Add to captions for chapters 1 to 6

chap1.tex

@@ -91,7 +91,7 @@ \section{The future}
 \begin{figure}%
   \centering
   \includegraphics[width=10cm]{images/introduction/mass_hierarchy.pdf}
-  \caption{The pattern of neutrino masses for the normal and inverted hierarchies.  The flavour composition of the mass eigenstates as a function of the unknown CP phase (labelled $\textrm{\delta}_{\textrm{CP}}$) is also shown~\cite{Qian20151}.}
+  \caption{The pattern of neutrino masses for the normal and inverted hierarchies with the atmospheric ($\Delta \textrm{m}^2_{\textrm{atm}}$) and solar ($\Delta \textrm{m}^2_{\textrm{sol}}$) mass splittings labelled.  The flavour composition of the mass eigenstates as a function of the unknown CP phase (labelled $\textrm{\delta}_{\textrm{CP}}$) is also shown~\cite{Qian20151}.}
   \label{fig:MassHierarchy}
 \end{figure}
 \newline

chap2.tex

@@ -88,7 +88,7 @@ \section{Neutrino interactions at the GeV-scale}
 \begin{figure}%
   \centering
   \includegraphics[width=12cm]{images/neutrino_interactions/CCQECrossSectionMiniBooNENOMAD.pdf}
-  \caption{The CCQE cross-sections measured by the MiniBooNE~(2010)~\cite{PhysRevD.81.092005}, LSND~(2002)~\cite{Auerbach:2002iy} and NOMAD~(2009)~\cite{Lyubushkin:2008pe} experiments.  The solid and dashed lines represent predictions from the NUANCE generator with different values of $M_A$~\cite{PhysRevD.81.092005}.}
+  \caption{The CCQE cross-sections measured by the MiniBooNE~(2010)~\cite{PhysRevD.81.092005}, LSND~(2002)~\cite{Auerbach:2002iy} and NOMAD~(2009)~\cite{Lyubushkin:2008pe} experiments.  The solid and dashed lines represent predictions from the NUANCE generator with different values of $M_A$~\cite{PhysRevD.81.092005}.  Each prediction does not well model all of the data shown in the figure, indicating tension between the data collected by each of the experiments.}
   \label{fig:CCQECrossSectionMiniBooNENOMAD}
 \end{figure}
 A popular explanation for this discrepancy is a lack of understanding of the nuclear environment.  Because the neutrino is not scattering of a free nucleon, but rather a nucleon in a strongly contained system, experiments actually measure an effective $M_A$.  It is possible that the nuclear effects cause a modification to the effective $M_A$ that the experiments measure.  This possible explanation for the discrepancy has placed a heavier emphasis on nuclear modelling in neutrino interaction experiments. 

chap3.tex

@@ -43,7 +43,7 @@ \subsection{Neutrino beamline}
 \begin{figure}
   \centering
   \includegraphics[width=15cm]{images/t2k/pot_history.png}
-  \caption{The POT recorded by CT5 as a function of time (blue line) and the recorded beam power in $\nu$ running mode (red dots) and $\bar{\nu}$ running mode (purple dots).}
+  \caption{The POT recorded by CT5 as a function of time (blue line) and the recorded beam power in $\nu$ running mode (red dots) and $\bar{\nu}$ running mode (purple dots).  The recorded POT as a function of time shows T2K has been successful in greatly increasing the size of its dataset during each data collection run.}
   \label{fig:POTHistory}
 \end{figure}
 \newline

chap5.tex

@@ -19,8 +19,8 @@ \subsection{Line-point duality}
 Now consider a new 2D space where the axes are defined by $m$ and $c$, rather than $x$ and $y$ (hereafter referred to as the parameter space).  As this parameter space is described by the parameters of a general 2D Cartesian line, there is an underlying symmetry between the two spaces.  The parameters of the 2D line shown in Fig.~\ref{fig:2DCartesianLine} can be used to form a pair of coordinates ($m$,$c$) in the parameter space as shown in Fig.~\ref{fig:2DParameterPoint}.  It is important here to state clearly the general result; a straight line in Cartesian space is represented by a single point in parameter space. 
 \begin{figure}%
   \centering
-  \subfloat[Line in 2D Cartesian space.]{\includegraphics[width=7cm]{images/hough_transform/cartesian_line} \label{fig:2DCartesianLine}}
-  \subfloat[Point in 2D parameter space.]{\includegraphics[width=7cm]{images/hough_transform/parameter_point} \label{fig:2DParameterPoint}}
+  \subfloat[Line in 2D Cartesian space.  The line is defined by its intercept with the $y$-axis, $c$, and its gradient, $\Delta y/\Delta x = m$ (not shown).]{\includegraphics[width=7cm]{images/hough_transform/cartesian_line} \label{fig:2DCartesianLine}}
+  \subfloat[Point representation of the line defined in Fig.~\ref{fig:2DCartesianLine} in 2D parameter space.  Because the line is solely defined by its intercept, $c$, and its gradient, $m$, the line is defined as a point in this parameter space.]{\includegraphics[width=7cm]{images/hough_transform/parameter_point} \label{fig:2DParameterPoint}}
   \caption{Representations of a 2D line in Cartesian space.}
   \label{fig:2DCartesianLineAndParameterPoint}
 \end{figure}
@@ -39,8 +39,8 @@ \subsection{Line-point duality}
 and the intercept of the line with the $c$ axis is $y$ as shown in Fig.~\ref{fig:2DParameterLine}.  As before, it is important to clearly state what has been shown; a point in Cartesian space is represented by a line in parameter space.
 \begin{figure}%
   \centering
-  \subfloat[Point in 2D Cartesian space.]{\includegraphics[width=7cm]{images/hough_transform/cartesian_point} \label{fig:2DCartesianPoint}}
-  \subfloat[Line in 2D parameter space.]{\includegraphics[width=7cm]{images/hough_transform/parameter_line} \label{fig:2DParameterLine}}
+  \subfloat[Point in 2D Cartesian space.  The point can be defined as an infinite set of lines, all of which cross at said point (three example lines are shown).]{\includegraphics[width=7cm]{images/hough_transform/cartesian_point} \label{fig:2DCartesianPoint}}
+  \subfloat[Line representation of the point defined in Fig.~\ref{fig:2DCartesianPoint} in 2D parameter space.  The infinite set of lines which represent the point in Fig.~\ref{fig:2DCartesianPoint} follow a relation, $c=-xm+y$, which itself is a line in the parameter space.]{\includegraphics[width=7cm]{images/hough_transform/parameter_line} \label{fig:2DParameterLine}}
   \caption{Representations of a 2D point in Cartesian space.}
   \label{fig:2DCartesianPointAndParameterLine}
 \end{figure}
@@ -62,7 +62,7 @@ \subsection{The parameter space}
 \end{equation}
 \begin{figure}%
   \centering
-  \subfloat[The three Cartesian points defined in equation~\ref{eq:HTExampleCartesianPoints}.]{\includegraphics[width=7cm]{images/hough_transform/HT_example_cartesian_space} \label{fig:HTExampleCartesianSpace}}
+  \subfloat[The three Cartesian points defined in equation~\ref{eq:HTExampleCartesianPoints} along with example lines from each point's infinite line set.  The coordinates of each point are also shown.]{\includegraphics[width=7cm]{images/hough_transform/HT_example_cartesian_space} \label{fig:HTExampleCartesianSpace}}
   \subfloat[The three parameter lines defined in equation~\ref{eq:HTExampleParameterLines}.  The coordinates (2,4) define the point of intersection of the three lines.]{\includegraphics[width=7cm]{images/hough_transform/HT_example_parameter_space} \label{fig:HTExampleParameterSpace}}
   \caption{The three points defined in equation~\ref{eq:HTExampleCartesianPoints} and their representation in the parameter space.  The colour coding matches the Cartesian points to their respective parameter lines.}
   \label{fig:HTExample}
@@ -88,7 +88,7 @@ \subsection{The parameter space}
 \begin{figure}
   \centering
   \includegraphics[width=9cm]{images/hough_transform/HT_example_cartesian_space_with_line}
-  \caption{The line represented by the intersection in Fig.~\ref{fig:HTExampleParameterSpace} with the Cartesian points it intercepts.}
+  \caption{The line represented by the parameter space intersection in Fig.~\ref{fig:HTExampleParameterSpace} with the Cartesian points it intercepts.}
   \label{fig:HTExampleCartesianSpaceWithLine}
 \end{figure}
 
@@ -185,7 +185,7 @@ \subsection{Parameter space generation}
 \begin{figure}
   \centering
   \includegraphics[width=10cm]{images/ecal_hough_transform/FullParameterSpace_3StateInteraction.eps}
-  \caption{The full parameter space of the 2D cluster shown in Fig.~\ref{fig:3StateInteractionNoReconstruction}.}
+  \caption{The full parameter space of the 2D cluster shown in Fig.~\ref{fig:3StateInteractionNoReconstruction}.  The height of each point in the parameter space corresponds to the number of hit scintillator bars intersected by the Cartesian line which the parameter space point represents.}
   \label{fig:FullParameterSpace3StateInteraction}
 \end{figure}
 
@@ -205,7 +205,7 @@ \subsection{Parameter space analysis}
 \begin{figure}
   \centering
   \includegraphics[width=10cm]{images/ecal_hough_transform/ReducedParameterSpace_3StateInteraction.eps}
-  \caption{The reduced parameter space of the 2D cluster shown in Fig.~\ref{fig:3StateInteractionNoReconstruction}.}
+  \caption{The reduced parameter space of the 2D cluster shown in Fig.~\ref{fig:3StateInteractionNoReconstruction}.  The reduced parameter space was formed by removing all of the hit scintillator bar representations which contributed to the full parameter space's (see Fig.~\ref{fig:FullParameterSpace3StateInteraction}) maximum.}
   \label{fig:ReducedParameterSpace3StateInteraction}
 \end{figure}
 
@@ -278,7 +278,7 @@ \subsection{Track splitting}
 \begin{figure}
   \centering
   \includegraphics[width=7cm]{images/hough_3d_matching/MergedTrackEventDisplay.pdf}
-  \caption{Event display of a problematic (for the reconstruction) neutrino interaction in the ECal.  The solid green track is the muon, the solid blue tracks are protons and the pink tracks are neutrons.  The neutrino is the short dashed green line.}
+  \caption{Event display (XY view) of a problematic (for the reconstruction) neutrino interaction in the ECal.  The solid green track is the muon, the solid blue tracks are protons and the pink tracks are neutrons.  The neutrino is the short dashed green line.  The proton travelling vertically downwards and the muon are created almost back to back leaving a line of hit scintillator bars.  The 2D hough transform would register this as a single straight line.}
   \label{fig:MergedTrackEventDisplay}
 \end{figure}
 \newline
@@ -346,7 +346,7 @@ \subsection{Validation of algorithm performance}
 \begin{figure}
   \centering
   \includegraphics[width=9cm]{images/hough_validation/MuonAngularResolutionDSECal}
-  \caption{The angular resolution as a function of trajectory length in the DS ECal when applying the enhanced reconstruction to muon MC.  The colour coding refers to the true entry angle range of the muons.}
+  \caption{The angular resolution as a function of trajectory length in the DS ECal when applying the enhanced reconstruction to muon MC.  The colour coding refers to the true entry angle range of the muons.  The figure was generated using single muon particle gun fired into the front face of the DS ECal with a controlled range of entry angles.  The angular resolution distributions were created by L. Pickering.}
   \label{fig:MuonAngularResolutionDSECal}
 \end{figure}
 \newline
@@ -359,7 +359,7 @@ \subsection{Validation of algorithm performance}
    $2^{\textrm{nd}}$ track matched&  & 89$\%$ & 79$\%$ \\
    $3^{\textrm{rd}}$ track matched&  &  & 70$\%$ \\
   \end{tabular}
-  \caption{The percentage number of correct matches in the 3D matching separated by which track matching likelihood was used.}
+  \caption{The percentage number of correct matches in the 3D matching separated by which track matching likelihood was used.  NEUT-based Monte Carlo simulation of the T2K beam was used to calculate the matching percentages.}
   \label{table:PercentageCorrect3DMatching}
 \end{table}
 
@@ -376,8 +376,8 @@ \subsection{Data-motivated validation of the algorithms}
 Fig.~\ref{fig:TotalChargeDataValidation} shows the summed charge contained in all tracks reconstructed in each ECal cluster.  To clarify what this means, if a reconstructed ECal cluster contained three reconstructed tracks where tracks 1, 2 and 3 contain 20~MEU, 50~MEU and 30~MEU of charge respectively, that event would be registered as having 100~MEU of charge in the relevant distribution in Fig.~\ref{fig:TotalChargeDataValidation}.  Both the barrel ECal and DS ECal samples show a large discrepancy around the charge peak.  This offset can be explained as a hit-level charge discrepancy between data and Monte Carlo and is not caused by the reconstruction.  This discrepancy should, however, be considered during analysis of the systematic uncertainties.  Unfortunately, the DS ECal events in the bskmu sample (Fig.~\ref{fig:TotalChargebskmuDS}) shows an extra data excess in the 20~MEU to 30~MEU region which is just before the charge peak.  This data excess can not be explained by a relative hit inefficiency. 
 \begin{figure}%
   \centering
-  \subfloat[Barrel ECal events in the fgdcol sample.]{\includegraphics[width=8cm]{images/hough_validation/TotalCharge_fgdcol_Barrel.eps} \label{fig:TotalChargefgdcolBarrel}}
-  \subfloat[DS ECal events in the bskmu sample.]{\includegraphics[width=8cm]{images/hough_validation/TotalCharge_bskmu_DSECal.eps} \label{fig:TotalChargebskmuDS}}
+  \subfloat[Barrel ECal events in the fgdcol sample.  The data peak is offset to the Monte Carlo peak, indicating an unmodelled dead channel issue.]{\includegraphics[width=8cm]{images/hough_validation/TotalCharge_fgdcol_Barrel.eps} \label{fig:TotalChargefgdcolBarrel}}
+  \subfloat[DS ECal events in the bskmu sample.  The data peak is offset to the Monte Carlo peak, indicating an unmodelled dead channel issue.  There is also a significant data excess before the peak of the distributions.]{\includegraphics[width=8cm]{images/hough_validation/TotalCharge_bskmu_DSECal.eps} \label{fig:TotalChargebskmuDS}}
   \caption{The summed charge contained on all tracks reconstructed in each ECal cluster.  The red histograms and black points are Monte Carlo and data respectively.}
   \label{fig:TotalChargeDataValidation}
 \end{figure}
@@ -386,8 +386,8 @@ \subsection{Data-motivated validation of the algorithms}
 Fig.~\ref{fig:TotalHitsDataValidation} shows the summed number of hits contained in all tracks reconstructed in each ECal cluster.  Generally speaking, the distributions in Fig.~\ref{fig:TotalHitsDataValidation} share similar features to those in Fig.~\ref{fig:TotalChargeDataValidation}.  Importantly, an excess of data events appears just before the peak in Fig.~\ref{fig:TotalHitsDataValidation}.  The fact that this excess also appears in Fig.~\ref{fig:TotalHitsDataValidation} strongly suggests that the issue is caused by the number of hits associated to the reconstructed tracks, rather than the deposited charge.  Further investigation of this discrepancy revealed that a mismodelled hit inefficiency, most likely due to dead DS ECal channels, was the issue.  One of the 2D track quality checks (see section~\ref{subsec:2DTrackQualityChecks}) requires that a 2D track candidate can not skip a layer in a given view which is problematic when considering dead channels.  
 \begin{figure}%
   \centering
-  \subfloat[Barrel ECal events in the fgdcol sample.]{\includegraphics[width=8cm]{images/hough_validation/TotalHits_fgdcol_Barrel.eps} \label{fig:TotalHitsfgdcolBarrel}}
-  \subfloat[DS ECal events in the bskmu sample.]{\includegraphics[width=8cm]{images/hough_validation/TotalHits_bskmu_DSECal.eps} \label{fig:TotalHitsbskmuDS}}
+  \subfloat[Barrel ECal events in the fgdcol sample.  The only significant discrepancy is the offset of the data peak relative to the Monte Carlo peak, suggesting an unmodelled dead channel issue.]{\includegraphics[width=8cm]{images/hough_validation/TotalHits_fgdcol_Barrel.eps} \label{fig:TotalHitsfgdcolBarrel}}
+  \subfloat[DS ECal events in the bskmu sample.  There is a significant data excess before the peak in the distributions.]{\includegraphics[width=8cm]{images/hough_validation/TotalHits_bskmu_DSECal.eps} \label{fig:TotalHitsbskmuDS}}
   \caption{The summed number of hits contained on all tracks reconstructed in each ECal cluster.  The red histograms and black points are Monte Carlo and data respectively.}
   \label{fig:TotalHitsDataValidation}
 \end{figure}
@@ -397,7 +397,7 @@ \subsection{Data-motivated validation of the algorithms}
 \begin{figure}[b!]%
   \centering
   \subfloat[Summed charge contained on all tracks in each reconstructed ECal cluster.]{\includegraphics[width=8cm]{images/hough_validation/TotalCharge_bskmuCorrected_DSECal.eps} \label{fig:TotalChargebskmuCorrectedDS}}
-  \subfloat[Summed number of hits contained on all tracks in each reconstructed ECal cluster..]{\includegraphics[width=8cm]{images/hough_validation/TotalHits_bskmuCorrected_DSECal.eps} \label{fig:TotalHitsbskmuCorrectedDS}}
-  \caption{The number of DS ECal events in the bskmu sample after relaxing the 2D track quality check.  The red histograms and black points are the Monte Carlo and data respectively.}
+  \subfloat[Summed number of hits contained on all tracks in each reconstructed ECal cluster.]{\includegraphics[width=8cm]{images/hough_validation/TotalHits_bskmuCorrected_DSECal.eps} \label{fig:TotalHitsbskmuCorrectedDS}}
+  \caption{The number of DS ECal events in the bskmu sample after relaxing the 2D track quality check.  The red histograms and black points are the Monte Carlo and data respectively.  The track quality fix has corrected the data excesses in both distributions, leaving only the offset between the data and Monte Carlo peaks.}
   \label{fig:bskmuCorrectedDSDataValidation}
 \end{figure}