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@@ -287,13 +287,16 @@ of momentum scaling factor is plotted on \cref{fig:al100_scan_rate}. The trend
showed that muons penetrated deeper as the momentum increased, reaching the showed that muons penetrated deeper as the momentum increased, reaching the
optimal value at the scale of 1.08, then decreased as punch through happened optimal value at the scale of 1.08, then decreased as punch through happened
more often from 1.09. The distributions of stopped muons are illustrated by more often from 1.09. The distributions of stopped muons are illustrated by
MC results on \cref{fig:al100_mu_stop_mc}. With the 1.09 scale beam, the muons MC results on the right hand side of \cref{fig:al100_scan_rate}. With the 1.09
stopped \SI{28}{\um} off-centre to the right silicon arm. scale beam, the muons stopped \SI{28}{\um} off-centre to the right silicon arm.
\begin{figure}[htb] \begin{figure}[htb]
\centering \centering
\includegraphics[width=0.85\textwidth]{figs/al100_scan_rate} \includegraphics[width=0.47\textwidth]{figs/al100_scan_rate}
\includegraphics[width=0.47\textwidth]{figs/al100_mu_stop_mc}
\caption{Number of X-rays per incoming muon as a function of momentum \caption{Number of X-rays per incoming muon as a function of momentum
scaling factor.} scaling factor (left); and muon stopping distributions from MC simulation
(right). The depth of muons is measured normal to surface of the target
facing the muon beam.}
\label{fig:al100_scan_rate} \label{fig:al100_scan_rate}
\end{figure} \end{figure}
@@ -365,13 +368,14 @@ of protons is normalised to the number of nuclear muon captures.
From the particle identification above, number of protons having energy in the From the particle identification above, number of protons having energy in the
range from \SIrange{2.2}{8.5}{\MeV} hitting the two arms are: range from \SIrange{2.2}{8.5}{\MeV} hitting the two arms are:
\begin{align} \begin{align}
N_{\textrm{p meas. left}} = 1789 \pm 42.3\\ N_{\textrm{p meas. left}} = 1822 \pm 42.7\\
N_{\textrm{p meas. right}} = 2285 \pm 47.8 N_{\textrm{p meas. right}} = 2373 \pm 48.7
\end{align} \end{align}
The right arm received significantly more protons than the left arm did, which The right arm received significantly more protons than the left arm did, which
is expected because in \cref{sub:momentum_scan_for_the_100_} it is shown that is expected as in \cref{sub:momentum_scan_for_the_100_} it is shown that
muons stopped off centre to the right arm. muons stopped off centre to the right arm.
%%TODO
The uncertainties are statistical only. The systematic uncertainties due to The uncertainties are statistical only. The systematic uncertainties due to
the cut on protons is estimated to be small compared to the statistical ones. the cut on protons is estimated to be small compared to the statistical ones.
@@ -379,742 +383,34 @@ the cut on protons is estimated to be small compared to the statistical ones.
\label{sub:corrections_for_the_number_of_protons} \label{sub:corrections_for_the_number_of_protons}
The protons spectra observed by the silicon detectors have been modified by The protons spectra observed by the silicon detectors have been modified by
the energy loss inside the target so correction (or unfolding) is necessary. the energy loss inside the target so correction (or unfolding) is necessary.
In the unfolding process, a response function that relates proton's true energy The unfolding, essentially, is finding a response function that relates proton's
and the measured one is needed. true energy and measured value. This can be done in MC simulation by generating
protons with a spatial distribution as close as possible to the real
distribution of muons inside the target, then counting the number of protons
reaching the silicon detectors. Such response function conveniently includes
the geometrical acceptance.
The response function is For the 100-\si{\um} aluminium target and muons at the momentum scale of 1.09,
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% the parameters of the initial protons are:
%\section{Charged particles following muon capture on a thick silicon target}
%\label{sec:charged_particles_from_muon_capture_on_silicon_thick_silicon}
%Firstly, the number of charged particles emitted after nuclear muon capture on
%the active target is calculated. The charged particles yield then is normalised
%to the number of nuclear muon capture to obtain an emission rate.
%Finally, the
%rate is compared with that from the literature.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%\subsection{Number of charged particles with energy above \SI{3}{\MeV}}
%\label{sub:number_of_charged_particles_with_energy_from_8_10_mev}
%As shown in \cref{fig:sir2_1us_slices} and illustrated by MC simulation
%in \cref{fig:sir2_mc_pdfs}, there are several components in
%the energy spectrum recorded by the active target:
%\begin{enumerate}
%\item charged particles from nuclear muon capture, this is the signal of
%interest;
%\item beam electrons with a characteristic Landau peak around \SI{800}{\keV},
%dominating at large delay (from \SI{6500}{\ns}), causing background at
%energy lower than \SI{1}{\MeV} which drops sharply at energy larger than
%\SI{3}{\MeV};
%\item electrons from muon decay-in-orbit (DIO) and recoiled nuclei
%from neutron emitting muon captures, peak at
%around \SI{300}{\keV}, dominate the region where energy smaller than
%\SI{1}{\MeV} and delay less than \SI{3500}{\ns}. This component is
%intrinsic background, having the same time structure as that of the signal;
%\item stray muons scattered into the target, this component is small compares
%to the charged particles yield so it is not considered further.
%\end{enumerate}
%\begin{figure}[htb]
%\centering
%\includegraphics[width=0.45\textwidth]{figs/sir2_meas_spec}
%\includegraphics[width=0.45\textwidth]{figs/sir2_mc_pdfs}
%\caption{The observed spectrum in the timing window 1300 -- 10000~ns (left)
%and its components from MC simulation (right). The charged particles
%spectrum is obtained assuming the spectrum shape and emission rate from
%Sobottka and Wills~\cite{SobottkaWills.1968}. The relative scales between
%components are arbitrarily chosen for the purpose of illustration.}
%\label{fig:sir2_mc_pdfs}
%\end{figure}
%An energy cut at \SI{2}{\MeV} is introduced to avoid the domination of the
%beam electrons at low energy. In order to obtain the yields of backgrounds
%above \SI{2}{\MeV}, a binned maximum likelihood fit was done. The likelihood of
%getting the measured spectrum is defined as:
%\begin{equation}
%L = \frac{e^{-\mu}\mu^n}{n!}\prod_i \frac{\mu_i^{n_i} e^{-\mu_i}}{n_i!}
%\label{eqn:llh_def}
%\end{equation}
%where $n$ is the total number of events observed, $\mu$ is the expected number
%of events according to some linear combination of the signal and the
%backgrounds shown in~\ref{fig:sir2_mc_pdfs}, namely:
%\begin{align}
%n &= n_{\textrm{sig}} + n_{\textrm{beam e}} + n_{\textrm{dio}}\\
%\textrm{(sum pdf)} &= n_{\textrm{sig}}\times\textrm{(sig pdf)} +
%n_{\textrm{beam e}}\times\textrm{(beam e pdf)} +
%n_{\textrm{dio}}\times\textrm{(dio pdf)};
%\label{eqn:sum_pdf}
%\end{align}
%and the $i$ index indicates the respective number of events in the $i$-th
%bin.
%The fit is done by the RooFit package~\cite{VerkerkeKirkby.2003} where the
%negative log likelihood $-2\ln{L}$ is minimised. Fitting results are shown
%in~\ref{fig:sir2_mll_fit}, the yields of backgrounds and signal are:
%\begin{align}
%n_{\textrm{beam e}} &= 23756 \pm 581\\
%n_{\textrm{dio}} &= 111340 \pm 1245\\
%n_{\textrm{sig}} &= 2.57 \pm 856
%\label{eqn:sir2_n_chargedparticles}
%\end{align}
%\begin{figure}[htb]
%\centering
%\includegraphics[width=0.42\textwidth]{figs/sir2_mllfit_nbkg}
%\includegraphics[width=0.42\textwidth]{figs/sir2_mllfit_nebeam}
%\includegraphics[width=0.84\textwidth]{figs/sir2_mllfit}
%\caption{Results of the maximum likelihood fit of the energy spectrum on the
%active target.}
%\label{fig:sir2_mll_fit}
%\end{figure}
% subsection number_of_charged_particles_with_energy_from_8_10_mev (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%\subsection{Number of nuclear muon captures}
%\label{sub:number_of_stopped_muons}
%The area of the $(2p-1s)$ peak is $N_{(2p-1s)} = 2981.5 \pm 65.6$,
%obtained by subtracting the background of 101.5 from the spectral integral of
%2083 in the region from 396 to 402 keV.
%The area of the $(2p-1s)$ peak is $2929.7 \pm 56.4$ obtained by fitting
%a Gaussian peak on top of a first-order polynomial background to the spectrum
%in \cref{fgi:sir2_xray} in the region from \SIrange{395}{405}{\keV}.
%The X-ray intensity in \cref{tab:mucap_pars} was normalised to the number of
%stopped muons, so the number of stopped muons is:
%\begin{align}
%N_{\mu\textrm{ stopped}} &=
%\dfrac{N_{(2p-1s)}}{\epsilon_{2p-1s}\times I_{(2p-1s)}}\nonumber\\
%&= \dfrac{370}{4.38\times10^{-4} \times 0.803} \\
%&= 1.05\times10^6 \nonumber
%\end{align}
%where $\epsilon_{(2p-1s)}$ is the calibrated absolute efficiency of the
%detector for the 400.177~keV line in \cref{tab:xray_eff}, and
%$I_{(2p-1s)}$ is the probability of emitting this X-ray per stopped muon
%(80.3\% from \cref{tab:mucap_pars}).
%Taking the statistical uncertainty of the peak area, and systematic
%uncertainties from parameters of muon capture, the number of stopped muons
%calculated from the X-ray measurement is
%$(10.50 \pm 0.65)\times 10^5$. This figure is consistent with the number of
%stopped muons of $9.82\times10^5$ after the cuts described in the event
%selection process.
%The number of nuclear captured muons is:
%\begin{equation}
%N_{\mu\textrm{ nucl.capture}} =
%N_{\mu\textrm{ stopped}}\times f_{\textrm{cap.Si}}
%= 10.05 \times 10^5 \times 0.658 = 6.91 \times 10^5
%\label{eqn:sir2_Ncapture}
%\end{equation}
%where the $f_{\textrm{cap.Si}}$ is the probability of nuclear capture per
%stopped muon from \cref{tab:mucap_pars}.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%\subsection{Emission rate of charged particles}
%\label{sub:emission_rate_of_charged_particles}
%The emission rate of charged particles is calculated by taking the ratio of
%number of charged particles in ~\eqref{eqn:sir2_Nchargedparticle} and number of
%nuclear muon capture in~\eqref{eqn:sir2_Ncapture}:
%\begin{equation}
%R_{\textrm{Si}} = \frac{N_{\textrm{charged particle}}}{N_{\mu\textrm{ nucl.capture}}}
%= \frac{149.9\times10^4}{7.25\times10^6} = 0.252
%\end{equation}
%Uncertainties of this rate calculation are listed in
%\cref{tab:sir2_uncertainties}, including:
%\begin{itemize}
%\item uncertainties from number of charged particles, both statistical and
%systematic (from spectrum shape and fitting) ones are absorbed in the
%quoted value in~\eqref{sir2_Nchargedparticle};
%\item uncertainties from number of nuclear capture:
%\begin{itemize}
%\item statistical error of the peak area calculation,
%\item systematic errors from the efficiency calibration, and referenced
%values of X-ray intensity and capture probability.
%\end{itemize}
%\end{itemize}
%So, the emission rate is:
%\begin{equation}
%R_{\textrm{Si}} = 0.252 \pm 0.009
%\label{eqn:sir2_rate_cal}
%\end{equation}
%\begin{table}[htb]
%\begin{center}
%\begin{tabular}{l l l}
%\toprule
%Number of charged particles & &\\
%Statistical and systematic & &0.004\\
%\midrule
%Number of nuclear capture & &\\
%Statistical & Peak area calculation& 0.022\\
%Systematic & Efficiency calibration & 0.024\\
%& X-ray intensity & 0.009\\
%& Capture probability & 0\\
%\midrule
%Total relative error & & 0.035\\
%Total absolute error & & 0.009\\
%\bottomrule
%\end{tabular}
%\end{center}
%\caption{Uncertainties of the emission rate from the thick silicon target}
%\label{tab:sir2_uncertainties}
%\end{table}
% subsection partial_emission_rate_of_charged_particle_in_8_10_mev_range (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%TODO
%\subsection{Partial emission rate of charged particles from the literature}
%\label{sub:partial_emission_rate_of_charged_particles_from_the_literature}
%\begin{figure}[htb]
%\centering
%\includegraphics[width=0.85\textwidth]{figs/sobottka_spec2}
%\caption{Reproduced charged particle spectrum from muon capture on silicon,
%measured by Sobottka and Wills. Integration region is shown in the green
%box.}
%\label{fig:sobottka_spec}
%\end{figure}
%The spectrum measured by Sobottka and Wills~\cite{SobottkaWills.1968} is
%reproduced in \cref{fig:sobottka_spec}, the spectral integral in the
%energy region from 8 to 10~\si{\MeV}\ is $2086.8 \pm 45.7$.
%The authors obtained the spectrum in a 4~\si{\us}\ gate period which began
%1~\si{\us}\ after a muon stopped, which would take 26.59\% of the emitted
%particles into account. The number of stopped muons was not explicitly stated,
%but can be inferred to be $55715/0.06 = 92858.3$.
%The partial rate of charged particle from 8 to 10~\si{\MeV}\ is then
%calculated to be:
%\begin{equation}
%R_{\textrm{8-10 MeV}}^{lit.} =
%\dfrac{2086.8}{0.2659 \times 92858.3 \times 0.658}
%= 1.28 \times 10^{-2}
%\end{equation}
%The authors did not mentioned how the uncertainties of their measurement was
%derived, but quoted the emission rate below 26~\si{\MeV}\ to be $0.15
%\pm 0.02$, which translates to a relative uncertainty of 0.133. The statistical
%uncertainty from the spectral integral and the number of stopped muons is:
%\begin{equation*}
%\dfrac{1}{\sqrt{25000}} + \dfrac{1}{\sqrt{92858.3}} = 0.9 \times 10^{-2}
%\end{equation*}
%Then their systematic uncertainty would be: $0.133 - 0.009 = 0.124$.
%For the partial spectrum from 8 to 10~\si{\MeV}, the statistical
%contribution to the uncertainty is:
%\begin{equation*}
%\dfrac{1}{\sqrt{2086.8}} + \dfrac{1}{\sqrt{92858.3}} = 2.5 \times 10^{-2}
%\end{equation*}
%So, the combined uncertainty of this partial rate calculation is: $0.124
%+ 0.025 = 0.150$. The partial rate of charged particles from 8 to
%10~\si{\MeV} per muon capture is:
%\begin{equation}
%R_{\textrm{8-10 MeV}}^{lit.} = (1.28 \pm 0.19) \times 10^{-2}
%\end{equation}
% subsection partial_emission_rate_of_charged_particles_from_the_literature
% (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Charged particles following muon capture on a thin silicon target}
\label{sec:charged_particles_following_muon_capture_on_a_thin_silicon_target}
In this measurement, a passive, 62-\si{\um}-thick silicon target was used as the
target. The silicon target is $5\times5$~\si{\centi\meter}$^2$ in area. The muon
momentum was chosen to be 1.06 after a scanning to maximise the stopping ratio.
The charged particles were measured by two arms of silicon detectors. The
plastic scintillators vetoing information were not used.
This data set consists of 66 runs, from 3474--3489 and 3491--3540.
Although there are a few issues found in the process of data quality
checking such as one very noisy timing channel, and several runs had
abnormally high rates, the whole data set is determined to be good. Without
an active target and veto, the muon signal is from the muon counter only. The
tree contains total $1.452 \times 10^8$ muon events. %145212698
\begin{figure}[htb]
\centering
\includegraphics[width=0.49\textwidth]{figs/si16_lldq_noise}
\includegraphics[width=0.49\textwidth]{figs/si16_lldq_islandrate}
\caption{Oddities found in checking data quality: noise level on timing
output of the SiL1-2 was much higher than the other detectors, and some
runs show large pulse rate.}
\label{fig:si16_lldq}
\end{figure}
\subsection{Particle identification by dE/dx and proton selection}
\label{sub:particle_identification_by_de_dx}
%All silicon hits with energy deposition larger than
%200~\si{\keV}\ that happened within $\pm 10$~\si{\us}\ of the
%muon hit are then
%associated to the muon and stored in the muon event tree. The
%200~\si{\keV}\ cut effectively rejects all MIPs hits on thin silicon
%detectors of which the most probable value is about 40~\si{\keV}.
%In order to use dE/dx for particle identification, $\Delta$E and total E are
%needed.
The charged particle selection starts from searching for muon event
that has at least one hit on thick silicon. If there is a thin silicon hit
within a coincidence window of $\pm 0.5$~\si{\us}\ around the thick
silicon hit, the two hits are considered to belong to one particle with
$\Delta$E being the energy of the thin hit, and total E being the sum energy of
the two hits. Particle identification is done using correlation between
$\Delta$E and E. \cref{fig:si16p_dedx_nocut} shows clearly visible banding
structure. No cut on energy deposit or timing with respect to muon hit are
applied yet.
With the aid from MC study (\cref{fig:pid_sim}), the banding on the
$\Delta$E-E plots can be identified as follows:
\begin{itemize} \begin{itemize}
\item the densest spot at the lower left conner belonged to electron hits; \item horizontal distribution: Gaussian \SI{26}{\mm} FWHM, centred at the
\item the small blurry cloud just above the electron region was muon hits; centre of the target;
\item the most intense band was due to proton hits; \item vertical distribution: Gaussian \SI{15}{\mm} FWHM, centred at the
\item the less intense, upper band caused by deuteron hits; centre of the target;
\item the highest band corresponded to alpha hits; \item depth: Gaussian \SI{69.2}{\um} FWHM, centred at \SI{68.8}{\um}-deep from
\item the faint stripe above the deuteron band should be triton the upstream face of the target;
hits, which is consistent with a relatively low probability of emission of \item energy: flatly distributed from \SIrange{1.5}{15}{\MeV}.
tritons.
\end{itemize} \end{itemize}
The resulting response matrices for the two arms are presented in
%The electrons either from Michel decay or from the beam are MIPs particles, \cref{fig:al100_resp_matrices}. These are then used as MC truth to train and
%which would deposit about 466~keV on the 1500-\si{\um}-thick silicon detector, test the unfolding code. The code uses an existing ROOT package
%and about 20~keV on the 65-\si{\um}-thick silicon detector. Therefore our thin called RooUnfold~\cite{Adye.2011} where the iterative Bayesian unfolding
%silicon counters could not distinguish electrons from electronic method is implemented.
%noise. The brightest spots on the $\Delta$E-E plots are identified as electrons
%due to
%the total E of about 500~keV, and is the accidental coincidence between
%electron hits on the thick silicon and electronics noise on the thin silicon.
\begin{figure}[htb] \begin{figure}[htb]
\centering \centering
\includegraphics[width=0.95\textwidth]{figs/si16p_dedx_nocut} \includegraphics[width=0.85\textwidth]{./figs/al100_resp}
\caption{$\Delta$E as a function of E of particles from muon capture on the \caption{Response functions for the two silicon arms.}
thin silicon target.} \label{fig:al100_resp_matrices}
\label{fig:si16p_dedx_nocut}
\end{figure} \end{figure}
After training the unfolding code is applied on the measured spectra from the
It is observed that the banding is more clearly visible in a log-log scale left and right arms. The unfolded proton spectra
plots like in \cref{fig:si16p_dedx_cut_explain}, this suggests
a geometrical cut on the logarithmic scale would be able to discriminate
protons from other particles. The protons and deuterons bands are nearly
parallel to the $\ln(\Delta \textrm{E [keV]}) + \ln(\textrm{E [keV]})$ line,
but have a slightly altered slope because $\ln(\textrm{E})$ is always greater
than $\ln(\Delta\textrm{E})$. The two parallel lines on
\cref{fig:si16p_dedx_cut_explain} suggest a check of
$\ln(\textrm{E}) + 0.85\times\ln(\Delta \textrm{E})$ could tell
protons from other particles.
Another feature of the $\Delta$E-E plots is their resolution power for protons
decrease as the energy E increases. The reason for this is the limited energy
resolution of the silicon detectors in use. The plots in logarithmic scale
show that this particle identification is good in the region where
$\ln(\textrm{E}) < 9$, which corresponds to $\textrm{E} < 8$~MeV.
\begin{figure}[htb]
\centering
\includegraphics[width=0.95\textwidth]{figs/si16p_dedx_cut}
\caption{$\Delta$E-E plots in the logarithmic scale and the geometrical cuts
for protons.}
\label{fig:si16p_dedx_nocut_log}
\end{figure}
The cut of $\ln(\textrm{E}) < 9$ is applied first, then
$\ln(\textrm{E})+ 0.85\times\ln(\Delta \textrm{E}) $ is plotted as
\cref{fig:si16p_loge+logde}. The protons make a clear peak in the region
between 14 and 14.8, the next peak at 15 corresponds to deuteron.
Imposing the
$14<\ln(\textrm{E})+ 0.85\times\ln(\Delta \textrm{E})<14.8$ cut,
the remaining proton band is shown on \cref{fig:si16p_proton_after_ecut}.
\begin{figure}[htb]
\centering
\includegraphics[width=0.85\textwidth]{figs/si16p_dedx_loge+logde}
\caption{Rationale for the cut on $\ln(\textrm{E})$ and $\ln(\Delta
\textrm{E})$}
\label{fig:si16p_loge+logde}
\end{figure}
\begin{figure}[htb]
\centering
\includegraphics[width=0.85\textwidth]{figs/si16p_proton_after_ecut}
\caption{Proton bands after cuts on energy}
\label{fig:si16p_proton_after_ecut}
\end{figure}
% subsection particle_identification_by_de_dx (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Number of muon captures}
\label{sub:number_stopped_muons}
The X-ray spectrum from this silicon target on \cref{fig:si16_xray} is
significantly noisier than the previous data set of SiR2, suffers from both
lower statistics and a more relaxed muon definition. The peak of $(2p-1s)$
X-ray at 400.177~keV can still be recognised but on a very high background. The
same timing requirement for the hit timing on the germanium detector as
in~\eqref{eqn:sir2_ge_cut}.
The double peaks of muonic X-rays from the lead shield at 431 and 438~keV are
very intense, reflects the fact that the low momentum muon beam of
29.68~MeV\cc\ (scaling factor 1.06) was strongly scattered by the upstream
counters. After a prompt cut that requires the photon
hit occured in $\pm 1$~\si{\us}\ around the muon hit, the peaks from lead
remain prominent which is an expected result because of all the lead shield
inside the chamber was to capture stray muons. The cut shows its effect on
reducing the background level under the 400.177 keV peak by about one third.
\begin{figure}[htb]
\centering
\includegraphics[width=0.98\textwidth]{figs/si16p_xray}
\caption{X-ray spectrum from the passive 62-\si{\um}-thick silicon target with
and with out timing cut.}
\label{fig:si16_xray}
\end{figure}
Using the same procedure on the region from 396 to 402 keV (without
self-absorption correction since this is a thin target), the number of
X-rays recorded and the number of captures are shown in
\cref{tab:si16p_ncapture_cal}.
\begin{table}[htb]
\begin{center}
\begin{tabular}{l l c c c}
\toprule
\textbf{Source}& \textbf{Quantity}& \textbf{Value} & \textbf{Absolute}
& \textbf{Relative}\\
& & & \textbf{error} & \textbf{error}\\
\midrule
Measured & $(2p-1s)$ peak area & 2613 & 145.5 & 0.056\\
\midrule
Calibration & X-ray efficiency & \sn{4.54}{-4} & \sn{1.11}{-5}
& 0.024\\
\midrule
Reference & X-ray intensity & 0.803 & 0.008 & \sn{9.9}{-3}\\
& Capture probability & 0.658 & 0 & 0 \\
\midrule
Corrections& Self absorption & 1 & 0 & 0\\
& True coincidence summing & 1 &0 & 0\\
& TRP reset time & 1.01 & 0 & 0 \\
& Dead time & 1.041& 0 & 0\\
\midrule
Results & Number of X-rays & \sn{6.05}{6} & \sn{0.37}{6} & 0.06\\
& Number of $\mu$ stopped & \sn{7.54}{6} & \sn{0.46}{6}&0.06\\
& Number of captures& \sn{4.96}{6} & \sn{0.31}{6} & 0.06\\
\bottomrule
\end{tabular}
\end{center}
\caption{Number of X-rays and muon captures in the passive silicon runs.}
\label{tab:si16p_ncapture_cal}
\end{table}
% subsection number_stopped_muons (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Lifetime measurement}
\label{sub:lifetime_measurement}w
To check the origin of the protons recorded, lifetime measurements were made by
cutting on time difference between a hit on one thick silicon and the muon
hit. Applying the time cut in 0.5~\si{\us}\ time steps on the proton
events in \cref{fig:si16p_proton_after_ecut}, the number of surviving
protons on each arm are plotted on \cref{fig:si16p_proton_lifetime}. The
curves show decay constants of $762.9 \pm 13.7$~\si{\ns}\ and $754.6 \pm
11.9$,
which are consistent with the each other, and with mean life time of muons in
silicon in the literatures of $758 \pm 2$~\cite{}. This is the confirmation
that the protons seen by the silicon detectors were indeed from the silicon
target.
\begin{figure}[htb]
\centering
\includegraphics[width=0.75\textwidth]{figs/si16p_proton_lifetime}
\caption{Lifetime measurement of protons seen on the silicon detectors.}
\label{fig:si16p_proton_lifetime}
\end{figure}
The fits are consistent with lifetime of muons in silicon in from after 500~ns,
before that, the time constants are shorter ($655.9\pm 9.9$ and $731.1\pm8.9$)
indicates the contamination from muon captured on material with higher $Z$.
Therefore a timing cut from 500~ns is used to select good silicon events, the
remaining protons are shown in \cref{fig:si16p_proton_ecut_500nstcut}.
The spectra have a low energy cut off at 2.5~MeV because protons with energy:
lower than that could not pass through the thin silicon to make the cuts as the
range of 2.5~MeV protons in silicon is about 68~\si{\um}.
\begin{figure}[htb]
\centering
\includegraphics[width=0.85\textwidth]{figs/si16p_proton_ecut_500nstcut}
\caption{Proton spectrum after energy and timing cuts}
\label{fig:si16p_proton_ecut_500nstcut}
\end{figure}
% subsection lifetime_measurement (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Proton emission rate from the silicon target}
\label{sub:proton_emission_rate_from_the_silicon_target}
The number of protons in \cref{fig:si16p_proton_ecut_500nstcut} is
counted from 500~ns after the muon event, where the survival rate is
$e^{-500/758} = 0.517$.
The geometry acceptance of each silicon arm is estimated to be \sn{2.64}{-2}
using a toy MC study where geantinos are generated within the image of the
collimator on the target, and the number of hits on each silicon package was
counted. Taking the geometry acceptance into account, the number of protons
with energy from 2.5 to 8~MeV emitted is:
\begin{equation}
N_{p \textrm{eff.}} = \dfrac{1927 + 1656}{0.517\times2.64\times10^{-2}}
= 2.625 \times 10^5
\end{equation}
The emission rate per muon capture is:
\begin{align}
R_{2.5-8\textrm{ MeV}}^{\textrm{eff.}} &= \dfrac{N_{p \textrm{eff.}}}
{N_{\mu \textrm{ captured}}^{\textrm{Si16p}}}\nonumber\\
&= \dfrac{2.625 \times 10^5}{6.256\times10^6} \nonumber\\
&= 4.20\times10^{-2}\nonumber
\end{align}
The proton spectra on the \cref{fig:si16p_proton_ecut_500nstcut} and the
emission rate are only effective ones, since the energy of protons are modified
by energy loss in the target, and low energy protons could not escape the
target. Therefore further corrections are needed for both rate and spectrum of
protons.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Proton emission rate uncertainties}
\label{sub:proton_emission_rate_and_uncertainties_estimation}
The uncertainty of the emission rate could come from several sources:
\begin{enumerate}
\item number of captures $\pm0.562\times10^6$, or 9\%, mainly from the
background under the X-ray peak (5.5\%) and the efficiency calibration
\item number of protons: efficiency of the cuts in energy, impacts of the
timing resolution on timing cut. The energy cuts' contribution should be
small since it can be seen from \cref{fig:si16p_loge+logde}, the peak
of protons is strong and well separated from others. The uncertainty in
timing contribution is significant because all the timing done in this
analysis was on the peak of the slow signals. As it is clear from the
\cref{fig:tme_sir_prompt_rational}, the timing resolution of the
silicon detector could not be better than 100~ns. Putting $\pm100$~ns into
the timing cut could change the survival rate of proton by about
$1-e^{-100/758} \simeq 13\%$. Also, the low statistics contributes a few
percent to the uncertainty budget.
\item acceptance of the silicon packages: muon stopping distribution,
imperfect alignment, efficiency of the detectors, different response to
different species. The muon stopping distribution is important in unfolding
the initial proton spectrum and also greatly affects the rate of protons.
By the end of the run, we found that the target was displaced from the
previously aligned position by 10~mm. Whether this misalignment is serious
or not depends on the spatial distribution of the muons after the
collimator. In the worst case when the muon beam is flatly distributed,
that displacement could change the acceptance of the silicon detectors by
12\%. Although no measurement was done to determine the efficiency of the
silicon detectors, it would have small effect compared to other factors.
\end{enumerate}
The combined uncertainty from known sources above therefore could be as large
as 35\%, and the effective proton emission rate in the 2.5--8~MeV could be
written as:
\begin{equation}
R_{2.5-8\textrm{ MeV}}^{\textrm{eff.}} = (4.20\pm1.47)\times 10^{-2}
\end{equation}
\subsection{Ratio of protons to other heavy charged particles}
\label{sub:heavy_charged_particles_emission_rate}
By using only the lower limit on
$\ln(\textrm{E}) + 0.85\times\ln(\Delta \textrm{E})$, the heavy charged
particles can be selected. These particles also show a lifetime that is
consistent with that of muons in silicon
(\cref{fig:si16p_allparticle_lifetime}).
\begin{figure}[htb]
\centering
\includegraphics[width=0.85\textwidth]{figs/si16p_allparticle_lifetime}
\caption{Lifetime of heavy charged particles}
\label{fig:si16p_allparticle_lifetime}
\end{figure}
The ratio between the number of protons and other particles at 500~ns is $(1927
+ 1656)/(2202 + 1909) \simeq 0.87$.
% subsection heavy_charged_particles_emission_rate (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%I have started the initial study on the correction ()
% subsection proton_emission_rate_from_the_silicon_target (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%\subsection{Rate and spectrum correction}
%\label{sub:proton_spectrum_deconvolution}
%The proton spectra on the \cref{fig:si16p_proton_ecut_500nstcut} and the
%emission rate are only effective ones, since the energy of protons are modified
%by energy loss in the target, and low energy protons could not escape the
%target. Therefore corrections are needed for both rate and spectrum of protons.
%To solve the unfolding problem, one needs to supply a response function that
%relates the observed energy to the initial energy of protons. This response
%function can be obtained from Monte Carlo simulation where protons with an
%assumed initial spatial distribution inside the target, and a uniform energy
%distribution are generated, then their modified energy spectrum is recorded.
%The initial spatial distribution of protons is inferred from the muon beam
%momentum using Monte Carlo simulation, and available measured data in momentum
%scanning runs. The response function for this thin silicon target is shown in
%\cref{fig:si16p_toyMC}.
%\begin{figure}[htb]
%\centering
%\includegraphics[width=0.85\textwidth]{figs/si16p_toyMC}
%\caption{An example of response function between the observed energy and
%initial energy of protons in a 62-\si{\um}-target.}
%\label{fig:si16p_toyMC}
%\end{figure}
%The response function is then used to train the unfolding program, which is
%based on the RooUnfold package. The package supports several unfolding methods,
%and I adopted the so-called Bayesian unfolding method~\cite{DAgostini.1995a}.
%The Bayesian method is chosen because it tends to be fast, typical number of
%iterations is from 4--8.
%\cref{fig:si16p_unfold_train} presented results of two tests unfolding with
%two distributions of initial energy, a Gaussian distribution and
%a parameterized function in~\eqref{eqn:EH_pdf}. The numbers of protons obtained
%from the tests show agreement with the generated numbers.
%\begin{figure}[htb]
%\centering
%\includegraphics[width=0.85\textwidth]{figs/si16p_unfold_train}
%\caption{Bayesian unfolding tests with two different initial proton energy
%distributions: Gaussian (left) and parameterized function of Sobottka and
%Wills's proton spectrum (right).}
%\label{fig:si16p_unfold_train}
%\end{figure}
%Finally, the unfolding is applied on the spectra in
%\cref{si16p_proton_spec}, the results are shown in
%\cref{si16p_unfold_meas}.
%\begin{figure}[htb]
%\centering
%\includegraphics[width=0.85\textwidth]{figs/si16p_unfold_meas}
%\caption{Unfolded spectrum from a thin silicon target}
%\label{fig:si16p_unfold_meas}
%\end{figure}
% subsection proton_spectrum_deconvolution (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%\subsection{Proton emission rate and uncertainties estimation}
%\label{sub:proton_emission_rate_and_uncertainties_estimation}
%The rate of proton emission from 2.5--10~\si{\MeV} is:
%\begin{equation}
%R =
%\end{equation}
%\begin{equation}
%R =
%\end{equation}
%The uncertainties are:
% subsection proton_emission_rate_and_uncertainties_estimation (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% section charged_particles_following_muon_capture_on_a_thin_silicon_target (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%The uncertainties are:
% subsection proton_emission_rate_and_uncertainties_estimation (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% section charged_particles_following_muon_capture_on_a_thin_silicon_target (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Proton emission following muon capture on an aluminium target}
\label{sec:proton_emission_following_muon_capture_on_an_aluminium_target}
The aluminium is the main object of the AlCap experiment, in this preliminary
analysis I chose one target, Al100 the 100-\si{\um}-thick target, on
a sub-range of the data set runs 2808--2873, as a demonstration.
Because this is a passive target, the same procedure and cuts used in the
passive silicon runs were applied.
\subsection{The number of stopped muons}
\label{sub:the_number_of_stopped_muons}
The X-ray spectrum on the germanium detector is shown on
\cref{fig:al100_ge_spec}.
\begin{figure}[htb]
\centering
\includegraphics[width=0.85\textwidth]{figs/al100_ge_spec}
\caption{X-ray spectrum from the aluminium target, the characteristic
$(2p-1s)$ line shows up at 346.67~keV}
\label{fig:al100_ge_spec}
\end{figure}
The area of the $(2p-1s)$ line of aluminium and the number of captured in this
target are:
\begin{align}
N_{(2p-1s)\textrm{Al}} &= 3800.0 \pm 179.4 \nonumber\\
N_{\mu \textrm{ captured}}^{\textrm{Al100}}
&= \dfrac{N_{(2p-1s)\textrm{Al}}}
{\epsilon_{(2p-1s)\textrm{Al}} \times I_{(2p-1s)\textrm{Al}}}
\times f_{\textrm{capture-Al}} \nonumber \\
&= \dfrac{3800.0} {5.12\times 10^{-4} \times 0.798} \times 0.609 \nonumber \\
&= (5.664 \pm 0.479) \times 10^6
\end{align}
% subsection the_number_of_stopped_muons (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Particle identification}
\label{sub:particle_identification}
Using the same charged particle selection
procedure and the cuts on $\ln(\textrm{E})$ and $\ln(\Delta\textrm{E})$, the
proton energy spectrum is shown in \cref{fig:al100_proton_spec}.
\begin{figure}[htb]
\centering
\includegraphics[width=1\textwidth]{figs/al100_selection}
\caption{Selection of protons from the Al100 target: coincidence cut (top),
cuts on energy (middle) and the results (bottom).}
\label{fig:al100_selection}
\end{figure}
The lifetime of these protons are shown in
\cref{fig:al100_proton_lifetime}, the fitted decay constant on the right
arm is consistent with the reference value of $864 \pm 2$~\si{\ns}~\cite{}.
But the left arm gives $918 \pm 16.1$~\si{\ns}, significantly larger than
the reference value.
%The longer lifetime suggested some contributions from
%other lighter materials, one possible source is from muons captured on the back
%side of the collimator (\cref{fig:alcap_setup_detailed}).
%For this reason, the emission rate calculated from the left arm will be taken as upper
%limit only.
\begin{figure}[htb]
\centering
\includegraphics[width=0.85\textwidth]{figs/al100_proton_lifetime}
\caption{Lifetime of protons from the aluminium Al100 target}
\label{fig:al100_proton_lifetime}
\end{figure}
Further investigation of the problem of longer lifetime was made and the first
channel on the thin silicon detector on that channel was the offender. The
lifetime measurement with out that SiL1-1 channel gives a reasonable result,
and the decay constant on the SiL1-1 alone was nearly about 1000~\si{\us}.
The reason for this behaviour is not known yet. For this emission rate
calculation, this channel is discarded and the rate on the left arm is scaled
with a factor of 4/3. The proton spectrum from the aluminium target is plotted
on \cref{fig:al100_proton_spec_wosil11}.
\begin{figure}[htb]
\centering
\includegraphics[width=0.40\textwidth]{figs/al100_proton_lifetime_wosil11}
\includegraphics[width=0.40\textwidth]{figs/al100_proton_lifetime_sil11}
\caption{Lifetime of protons without channel SiL1-1 (right) and of the
channel SiL1-1 alone (left).}
\label{fig:al100_proton_lifetime_sil11}
\end{figure}
\begin{figure}[htb]
\centering
\includegraphics[width=0.85\textwidth]{figs/al100_proton_spec_wosil11}
\caption{Spectrum of protons from the Al100 target after cuts on energy and
time, without channel SiL1-1}
\label{fig:al100_proton_spec_wosil11}
\end{figure}
% subsection particle_identification (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Proton emission rate}
\label{sub:proton_emission_rate_and_corrections}
The proton rate is calculated as:
\begin{equation}
N_{p \textrm{eff.}} = \dfrac{1132\times \frac{4}{3} + 2034}
{e^{-500/864}\times2.64\times10^{-2}}
= 1.34 \times 10^5
\end{equation}
\begin{equation}
R_{2.5-8\textrm{ MeV}}^{\textrm{Al eff.}} = \dfrac{N_{p \textrm{eff.}}}
{N_{\mu \textrm{ captured}}^{\textrm{Al100}}}
= \dfrac{1.34 \times 10^5}{5.664\times10^6}
= 2.37\times10^{-2}
\end{equation}
The uncertainty of the emission rates will be smaller than that of the rate
from silicon because of a longer lifetime of muons in aluminium and a higher
momentum beam made the misalignment of the target, if any, less important. To
be conservative, I take to 35\% above as this calculation uncertainty, and the
rates will be:
\begin{equation}
R_{2.5-8\textrm{ MeV}}^{\textrm{Al eff.}}=(2.37\pm0.83)\times10^{-2}
\end{equation}
% subsection proton_emission_rate_and_corrections (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% section proton_emission_following_muon_capture_on_an_aluminium_target (end)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% chapter data_analysis (end)

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