3.04 $ &$ 3.77$ & $ 252$ \\ $ 79 $ &$ 15. $ &$ 0.954 \times 10^{-3}$ & $ 0.248 $ &$ 1.050 $ &$ 1.059 $ &$ 0.76 $ &$ 1.29 $ &$ 2.90 $ &$ 3.26$ & $ 252$ \\ $ 80 $ &$ 15. $ &$ 0.148 \times 10^{-2}$ & $ 0.160 $ &$ 0.955 $ &$ 0.958 $ &$ 0.79 $ &$ 1.30 $ &$ 3.01 $ &$ 3.37$ & $ 252$ \\ $ 81 $ &$ 15. $ &$ 0.247 \times 10^{-2}$ & $ 0.096 $ &$ 0.859 $ &$ 0.860 $ &$ 1.02 $ &$ 1.39 $ &$ 3.18 $ &$ 3.62$ & $ 252$ \\ $ 82 $ &$ 20. $ &$ 0.372 \times 10^{-3}$ & $ 0.848 $ &$ 1.283 $ &$ 1.501 $ &$ 6.60 $ &$ 4.25 $ &$ 3.74 $ &$ 8.70$ & $ 252$ \\ $ 83 $ &$ 20. $ &$ 0.415 \times 10^{-3}$ & $ 0.760 $ &$ 1.242 $ &$ 1.400 $ &$ 3.66 $ &$ 2.93 $ &$ 3.00 $ &$ 5.57$ & $ 252$ \\ $ 84 $ &$ 20. $ &$ 0.464 \times 10^{-3}$ & $ 0.850 $ &$ 1.006 $ &$ 1.177 $ &$ 5.33 $ &$ 4.21 $ &$ 3.52 $ &$ 7.65$ & $ 225$ \\ $ 85 $ &$ 20. $ &$ 0.464 \times 10^{-3}$ & $ 0.680 $ &$ 1.288 $ &$ 1.410 $ &$ 3.05 $ &$ 2.46 $ &$ 2.89 $ &$ 4.87$ & $ 252$ \\ $ 86 $ &$ 20. $ &$ 0.526 \times 10^{-3}$ & $ 0.750 $ &$ 1.204 $ &$ 1.351 $ &$ 2.27 $ &$ 2.87 $ &$ 3.02 $ &$ 4.74$ & $ 225$ \\ $ 87 $ &$ 20. $ &$ 0.526 \times 10^{-3}$ & $ 0.600 $ &$ 1.131 $ &$ 1.208 $ &$ 3.18 $ &$ 2.46 $ &$ 3.00 $ &$ 5.02$ & $ 252$ \\ $ 88 $ &$ 20. $ &$ 0.607 \times 10^{-3}$ & $ 0.650 $ &$ 1.181 $ &$ 1.280 $ &$ 1.97 $ &$ 2.39 $ &$ 2.91 $ &$ 4.25$ & $ 225$ \\ $ 89 $ &$ 20. $ &$ 0.607 \times 10^{-3}$ & $ 0.520 $ &$ 1.219 $ &$ 1.277 $ &$ 2.58 $ &$ 2.06 $ &$ 3.18 $ &$ 4.58$ & $ 252$ \\ $ 90 $ &$ 20. $ &$ 0.805 \times 10^{-3}$ & $ 0.490 $ &$ 1.169 $ &$ 1.217 $ &$ 1.06 $ &$ 1.85 $ &$ 3.08 $ &$ 3.75$ & $ 225$ \\ $ 91 $ &$ 20. $ &$ 0.805 \times 10^{-3}$ & $ 0.392 $ &$ 1.207 $ &$ 1.236 $ &$ 1.41 $ &$ 1.84 $ &$ 2.96 $ &$ 3.76$ & $ 252$ \\ $ 92 $ &$ 20. $ &$ 0.127 \times 10^{-2}$ & $ 0.248 $ &$ 1.094 $ &$ 1.103 $ &$ 0.83 $ &$ 1.30 $ &$ 2.97 $ &$ 3.35$ & $ 252$ \\ $ 93 $ &$ 20. $ &$ 0.197 \times 10^{-2}$ & $ 0.160 $ &$ 0.985 $ &$ 0.988 $ &$ 0.85 $ &$ 1.31 $ &$ 2.97 $ &$ 3.36$ & $ 252$ \\ $ 94 $ &$ 20. $ &$ 0.329 \times 10^{-2}$ & $ 0.096 $ &$ 0.869 $ &$ 0.869 $ &$ 1.09 $ &$ 1.42 $ &$ 3.05 $ &$ 3.54$ & $ 252$ \\ $ 95 $ &$ 25. $ &$ 0.493 \times 10^{-3}$ & $ 0.800 $ &$ 1.260 $ &$ 1.443 $ &$ 3.95 $ &$ 3.02 $ &$ 2.93 $ &$ 5.77$ & $ 252$ \\ $ 96 $ &$ 25. $ &$ 0.616 \times 10^{-3}$ & $ 0.800 $ &$ 1.210 $ &$ 1.386 $ &$ 2.42 $ &$ 2.94 $ &$ 3.04 $ &$ 4.87$ & $ 225$ \\ $ 97 $ &$ 25. $ &$ 0.616 \times 10^{-3}$ & $ 0.640 $ &$ 1.268 $ &$ 1.370 $ &$ 2.19 $ &$ 2.46 $ &$ 2.90 $ &$ 4.39$ & $ 252$ \\ $ 98 $ &$ 25. $ &$ 0.759 \times 10^{-3}$ & $ 0.650 $ &$ 1.240 $ &$ 1.344 $ &$ 2.00 $ &$ 2.43 $ &$ 2.94 $ &$ 4.31$ & $ 225$ \\ $ 99 $ &$ 25. $ &$ 0.759 \times 10^{-3}$ & $ 0.520 $ &$ 1.216 $ &$ 1.273 $ &$ 2.61 $ &$ 2.06 $ &$ 3.00 $ &$ 4.48$ & $ 252$ \\ $ 100 $ &$ 25. $ &$ 0.101 \times 10^{-2}$ & $ 0.490 $ &$ 1.193 $ &$ 1.242 $ &$ 1.10 $ &$ 1.86 $ &$ 3.05 $ &$ 3.74$ & $ 225$ \\ $ 101 $ &$ 25. $ &$ 0.101 \times 10^{-2}$ & $ 0.392 $ &$ 1.223 $ &$ 1.252 $ &$ 1.54 $ &$ 1.86 $ &$ 2.95 $ &$ 3.82$ & $ 252$ \\ $ 102 $ &$ 25. $ &$ 0.159 \times 10^{-2}$ & $ 0.248 $ &$ 1.106 $ &$ 1.115 $ &$ 0.93 $ &$ 1.33 $ &$ 2.92 $ &$ 3.34$ & $ 252$ \\ $ 103 $ &$ 25. $ &$ 0.247 \times 10^{-2}$ & $ 0.160 $ &$ 1.001 $ &$ 1.004 $ &$ 0.95 $ &$ 1.34 $ &$ 3.08 $ &$ 3.49$ & $ 252$ \\ $ 104 $ &$ 25. $ &$ 0.411 \times 10^{-2}$ & $ 0.096 $ &$ 0.868 $ &$ 0.869 $ &$ 1.22 $ &$ 1.47 $ &$ 3.04 $ &$ 3.59$ & $ 252$ \\ $ 105 $ &$ 35. $ &$ 0.727 \times 10^{-3}$ & $ 0.760 $ &$ 1.434 $ &$ 1.617 $ &$ 6.28 $ &$ 3.72 $ &$ 3.33 $ &$ 8.02$ & $ 252$ \\ $ 106 $ &$ 35. $ &$ 0.812 \times 10^{-3}$ & $ 0.680 $ &$ 1.359 $ &$ 1.488 $ &$ 3.52 $ &$ 2.60 $ &$ 3.05 $ &$ 5.33$ & $ 252$ \\ $ 107 $ &$ 35. $ &$ 0.921 \times 10^{-3}$ & $ 0.750 $ &$ 1.110 $ &$ 1.246 $ &$ 3.83 $ &$ 3.32 $ &$ 3.22 $ &$ 6.01$ & $ 225$ \\ $ 108 $ &$ 35. $ &$ 0.921 \times 10^{-3}$ & $ 0.600 $ &$ 1.338 $ &$ 1.430 $ &$ 3.13 $ &$ 2.52 $ &$ 2.94 $ &$ 4.98$ & $ 252$ \\ $ 109 $ &$ 35. $ &$ 0.106 \times 10^{-2}$ & $ 0.650 $ &$ 1.228 $ &$ 1.331 $ &$ 2.23 $ &$ 2.50 $ &$ 3.09 $ &$ 4.56$ & $ 225$ \\ $ 110 $ &$ 35. $ &$ 0.106 \times 10^{-2}$ & $ 0.520 $ &$ 1.309 $ &$ 1.371 $ &$ 2.74 $ &$ 2.11 $ &$ 3.01 $ &$ 4.58$ & $ 252$ \\ $ 111 $ &$ 35. $ &$ 0.141 \times 10^{-2}$ & $ 0.490 $ &$ 1.198 $ &$ 1.247 $ &$ 1.14 $ &$ 1.87 $ &$ 2.99 $ &$ 3.71$ & $ 225$ \\ $ 112 $ &$ 35. $ &$ 0.141 \times 10^{-2}$ & $ 0.392 $ &$ 1.250 $ &$ 1.280 $ &$ 1.55 $ &$ 1.87 $ &$ 2.92 $ &$ 3.80$ & $ 252$ \\ $ 113 $ &$ 35. $ &$ 0.223 \times 10^{-2}$ & $ 0.248 $ &$ 1.100 $ &$ 1.109 $ &$ 0.98 $ &$ 1.34 $ &$ 2.90 $ &$ 3.34$ & $ 252$ \\ $ 114 $ &$ 35. $ &$ 0.345 \times 10^{-2}$ & $ 0.160 $ &$ 0.977 $ &$ 0.981 $ &$ 1.07 $ &$ 1.36 $ &$ 2.93 $ &$ 3.40$ & $ 252$ \\ $ 115 $ &$ 35. $ &$ 0.575 \times 10^{-2}$ & $ 0.096 $ &$ 0.849 $ &$ 0.850 $ &$ 1.36 $ &$ 1.52 $ &$ 3.26 $ &$ 3.85$ & $ 252$ \\ $ 116 $ &$ 45. $ &$ 0.104 \times 10^{-2}$ & $ 0.680 $ &$ 1.270 $ &$ 1.390 $ &$ 6.37 $ &$ 3.42 $ &$ 2.87 $ &$ 7.78$ & $ 252$ \\ $ 117 $ &$ 45. $ &$ 0.118 \times 10^{-2}$ & $ 0.600 $ &$ 1.262 $ &$ 1.348 $ &$ 3.81 $ &$ 2.68 $ &$ 2.92 $ &$ 5.50$ & $ 252$ \\ $ 118 $ &$ 45. $ &$ 0.137 \times 10^{-2}$ & $ 0.650 $ &$ 1.261 $ &$ 1.367 $ &$ 3.13 $ &$ 2.84 $ &$ 2.91 $ &$ 5.13$ & $ 225$ \\ $ 119 $ &$ 45. $ &$ 0.137 \times 10^{-2}$ & $ 0.520 $ &$ 1.287 $ &$ 1.348 $ &$ 3.08 $ &$ 2.20 $ &$ 2.87 $ &$ 4.75$ & $ 252$ \\ $ 120 $ &$ 45. $ &$ 0.181 \times 10^{-2}$ & $ 0.490 $ &$ 1.189 $ &$ 1.238 $ &$ 1.29 $ &$ 1.91 $ &$ 3.01 $ &$ 3.79$ & $ 225$ \\ $ 121 $ &$ 45. $ &$ 0.181 \times 10^{-2}$ & $ 0.392 $ &$ 1.189 $ &$ 1.217 $ &$ 1.70 $ &$ 1.89 $ &$ 2.91 $ &$ 3.87$ & $ 252$ \\ $ 122 $ &$ 45. $ &$ 0.286 \times 10^{-2}$ & $ 0.248 $ &$ 1.095 $ &$ 1.104 $ &$ 1.01 $ &$ 1.35 $ &$ 2.87 $ &$ 3.33$ & $ 252$ \\ $ 123 $ &$ 45. $ &$ 0.444 \times 10^{-2}$ & $ 0.160 $ &$ 0.948 $ &$ 0.951 $ &$ 1.09 $ &$ 1.37 $ &$ 2.95 $ &$ 3.43$ & $ 252$ \\ $ 124 $ &$ 45. $ &$ 0.740 \times 10^{-2}$ & $ 0.096 $ &$ 0.812 $ &$ 0.812 $ &$ 1.42 $ &$ 1.54 $ &$ 3.18 $ &$ 3.80$ & $ 252$ \\ $ 125 $ &$ 60. $ &$ 0.158 \times 10^{-2}$ & $ 0.600 $ &$ 1.282 $ &$ 1.370 $ &$ 8.42 $ &$ 4.22 $ &$ 3.23 $ &$ 9.96$ & $ 252$ \\ $ 126 $ &$ 60. $ &$ 0.182 \times 10^{-2}$ & $ 0.520 $ &$ 1.258 $ &$ 1.318 $ &$ 4.24 $ &$ 2.54 $ &$ 2.91 $ &$ 5.73$ & $ 252$ \\ $ 127 $ &$ 60. $ &$ 0.242 \times 10^{-2}$ & $ 0.490 $ &$ 1.204 $ &$ 1.254 $ &$ 1.63 $ &$ 2.01 $ &$ 3.01 $ &$ 3.97$ & $ 225$ \\ $ 128 $ &$ 60. $ &$ 0.242 \times 10^{-2}$ & $ 0.392 $ &$ 1.163 $ &$ 1.191 $ &$ 1.96 $ &$ 1.94 $ &$ 2.86 $ &$ 3.97$ & $ 252$ \\ $ 129 $ &$ 60. $ &$ 0.382 \times 10^{-2}$ & $ 0.248 $ &$ 1.032 $ &$ 1.041 $ &$ 1.16 $ &$ 1.38 $ &$ 2.87 $ &$ 3.39$ & $ 252$ \\ $ 130 $ &$ 60. $ &$ 0.592 \times 10^{-2}$ & $ 0.160 $ &$ 0.957 $ &$ 0.960 $ &$ 1.18 $ &$ 1.40 $ &$ 2.90 $ &$ 3.43$ & $ 252$ \\ $ 131 $ &$ 60. $ &$ 0.986 \times 10^{-2}$ & $ 0.096 $ &$ 0.791 $ &$ 0.791 $ &$ 1.51 $ &$ 1.58 $ &$ 3.01 $ &$ 3.72$ & $ 252$ \\ %\input{tables/p_3_lowe} $ 132 $ &$ 90. $ &$ 0.362 \times 10^{-2}$ & $ 0.490 $ &$ 1.100 $ &$ 1.145 $ &$ 3.36 $ &$ 2.72 $ &$ 3.06 $ &$ 5.29$ & $ 225$ \\ $ 133 $ &$ 90. $ &$ 0.362 \times 10^{-2}$ & $ 0.392 $ &$ 1.142 $ &$ 1.170 $ &$ 2.92 $ &$ 2.17 $ &$ 2.88 $ &$ 4.64$ & $ 252$ \\ $ 134 $ &$ 90. $ &$ 0.573 \times 10^{-2}$ & $ 0.248 $ &$ 0.954 $ &$ 0.962 $ &$ 1.43 $ &$ 1.45 $ &$ 2.85 $ &$ 3.50$ & $ 252$ \\ $ 135 $ &$ 90. $ &$ 0.888 \times 10^{-2}$ & $ 0.160 $ &$ 0.850 $ &$ 0.853 $ &$ 1.39 $ &$ 1.45 $ &$ 2.95 $ &$ 3.56$ & $ 252$ \\ $ 136 $ &$ 90. $ &$ 0.148 \times 10^{-1}$ & $ 0.096 $ &$ 0.728 $ &$ 0.729 $ &$ 1.74 $ &$ 1.67 $ &$ 2.94 $ &$ 3.80$ & $ 252$ \\ \hline \end{tabular} \end{center} \end{tiny} \tablecaption{\label{tablowea2}Continuation of \Tab~\ref{tablowea1}} %\small \end{table} \begin{table} \begin{center} \begin{tiny} \begin{tabular}{cc|ccccc|ccccc|c} \hline \\[-6pt] $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{F_L}$ & $\boldsymbol{\Delta_{\rm stat}F_L}$ & $\boldsymbol{\Delta_{\rm uncor}F_L}$ & $\boldsymbol{\Delta_{\rm cor}F_L}$ & $\boldsymbol{\Delta_{\rm tot}F_L}$ & $\boldsymbol{F_2}$ & $\boldsymbol{\Delta_{\rm stat} F_2}$ & $\boldsymbol{\Delta_{\rm uncor} F_2}$ & $\boldsymbol{\Delta_{\rm cor} F_2}$ & $\boldsymbol{\Delta_{\rm tot} F_2}$ & $\boldsymbol{\rho}$ \\ \hline \\[-6pt] %\input{tables/p_1_flf2615} $ 1.5 $ &$ 0.279 \times 10^{-4}$ & $ 0.091 $ &$ 0.114 $ &$ 0.188 $ &$ 0.054 $ &$ 0.226 $ &$ 0.740 $ &$ 0.066 $ &$0.097$ & $0.029$ & $0.121$ & $0.882$ \\ $ 2. $ &$ 0.372 \times 10^{-4}$ & $ 0.102 $ &$ 0.069 $ &$ 0.131 $ &$ 0.062 $ &$ 0.160 $ &$ 0.843 $ &$ 0.028 $ &$0.051$ & $0.032$ & $0.066$ & $0.855$ \\ $ 2. $ &$ 0.415 \times 10^{-4}$ & $ 0.419 $ &$ 0.110 $ &$ 0.181 $ &$ 0.071 $ &$ 0.223 $ &$ 0.903 $ &$ 0.039 $ &$0.060$ & $0.030$ & $0.078$ & $0.852$ \\ $ 2. $ &$ 0.464 \times 10^{-4}$ & $ 0.035 $ &$ 0.052 $ &$ 0.104 $ &$ 0.033 $ &$ 0.121 $ &$ 0.741 $ &$ 0.033 $ &$0.052$ & $0.009$ & $0.062$ & $0.821$ \\ $ 2.5 $ &$ 0.465 \times 10^{-4}$ & $ 0.007 $ &$ 0.057 $ &$ 0.120 $ &$ 0.047 $ &$ 0.141 $ &$ 0.847 $ &$ 0.022 $ &$0.045$ & $0.016$ & $0.053$ & $0.856$ \\ $ 2.5 $ &$ 0.519 \times 10^{-4}$ & $ 0.093 $ &$ 0.062 $ &$ 0.129 $ &$ 0.043 $ &$ 0.149 $ &$ 0.897 $ &$ 0.023 $ &$0.045$ & $0.016$ & $0.053$ & $0.859$ \\ $ 2.5 $ &$ 0.580 \times 10^{-4}$ & $ 0.167 $ &$ 0.047 $ &$ 0.090 $ &$ 0.059 $ &$ 0.117 $ &$ 0.890 $ &$ 0.021 $ &$0.035$ & $0.028$ & $0.049$ & $0.819$ \\ $ 2.5 $ &$ 0.658 \times 10^{-4}$ & $ 0.161 $ &$ 0.043 $ &$ 0.099 $ &$ 0.064 $ &$ 0.125 $ &$ 0.866 $ &$ 0.019 $ &$0.035$ & $0.031$ & $0.050$ & $0.838$ \\ $ 2.5 $ &$ 0.759 \times 10^{-4}$ & $ 0.396 $ &$ 0.096 $ &$ 0.155 $ &$ 0.080 $ &$ 0.199 $ &$ 0.877 $ &$ 0.024 $ &$0.035$ & $0.026$ & $0.050$ & $0.781$ \\ $ 3.5 $ &$ 0.651 \times 10^{-4}$ & $ 0.128 $ &$ 0.065 $ &$ 0.135 $ &$ 0.053 $ &$ 0.159 $ &$ 0.978 $ &$ 0.025 $ &$0.051$ & $0.022$ & $0.061$ & $0.844$ \\ $ 3.5 $ &$ 0.727 \times 10^{-4}$ & $ 0.198 $ &$ 0.061 $ &$ 0.133 $ &$ 0.044 $ &$ 0.153 $ &$ 0.995 $ &$ 0.024 $ &$0.047$ & $0.022$ & $0.057$ & $0.848$ \\ $ 3.5 $ &$ 0.812 \times 10^{-4}$ & $ 0.248 $ &$ 0.045 $ &$ 0.094 $ &$ 0.041 $ &$ 0.112 $ &$ 0.986 $ &$ 0.019 $ &$0.036$ & $0.016$ & $0.044$ & $0.807$ \\ $ 3.5 $ &$ 0.921 \times 10^{-4}$ & $ 0.227 $ &$ 0.037 $ &$ 0.099 $ &$ 0.038 $ &$ 0.112 $ &$ 0.973 $ &$ 0.015 $ &$0.034$ & $0.015$ & $0.040$ & $0.811$ \\ $ 3.5 $ &$ 0.106 \times 10^{-3}$ & $ 0.144 $ &$ 0.049 $ &$ 0.124 $ &$ 0.048 $ &$ 0.141 $ &$ 0.937 $ &$ 0.015 $ &$0.032$ & $0.010$ & $0.037$ & $0.793$ \\ $ 3.5 $ &$ 0.141 \times 10^{-3}$ & $ 0.630 $ &$ 0.112 $ &$ 0.221 $ &$ 0.127 $ &$ 0.278 $ &$ 0.938 $ &$ 0.011 $ &$0.028$ & $0.012$ & $0.032$ & $0.731$ \\ $ 5. $ &$ 0.931 \times 10^{-4}$ & $ 0.411 $ &$ 0.081 $ &$ 0.163 $ &$ 0.069 $ &$ 0.194 $ &$ 1.157 $ &$ 0.031 $ &$0.061$ & $0.032$ & $0.075$ & $0.843$ \\ $ 5. $ &$ 0.104 \times 10^{-3}$ & $ 0.341 $ &$ 0.065 $ &$ 0.143 $ &$ 0.044 $ &$ 0.163 $ &$ 1.078 $ &$ 0.027 $ &$0.052$ & $0.024$ & $0.063$ & $0.856$ \\ $ 5. $ &$ 0.116 \times 10^{-3}$ & $ 0.254 $ &$ 0.048 $ &$ 0.109 $ &$ 0.049 $ &$ 0.129 $ &$ 1.133 $ &$ 0.021 $ &$0.042$ & $0.018$ & $0.051$ & $0.824$ \\ $ 5. $ &$ 0.131 \times 10^{-3}$ & $ 0.305 $ &$ 0.037 $ &$ 0.110 $ &$ 0.042 $ &$ 0.123 $ &$ 1.088 $ &$ 0.016 $ &$0.037$ & $0.018$ & $0.044$ & $0.825$ \\ $ 5. $ &$ 0.152 \times 10^{-3}$ & $ 0.217 $ &$ 0.044 $ &$ 0.135 $ &$ 0.046 $ &$ 0.149 $ &$ 1.065 $ &$ 0.014 $ &$0.035$ & $0.015$ & $0.040$ & $0.827$ \\ $ 5. $ &$ 0.201 \times 10^{-3}$ & $ 0.512 $ &$ 0.057 $ &$ 0.203 $ &$ 0.088 $ &$ 0.229 $ &$ 1.022 $ &$ 0.009 $ &$0.028$ & $0.013$ & $0.032$ & $0.798$ \\ $ 6.5 $ &$ 0.121 \times 10^{-3}$ & $ 0.429 $ &$ 0.096 $ &$ 0.180 $ &$ 0.077 $ &$ 0.218 $ &$ 1.219 $ &$ 0.037 $ &$0.066$ & $0.027$ & $0.080$ & $0.852$ \\ $ 6.5 $ &$ 0.135 \times 10^{-3}$ & $ 0.196 $ &$ 0.071 $ &$ 0.151 $ &$ 0.043 $ &$ 0.172 $ &$ 1.108 $ &$ 0.030 $ &$0.055$ & $0.020$ & $0.066$ & $0.860$ \\ $ 6.5 $ &$ 0.151 \times 10^{-3}$ & $ 0.136 $ &$ 0.051 $ &$ 0.114 $ &$ 0.054 $ &$ 0.136 $ &$ 1.142 $ &$ 0.023 $ &$0.045$ & $0.023$ & $0.055$ & $0.840$ \\ $ 6.5 $ &$ 0.171 \times 10^{-3}$ & $ 0.356 $ &$ 0.040 $ &$ 0.120 $ &$ 0.045 $ &$ 0.134 $ &$ 1.166 $ &$ 0.017 $ &$0.041$ & $0.020$ & $0.049$ & $0.839$ \\ $ 6.5 $ &$ 0.197 \times 10^{-3}$ & $ 0.316 $ &$ 0.044 $ &$ 0.146 $ &$ 0.055 $ &$ 0.162 $ &$ 1.154 $ &$ 0.014 $ &$0.038$ & $0.019$ & $0.045$ & $0.848$ \\ $ 6.5 $ &$ 0.262 \times 10^{-3}$ & $ 0.186 $ &$ 0.046 $ &$ 0.206 $ &$ 0.093 $ &$ 0.231 $ &$ 1.051 $ &$ 0.007 $ &$0.029$ & $0.018$ & $0.035$ & $0.832$ \\ $ 8.5 $ &$ 0.158 \times 10^{-3}$ & $ 0.497 $ &$ 0.109 $ &$ 0.196 $ &$ 0.095 $ &$ 0.244 $ &$ 1.360 $ &$ 0.044 $ &$0.074$ & $0.034$ & $0.093$ & $0.844$ \\ $ 8.5 $ &$ 0.177 \times 10^{-3}$ & $ 0.480 $ &$ 0.089 $ &$ 0.184 $ &$ 0.052 $ &$ 0.211 $ &$ 1.339 $ &$ 0.038 $ &$0.068$ & $0.022$ & $0.080$ & $0.860$ \\ $ 8.5 $ &$ 0.197 \times 10^{-3}$ & $ 0.268 $ &$ 0.058 $ &$ 0.123 $ &$ 0.058 $ &$ 0.148 $ &$ 1.202 $ &$ 0.027 $ &$0.048$ & $0.021$ & $0.059$ & $0.838$ \\ $ 8.5 $ &$ 0.224 \times 10^{-3}$ & $ 0.240 $ &$ 0.045 $ &$ 0.126 $ &$ 0.043 $ &$ 0.140 $ &$ 1.164 $ &$ 0.019 $ &$0.043$ & $0.017$ & $0.050$ & $0.844$ \\ $ 8.5 $ &$ 0.258 \times 10^{-3}$ & $ -.123 $ &$ 0.045 $ &$ 0.141 $ &$ 0.053 $ &$ 0.157 $ &$ 1.044 $ &$ 0.015 $ &$0.036$ & $0.016$ & $0.042$ & $0.848$ \\ $ 8.5 $ &$ 0.342 \times 10^{-3}$ & $ 0.163 $ &$ 0.045 $ &$ 0.217 $ &$ 0.093 $ &$ 0.241 $ &$ 1.102 $ &$ 0.007 $ &$0.030$ & $0.017$ & $0.036$ & $0.836$ \\ $ 12. $ &$ 0.223 \times 10^{-3}$ & $ 0.088 $ &$ 0.101 $ &$ 0.159 $ &$ 0.085 $ &$ 0.207 $ &$ 1.318 $ &$ 0.039 $ &$0.041$ & $0.045$ & $0.072$ & $0.853$ \\ $ 12. $ &$ 0.249 \times 10^{-3}$ & $ 0.533 $ &$ 0.098 $ &$ 0.155 $ &$ 0.059 $ &$ 0.193 $ &$ 1.392 $ &$ 0.035 $ &$0.036$ & $0.028$ & $0.057$ & $0.833$ \\ $ 12. $ &$ 0.278 \times 10^{-3}$ & $ 0.272 $ &$ 0.059 $ &$ 0.098 $ &$ 0.048 $ &$ 0.124 $ &$ 1.313 $ &$ 0.024 $ &$0.024$ & $0.019$ & $0.039$ & $0.751$ \\ $ 12. $ &$ 0.316 \times 10^{-3}$ & $ 0.239 $ &$ 0.050 $ &$ 0.100 $ &$ 0.039 $ &$ 0.118 $ &$ 1.261 $ &$ 0.019 $ &$0.023$ & $0.015$ & $0.033$ & $0.724$ \\ $ 12. $ &$ 0.364 \times 10^{-3}$ & $ 0.423 $ &$ 0.055 $ &$ 0.121 $ &$ 0.044 $ &$ 0.140 $ &$ 1.273 $ &$ 0.016 $ &$0.022$ & $0.014$ & $0.030$ & $0.716$ \\ $ 12. $ &$ 0.483 \times 10^{-3}$ & $ 0.397 $ &$ 0.050 $ &$ 0.163 $ &$ 0.067 $ &$ 0.183 $ &$ 1.194 $ &$ 0.007 $ &$0.016$ & $0.012$ & $0.021$ & $0.630$ \\ $ 15. $ &$ 0.279 \times 10^{-3}$ & $ 0.502 $ &$ 0.109 $ &$ 0.184 $ &$ 0.086 $ &$ 0.230 $ &$ 1.489 $ &$ 0.040 $ &$0.048$ & $0.049$ & $0.079$ & $0.853$ \\ $ 15. $ &$ 0.312 \times 10^{-3}$ & $ 0.137 $ &$ 0.088 $ &$ 0.150 $ &$ 0.053 $ &$ 0.181 $ &$ 1.373 $ &$ 0.032 $ &$0.035$ & $0.027$ & $0.055$ & $0.832$ \\ $ 15. $ &$ 0.348 \times 10^{-3}$ & $ 0.177 $ &$ 0.061 $ &$ 0.099 $ &$ 0.040 $ &$ 0.123 $ &$ 1.332 $ &$ 0.023 $ &$0.023$ & $0.017$ & $0.037$ & $0.742$ \\ $ 15. $ &$ 0.395 \times 10^{-3}$ & $ 0.408 $ &$ 0.051 $ &$ 0.100 $ &$ 0.038 $ &$ 0.118 $ &$ 1.325 $ &$ 0.017 $ &$0.021$ & $0.015$ & $0.031$ & $0.700$ \\ $ 15. $ &$ 0.455 \times 10^{-3}$ & $ 0.246 $ &$ 0.062 $ &$ 0.118 $ &$ 0.047 $ &$ 0.141 $ &$ 1.273 $ &$ 0.015 $ &$0.019$ & $0.013$ & $0.027$ & $0.682$ \\ $ 15. $ &$ 0.604 \times 10^{-3}$ & $ 0.048 $ &$ 0.054 $ &$ 0.157 $ &$ 0.070 $ &$ 0.180 $ &$ 1.184 $ &$ 0.007 $ &$0.014$ & $0.012$ & $0.020$ & $0.598$ \\ $ 20. $ &$ 0.372 \times 10^{-3}$ & $ 0.209 $ &$ 0.116 $ &$ 0.197 $ &$ 0.066 $ &$ 0.238 $ &$ 1.455 $ &$ 0.041 $ &$0.051$ & $0.033$ & $0.073$ & $0.876$ \\ $ 20. $ &$ 0.415 \times 10^{-3}$ & $ 0.309 $ &$ 0.092 $ &$ 0.158 $ &$ 0.045 $ &$ 0.189 $ &$ 1.426 $ &$ 0.032 $ &$0.037$ & $0.022$ & $0.054$ & $0.835$ \\ $ 20. $ &$ 0.464 \times 10^{-3}$ & $ 0.402 $ &$ 0.070 $ &$ 0.108 $ &$ 0.038 $ &$ 0.135 $ &$ 1.400 $ &$ 0.024 $ &$0.025$ & $0.016$ & $0.038$ & $0.745$ \\ $ 20. $ &$ 0.526 \times 10^{-3}$ & $ 0.347 $ &$ 0.052 $ &$ 0.103 $ &$ 0.039 $ &$ 0.122 $ &$ 1.358 $ &$ 0.018 $ &$0.021$ & $0.016$ & $0.032$ & $0.698$ \\ $ 20. $ &$ 0.607 \times 10^{-3}$ & $ 0.289 $ &$ 0.062 $ &$ 0.119 $ &$ 0.043 $ &$ 0.141 $ &$ 1.299 $ &$ 0.015 $ &$0.019$ & $0.013$ & $0.027$ & $0.680$ \\ $ 20. $ &$ 0.805 \times 10^{-3}$ & $ 0.194 $ &$ 0.060 $ &$ 0.163 $ &$ 0.071 $ &$ 0.188 $ &$ 1.227 $ &$ 0.007 $ &$0.014$ & $0.012$ & $0.020$ & $0.586$ \\ $ 25. $ &$ 0.493 \times 10^{-3}$ & $ 0.350 $ &$ 0.072 $ &$ 0.157 $ &$ 0.044 $ &$ 0.178 $ &$ 1.487 $ &$ 0.022 $ &$0.040$ & $0.024$ & $0.052$ & $0.848$ \\ $ 25. $ &$ 0.616 \times 10^{-3}$ & $ 0.274 $ &$ 0.043 $ &$ 0.089 $ &$ 0.032 $ &$ 0.104 $ &$ 1.386 $ &$ 0.013 $ &$0.021$ & $0.014$ & $0.028$ & $0.686$ \\ $ 25. $ &$ 0.759 \times 10^{-3}$ & $ 0.281 $ &$ 0.065 $ &$ 0.125 $ &$ 0.044 $ &$ 0.147 $ &$ 1.334 $ &$ 0.015 $ &$0.020$ & $0.013$ & $0.028$ & $0.687$ \\ $ 25. $ &$ 0.101 \times 10^{-2}$ & $ 0.149 $ &$ 0.064 $ &$ 0.168 $ &$ 0.071 $ &$ 0.193 $ &$ 1.240 $ &$ 0.008 $ &$0.014$ & $0.012$ & $0.020$ & $0.595$ \\ $ 35. $ &$ 0.727 \times 10^{-3}$ & $ 0.019 $ &$ 0.144 $ &$ 0.233 $ &$ 0.067 $ &$ 0.281 $ &$ 1.419 $ &$ 0.038 $ &$0.048$ & $0.020$ & $0.065$ & $0.882$ \\ $ 35. $ &$ 0.812 \times 10^{-3}$ & $ 0.104 $ &$ 0.119 $ &$ 0.190 $ &$ 0.051 $ &$ 0.230 $ &$ 1.416 $ &$ 0.030 $ &$0.036$ & $0.020$ & $0.051$ & $0.825$ \\ $ 35. $ &$ 0.921 \times 10^{-3}$ & $ 0.423 $ &$ 0.080 $ &$ 0.125 $ &$ 0.042 $ &$ 0.154 $ &$ 1.409 $ &$ 0.022 $ &$0.024$ & $0.014$ & $0.036$ & $0.720$ \\ $ 35. $ &$ 0.106 \times 10^{-2}$ & $ 0.185 $ &$ 0.072 $ &$ 0.131 $ &$ 0.044 $ &$ 0.156 $ &$ 1.329 $ &$ 0.017 $ &$0.021$ & $0.013$ & $0.030$ & $0.688$ \\ $ 35. $ &$ 0.141 \times 10^{-2}$ & $ 0.036 $ &$ 0.067 $ &$ 0.170 $ &$ 0.069 $ &$ 0.195 $ &$ 1.230 $ &$ 0.008 $ &$0.015$ & $0.012$ & $0.021$ & $0.618$ \\ $ 45. $ &$ 0.104 \times 10^{-2}$ & $ 0.358 $ &$ 0.177 $ &$ 0.276 $ &$ 0.037 $ &$ 0.330 $ &$ 1.433 $ &$ 0.036 $ &$0.046$ & $0.016$ & $0.060$ & $0.864$ \\ $ 45. $ &$ 0.118 \times 10^{-2}$ & $ 0.405 $ &$ 0.159 $ &$ 0.254 $ &$ 0.046 $ &$ 0.303 $ &$ 1.401 $ &$ 0.029 $ &$0.036$ & $0.014$ & $0.048$ & $0.823$ \\ $ 45. $ &$ 0.137 \times 10^{-2}$ & $ 0.236 $ &$ 0.100 $ &$ 0.151 $ &$ 0.050 $ &$ 0.188 $ &$ 1.353 $ &$ 0.021 $ &$0.023$ & $0.014$ & $0.034$ & $0.720$ \\ $ 45. $ &$ 0.181 \times 10^{-2}$ & $ 0.077 $ &$ 0.075 $ &$ 0.176 $ &$ 0.069 $ &$ 0.203 $ &$ 1.214 $ &$ 0.009 $ &$0.016$ & $0.012$ & $0.022$ & $0.640$ \\ \hline \end{tabular} \end{tiny} \end{center} \tablecaption{\label{tab:flf2xq}The proton structure functions $F_L$ and $F_2$ measured at the given values of $Q^2$ and $x$ without model assumptions. $\Delta_{\rm stat}F_L$, $\Delta_{\rm uncor}F_L$, $\Delta_{\rm cor}F_L$ and $\Delta_{\rm tot}F_L$ are the statistical, uncorrelated systematic, correlated systematic and total uncertainty on $F_L$, respectively. $\Delta_{\rm stat}F_2$, $\Delta_{\rm uncor}F_2$, $\Delta_{\rm cor}F_2$ and $\Delta_{\rm tot}F_2$ are the statistical, uncorrelated systematic, correlated systematic and total uncertainty on $F_2$, respectively. $\rho$ is the correlation coefficient between the $F_L$ and $F_2$ values. } \end{table} \begin{table} \begin{scriptsize} \begin{center} \begin{tabular}{cccccccc} \hline \\[-8pt] $\boldsymbol{Q^2}$ & $\boldsymbol{x}$ & $\boldsymbol{F_L}$ & $\boldsymbol{\Delta_{\rm stat}}$ & $\boldsymbol{\Delta_{\rm uncor}}$ & $\boldsymbol{\Delta_{\rm cor}}$ & $\boldsymbol{\Delta_{\rm tot}}$\\ {\bf GeV}$\boldsymbol{^2}$& \\ \hline \\[-8pt] %\input{tables/ave_fl} $ 1.5 $ &$ 0.279 \times 10^{-4}$ & $ 0.091 $ &$ 0.114 $ &$ 0.188 $ &$ 0.054 $ &$0.226$ \\ $ 2. $ &$ 0.427 \times 10^{-4}$ & $ 0.117 $ &$ 0.039 $ &$ 0.074 $ &$ 0.017 $ &$0.086$ \\ $ 2.5 $ &$ 0.588 \times 10^{-4}$ & $ 0.147 $ &$ 0.025 $ &$ 0.050 $ &$ 0.008 $ &$0.056$ \\ $ 3.5 $ &$ 0.877 \times 10^{-4}$ & $ 0.222 $ &$ 0.021 $ &$ 0.049 $ &$ 0.006 $ &$0.054$ \\ $ 5. $ &$ 0.129 \times 10^{-3}$ & $ 0.310 $ &$ 0.022 $ &$ 0.055 $ &$ 0.007 $ &$0.059$ \\ $ 6.5 $ &$ 0.169 \times 10^{-3}$ & $ 0.263 $ &$ 0.023 $ &$ 0.059 $ &$ 0.008 $ &$0.064$ \\ $ 8.5 $ &$ 0.224 \times 10^{-3}$ & $ 0.213 $ &$ 0.025 $ &$ 0.063 $ &$ 0.009 $ &$0.068$ \\ $ 12. $ &$ 0.319 \times 10^{-3}$ & $ 0.314 $ &$ 0.027 $ &$ 0.051 $ &$ 0.008 $ &$0.058$ \\ $ 15. $ &$ 0.402 \times 10^{-3}$ & $ 0.255 $ &$ 0.027 $ &$ 0.051 $ &$ 0.008 $ &$0.058$ \\ $ 20. $ &$ 0.540 \times 10^{-3}$ & $ 0.315 $ &$ 0.029 $ &$ 0.053 $ &$ 0.009 $ &$0.061$ \\ $ 25. $ &$ 0.686 \times 10^{-3}$ & $ 0.269 $ &$ 0.029 $ &$ 0.061 $ &$ 0.010 $ &$0.069$ \\ $ 35. $ &$ 0.103 \times 10^{-2}$ & $ 0.201 $ &$ 0.040 $ &$ 0.070 $ &$ 0.014 $ &$0.082$ \\ $ 45. $ &$ 0.146 \times 10^{-2}$ & $ 0.219 $ &$ 0.056 $ &$ 0.098 $ &$ 0.024 $ &$0.116$ \\ \hline \end{tabular} \end{center} \end{scriptsize} \tablecaption{\label{tab:flave} The proton structure function $F_L(x,Q^2)$ obtained by averaging $F_L$ data from \Tab~\ref{tab:flf2xq} for each $Q^2$ bin at the given values of $Q^2$ and $x$. $\Delta_{\rm stat}$, $\Delta_{\rm uncor}$, $\Delta_{\rm cor}$ and $\Delta_{\rm tot}$ are the statistical, uncorrelated systematic, correlated systematic and total uncertainty on $F_L$, respectively. } \end{table} \clearpage %\input{figures} \begin{figure}[b] \begin{center} \includegraphics[angle =90, width=0.6\linewidth]{d10-228f1.eps} %\epsfig{file=figs/event.eps, bburx=500, bbury=543,bbllx=69,bblly=0, angle=90,width=0.6\linewidth} %\end{center} \put(-130,53){\vector(1,0){10}} \put(-130,55){e} \put(40,53){\vector(-1,0){10}} \put(40,55){p} \put(30,0){\vector(-1,0){10}} \put(30,0){\vector(0,1){10}} \put(20,-3){z} \put(32,7){r} \put(-5,90){\LARGE\bf H1} \put(-85,81){\large\bf LAr calorimeter} \put(-85,85){hadronic} \put(-85,77){electromagnetic} \put(-40,66){\large\bf central tracker} \put(-20,45){CJC1} \put(-20,37){CJC2} \put(-8,53){BST} \put(2,35){BPC} \put(10,71){\large\bf SpaCal} \put(10,66){em~~~~~had} \put(0,49){CIP} \end{center} \caption{A high $y$ event as reconstructed in the H1 detector. The scattered electron is measured in the SpaCal calorimeter. The electron trajectory, shown by a thick line, is reconstructed in the backward silicon tracker (BST) and in the inner central jet chamber (CJC1). The trajectory crosses the central inner proportional chamber (CIP) which is used for triggering. The backward proportional chamber (BPC) may assists the measurement of the scattering angle. The hadronic final state particles are detected in the central tracker, liquid argon calorimeter (LAr) and in the SpaCal electromagnetic and hadronic sections. \label{fig:event}} \end{figure} \begin{figure} \epsfig{file=d10-228f2.eps,width=\linewidth} \caption{\label{fig:eid}Distribution of variables used for the scattered lepton identification, for the \ler\ sample: a) logarithmic cluster radius $R_{\log}$; b) square root weighted cluster radius {\tt ECRA}; c) fraction of energy in the four hottest cells of the cluster $R_4$; d) ratio of the energy in the hadronic section of the SpaCal in the cone behind the electron candidate to the electron candidate energy $E_h/E'_e$; e) distance between BC track extrapolated to the SpaCal cluster $Z$ and the cluster $D_{BC}$; f) ratio of the lepton candidate energy to the track momentum $\ee/p_e$. The data are shown as dots, the background as shaded histograms and the sum of the signal MC simulation and the background as open histograms. The vertical lines indicate the value of the electron identification cuts. The arrow points in the direction of the part of the distribution kept by the cut. The data are presented for $\ee<10$~GeV except for the $\ee/p_e$ plot which is shown for $\ee<7$~GeV. %Data are shown as dots with error bars, %the shaded histograms show the data driven estimation of the background %and the open histograms represent %the simulation of DIS signal. } \end{figure} \begin{figure} \epsfig{file=d10-228f3.eps,width=0.9\linewidth} \caption{\label{fig:charge} Sum of energies of the scattered electron and the photon for correct (a) and wrong (b) charge of the lepton candidate, for the dedicated selection of events with hard initial state radiation. The distributions are fitted by the sum of a Gaussian and exponential distributions, the fit result is shown by the line. The data are taken from the \lermer\ samples.} \end{figure} \begin{figure} \epsfig{file=d10-228f4.eps,width=0.9\linewidth} \caption{\label{fig:empzrad} $\empz$ distribution for the \mer\ sample passing all cuts excluding cut on $\empz$ for $\ee<5$~GeV. The dots show the background subtracted data with statistical errors, the solid line is the total MC prediction, the dashed line, labeled MC NoRad+FSR, is the sum non-radiative and final state radiation components and the dotted line, labeled MC ISR+Compton, shows the sum of initial state radiation and QED-Compton contributions. } \end{figure} \begin{figure} \vspace{1cm} \centerline{\epsfig{file=d10-228f5a.eps,width=0.9\linewidth}} \vspace{-7.cm} \centerline{\epsfig{file=d10-228f5b.eps,width=0.9\linewidth}} \vspace{-7.cm} \caption{ Distributions of the scattered electron energy $E'_e$ (a), polar angle $\thetae$ (b), $\empz$ (c) and of the kinematic variables $y$ (d), $Q^2$ (e), $x$ (f) for events passing all analysis cuts from \ler\ sample. Data are shown as dots with statistical errors, the shaded histograms show the data driven estimation of the background and the shaded bands represent the simulation of DIS signal with statistical and systematic uncertainties added in quadrature. %Data are shown as dots with error bars, %open histogram represents the simulation of DIS %signal and shaded histogram shows the data driven estimation of the background. \label{fig:cont460}} \end{figure} \begin{figure} \vspace{1cm} \centerline{\epsfig{file=d10-228f6a.eps,width=0.9\linewidth}} \vspace{-7.cm} \centerline{\epsfig{file=d10-228f6b.eps,width=0.9\linewidth}} \vspace{-7.cm} \caption{ Distributions of the scattered electron energy $E'_e$ (a), polar angle $\thetae$ (b), $\empz$ (c) and of the kinematic variables $y$ (d), $Q^2$ (e), $x$ (f) for events passing all analysis cuts from \mer\ sample. Data are shown as dots with statistical errors, the shaded histograms show the data driven estimation of the background and the shaded bands represent the simulation of DIS signal with statistical and systematic uncertainties added in quadrature. %Data are shown as dots with error bars, %open histogram represents the simulation of DIS %signal and shaded histogram shows the data driven estimation of the background. \label{fig:cont575}} \end{figure} \begin{figure} \vspace{1cm} \centerline{\epsfig{file=d10-228f7a.eps,width=0.9\linewidth}} \vspace{-7.cm} \centerline{\epsfig{file=d10-228f7b.eps,width=0.9\linewidth}} \vspace{-7.cm} \caption{ Distributions of the scattered electron energy $E'_e$ (a), polar angle $\thetae$ (b), $\empz$ (c) and of the kinematic variables $y$ (d), $Q^2$ (e), $x$ (f) for events passing all analysis cuts from \lqbst\ sample. Data are shown as dots with statistical errors, the shaded histograms show the data driven estimation of the background and the shaded bands represent the simulation of DIS signal with statistical and systematic uncertainties added in quadrature. %Data are shown as dots with error bars, %open histogram represents the simulation of DIS %signal and shaded histogram shows the data driven estimation of the background. \label{fig:cont920a}} \end{figure} \begin{figure} \vspace{1cm} \centerline{\epsfig{file=d10-228f8a.eps,width=0.9\linewidth}} \vspace{-7.cm} \centerline{\epsfig{file=d10-228f8b.eps,width=0.9\linewidth}} \vspace{-7.cm} \caption{ Distributions of the scattered electron energy $E'_e$ (a), polar angle $\thetae$ (b), $\empz$ (c) and of the kinematic variables $y$ (d), $Q^2$ (e), $x$ (f) for events passing all analysis cuts from \hqcjc\ sample. Data are shown as dots with statistical errors, the shaded histograms show the data driven estimation of the background and the shaded bands represent the simulation of DIS signal with statistical and systematic uncertainties added in quadrature. %Data are shown as dots with error bars, %open histogram represents the simulation of DIS %signal and shaded histogram shows the data driven estimation of the background. \label{fig:cont920b}} \end{figure} %\begin{figure} %\centerline{\epsfig{file=figs/control06pm_v1001.eps,width=0.9\linewidth}} %\caption{Control plots BST \label{fig:cont920c}} %\end{figure} %\begin{figure} %\centerline{\epsfig{file=figs/e_peak_371_5.eps,width=0.9\linewidth}} %\caption{Kin. peak 2006 comb.} %\end{figure} %\begin{figure} %\centerline{\epsfig{file=figs/allavelow.eps,width=0.9\linewidth}} %\caption{Combined} %\end{figure} %\begin{figure} %\centerline{\epsfig{file=figs/allave.eps,width=0.9\linewidth}} %\caption{Combined} %\end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f9.eps,width=\linewidth}} \caption{Results on the reduced cross section $\sigma_r$ as determined from the $E_p=920$~GeV, $E_p=575$~GeV and $E_p=460$~GeV samples. The error bars represent statistical and systematic uncertainties added in quadrature. \label{fig:newdata}} \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f10.eps,width=0.9\linewidth}} \caption{\label{fig:rosen}The reduced DIS cross section $\sigma_r$ as a function of $y^2/(1+(1-y)^2)$ for six values of $x$ at $Q^2=6.5$~GeV$^2$, measured for proton beam energies of $E_p=920$, $575$ and $460$~GeV. The inner error bars denote the statistical error, the outer error bars show statistical and systematic uncertainties added in quadrature. The luminosity uncertainty is not included in the error bars. The slope of the straight-line fits is determined by the structure function $F_L(x,Q^2)$.} \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f11.eps,width=\linewidth}} \caption{The proton structure function $F_L(x,Q^2)$. The inner error bars represent statistical error, the full error bars include the statistical and systematic uncertainties added in quadrature, excluding $0.5\%$ global normalisation uncertainty. The curves represent predictions of the DGLAP fit in the ACOT scheme. \label{fig:flxq}} \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f12.eps,width=\linewidth}} \caption{The proton structure functions $F_2(x,Q^2)$ and $F_L(x,Q^2)$. The inner error bars represent statistical error, the full error bars include the statistical and systematic uncertainties added in quadrature, excluding $0.5\%$ global normalisation uncertainty. The curves represent predictions of the DGLAP fit in the ACOT scheme for the structure functions $F_2$ and $F_L$. \label{fig:flf2xq}} \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f13.eps,width=\linewidth}} \caption{\label{fig:flaveth}The proton structure function $F_L$ shown as a function of $Q^2$. The average $x$ values for each $Q^2$ are indicated. The inner error bars represent statistical error, the full error bars include the statistical and systematic uncertainties added in quadrature. The bands represent predictions based on HERAPDF1.0, CTEQ6.6 and NNPDF2.1 NLO as well as %DGLAP ACOT and RT as well as MSTW08, GJR08 and ABKM09 NNLO calculations. } \end{figure} \clearpage \begin{figure} \centerline{\epsfig{file=d10-228f14.eps,width=\linewidth}} \caption{The ratio $R=F_L(x,Q^2)/(F_2(x,Q^2)-F_L(x,Q^2))$. The inner error bars represent statistical error, the full error bars include the statistical and systematic uncertainties added in quadrature. The solid curves represent predictions of the DGLAP fit in ACOT scheme. \label{fig:flr}} \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f15.eps,width=0.6\linewidth}} \caption{\label{fig:rscan} $\chi^2$ for combination of the data taken at $E_p=920$, $575$ and $460$~GeV as a function of $R$ assuming $R$ being constant. The solid line shows parabolic fit around the $\chi^2$ minimum. The solid vertical line shows the value of $R_{\rm min}$ at which $\chi^2$ has the minimum and the dotted vertical lines correspond to the total uncertainty of $R_{\rm min}$.} \end{figure} %\begin{figure}[t] %\begin{center} %\begin{minipage}{0.9\linewidth} %\epsfig{file=figs/all_q21f2.eps,width=\linewidth} %\put(-22,3){\large\bf x} %\put(-68,3){\large\bf x} %\put(-110,3){\large\bf x} %\put(-157,55){\begin{sideways}\large\bf $\sigma_{r}$\end{sideways}} %\put(-157,105){\begin{sideways}\large\bf $\sigma_{r}$\end{sideways}} %\put(-157,155){\begin{sideways}\large\bf $\sigma_{r}$\end{sideways}} %\put(-157,205){\begin{sideways}\large\bf $\sigma_{r}$\end{sideways}} %\end{minipage} %\end{center} %\caption{ %\label{fig:xlamf2a}} %\end{figure} %\begin{figure}[t] %\begin{center} %\begin{minipage}{0.9\linewidth} %\epsfig{file=figs/all_q22f2.eps,width=\linewidth} %\put(-22,3){\large\bf x} %\put(-68,3){\large\bf x} %\put(-110,3){\large\bf x} %\put(-157,55){\begin{sideways}\large\bf $\sigma_{r}$\end{sideways}} %\put(-157,105){\begin{sideways}\large\bf $\sigma_{r}$\end{sideways}} %\put(-157,155){\begin{sideways}\large\bf $\sigma_{r}$\end{sideways}} %\put(-157,205){\begin{sideways}\large\bf $\sigma_{r}$\end{sideways}} %\end{minipage} %\end{center} %\caption{\FFig~\ref{fig:xlamf2a} continued. \label{fig:xlamf2b}} %\end{figure} \begin{figure} %\epsfig{file=figs/c_lambda_vs_q2.eps,width=\linewidth} %\put(-40,-3){\large\bf $Q^{2}/GeV^{2}$} %\put(-110,-3){\large\bf $Q^{2}/GeV^{2}$} %\put(-88,50){\begin{sideways}\large\bf $\lambda$\end{sideways}} %\put(-157,50){\begin{sideways}\large\bf C\end{sideways}} \begin{tabular}{cc} \begin{minipage}{0.5\linewidth} \hspace*{-1cm}\epsfig{file=d10-228f16a.eps,width=1.2\linewidth} \end{minipage} & \begin{minipage}{0.5\linewidth} \hspace*{-1cm}\epsfig{file=d10-228f16b.eps,width=1.2\linewidth} \end{minipage} \end{tabular} \caption{Coefficients $c$ and $\lambda$, as defined in \Eq~\ref{eq:lamfit}, determined from a fit to the data as a function of $Q^2$. The inner error bars represent statistical uncertainties. The outer error bars contain the statistical and systematic uncertainties added in quadrature. The line in b) is from a straight-line fit for $Q^2\ge 2$~GeV$^2$. \label{fig:xlamlc}} \end{figure} \begin{figure} \begin{tabular}{cc} \begin{minipage}{0.5\linewidth} \hspace*{-1cm}\epsfig{file=d10-228f17a.eps,width=1.2\linewidth} \end{minipage} & \begin{minipage}{0.5\linewidth} \hspace*{-1cm}\epsfig{file=d10-228f17b.eps,width=1.2\linewidth} \end{minipage} \end{tabular} \caption{ Coefficients $\lambda$ and $\lambda'$, as defined in \Eq~\ref{eq:lamprim}, determined from a fit to the H1 data as a function of $Q^2$. The inner error bars represent statistical uncertainties. The outer error bars contain the statistical and systematic uncertainties added in quadrature. The line in a) is from a constant fit for $Q^2\ge 2$~GeV$^2$. \label{fig:lamlamprim} } \end{figure} \begin{figure} \begin{tabular}{cc} \begin{minipage}{0.5\linewidth} \hspace*{-1cm}\epsfig{file=d10-228f18a.eps,width=1.2\linewidth} \end{minipage} & \begin{minipage}{0.5\linewidth} \hspace*{-1cm}\epsfig{file=d10-228f18b.eps,width=1.2\linewidth} \end{minipage} \end{tabular} \caption{Coefficients $c$ and $\lambda'$, as defined in \Eq~\ref{eq:lamprim}, determined from a fit to the H1 data as a function of $Q^2$ with fixed $\lambda=0.25$. The inner error bars represent statistical uncertainties. The outer error bars contain the statistical and systematic uncertainties added in quadrature. \label{fig:clamprim}} \end{figure} \begin{figure}[t] \begin{center} \epsfig{file=d10-228f19.eps,width=0.9\linewidth} \end{center} \caption{ Reduced cross section $\sigma_{r}$ as a function of $x$ for different $Q^2$ bins for $Q^2\le 5$~GeV$^2$. The H1 data are compared to the $\lambda'$ fit result (shown by curves) for different proton beam energies $E_p$. \label{fig:xlam1}} \end{figure} \begin{figure}[t] \begin{center} \epsfig{file=d10-228f20.eps,width=0.9\linewidth} \end{center} \caption{ Reduced cross section $\sigma_{r}$ as a function of $x$ for different $Q^2$ bins for $Q^2> 5$~GeV$^2$. The H1 data are compared to the $\lambda'$ fit result (shown by curves) for different proton beam energies $E_p$. \label{fig:xlam2}} \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f21.eps,width=\linewidth}} \caption{ Structure function $F_2(x,Q^2)$ as a function of $x$ calculated from the reduced cross section using $R=0.26$ for different $Q^2$ bins. The H1 data for different proton beam energies $E_p$ are compared to the $\lambda$ and $\lambda'$ fit results. \label{fig:f2}} \end{figure} %\begin{figure} %\centerline{\epsfig{file=figs/2_q2ll.eps,width=\linewidth}} %\caption{ %$\lambda$ and $\lambda'$ fit results for the structure function %$F_2(x,Q^2)$ as a function of $x$ %at $Q^2=5$~GeV$^2$ and $Q^2=90$~GeV$^2$. %\label{fig:2f2}} %\end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f22.eps,width=\linewidth}} \caption{ \label{fig:acotcent} The reduced cross-section measurements taken at different proton beam energies $E_p$ compared to the DGLAP fit in the ACOT scheme (shown by curves) for $2.0 \le Q^2\le 150$~GeV$^2$. The dashed line for $Q^2\le 2.5$~GeV$^2$ corresponds to the fit extrapolation. } \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f23.eps,width=0.9\linewidth}} \caption{ \label{fig:acotf2} The structure function $F_2$ as a function of $x$ calculated from the reduced cross section using $R=0.26$ for different $Q^2$ bins. The H1 data for different proton beam energies $E_p$ are compared to the DGLAP fit in the ACOT scheme with different values of the $Q^2_{min}$ cut. The dashed and dotted lines correspond to the extrapolation of the fits to lower $Q^2$ values. } \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f24.eps,width=0.9\linewidth}} \tablecaption{\label{fig:q2pdfs}Gluon and sea quark PDFs shown at the starting scale $Q^2_0=1.9$~GeV$^2$ for different values of $Q^2_{min}$.} \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f25.eps,width=0.9\linewidth}} \tablecaption{\label{fig:satpdfs}Gluon and sea quark PDFs shown at the starting scale $Q^2_0=1.9$~GeV$^2$ for the central fit with $Q^2_{min}=3.5$~GeV$^2$ and for the fits with additional cuts $Q^2>A_s x^{-0.3}$ where $A_{S}=0.2$ and $A_{s}=1.5$.} \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f26.eps,width=.9\linewidth}} \caption{ \label{fig:iimfit1} Reduced cross-section data taken at different proton beam energies $E_p$ compared to \iim\ fit results for $0.2 \le Q^2\le 5$~GeV$^2$. } \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f27.eps,width=.9\linewidth}} \caption{ \label{fig:iimfit2} Reduced cross-section data taken at different proton beam energies $E_p$ compared to \iim\ fit results for $6.5 \le Q^2\le 150$~GeV$^2$. } \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f28.eps,width=.9\linewidth}} \caption{ \label{fig:iimdglap} Reduced cross-section data taken at different proton beam energies $E_p$ compared to \iimdglap\ fit results for $3.5 \le Q^2\le 150$~GeV$^2$. The lower curves show the contribution of DGLAP$_{\rm valence}$ calculation. } \end{figure} \begin{figure} \centerline{\epsfig{file=d10-228f29.eps,width=\linewidth}} \caption{\label{fig:flave}The proton structure function $F_L$ shown as a function of $Q^2$. The average $x$ values for each $Q^2$ are indicated. The inner error bars represent statistical error, the full error bars include the statistical and systematic uncertainties added in quadrature. The lines represent results of the DGLAP ACOT and RT as well as dipole \iim\ and \bsat\ model fits. } \end{figure} %\begin{figure} %\epsfig{file=figs/r_vs_q2.eps,width=\linewidth} %\put(-50,-3){\large\bf $Q^{2}/GeV^{2}$} %\put(-153,75){\begin{sideways}\large\bf R\end{sideways}} %\caption{$R$ vs $Q^2$ } %\end{figure} \end{document}