1058 lines
51 KiB
TeX
1058 lines
51 KiB
TeX
\chapter{The AlCap Run 2013}
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\label{cha:the_alcap_run_2013}
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\thispagestyle{empty}
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The first run of the AlCap experiment was performed at the $\pi$E1 beam line
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area, PSI from November 26 to December 23, 2013. The goal of the run was to
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measure protons rate and their spectrum following muon capture on aluminium.
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\section{Experimental set up}
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\label{sec:experimental_set_up}
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The low energy muons from the $\pi$E1 beam line were stopped in thin aluminium
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and silicon targets, and charged particles emitted were measured by two pairs
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of silicon detectors inside of a vacuum vessel
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(\cref{fig:alcap_setup_detailed}). A stopped muon event is defined by
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a group of upstream detectors and a muon veto plastic scintillator.
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The number of stopped muons is monitored by a germanium detector placed outside
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of the vacuum chamber. In addition, several plastic scintillators were used to
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provide veto signals for the silicon and germanium detectors. Two liquid
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scintillators for neutron measurements were also tested in this run.
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\begin{figure}[btp]
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\centering
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\includegraphics[width=0.65\textwidth]{figs/alcap_setup_detailed}
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\caption{AlCap detectors: two silicon packages inside the vacuum vessel,
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muon beam detectors including plastic scintillators and a wire chamber,
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germanium detector and veto plastic scintillators.}
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\label{fig:alcap_setup_detailed}
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\end{figure}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\subsection{Muon beam and vacuum chamber}
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Muons in the $\pi$E1 beam line are decay products of pions created
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as a \SI{590}{\mega\electronvolt} proton beam hits a thick carbon target. The
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beam line was designed to deliver muons with momenta ranging from
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\SIrange{10}{500}{\mega\electronvolt\per\cc} and momentum spread from
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\SIrange{0.26}{8.0}{\percent}~\cite{Foroughli.1997}. These parameters can be
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selected by changing various magnets and slits shown in
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\cref{fig:psi_piE1_elements}.
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%(E-target in \cref{fig:psi_exp_hall_all}).
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%\begin{figure}[p]
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%\centering
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%\includegraphics[height=0.85\textheight]{figs/psi_exp_hall_all}
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%\caption{Layout of the PSI experimental hall, $\pi$E1 experimental area is
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%marked with the red circle. \\Image taken from
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%\url{http://www.psi.ch/num/FacilitiesEN/HallenplanPSI.png}}
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%\label{fig:psi_exp_hall_all}
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%\end{figure}
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\begin{figure}[btp]
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\centering
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\includegraphics[width=0.7\textwidth]{figs/psi_piE1_elements}
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\caption{The $\pi$E1 beam line}
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\label{fig:psi_piE1_elements}
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\end{figure}
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One of the main requirements of the AlCap experiment was a low energy muon beam
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with narrow momentum bite in order to achieve a high fraction of stopping muons
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in the very thin targets. In this Run 2013, muons from
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\SIrange{28}{45}{\mega\electronvolt\per\cc} and momentum spread of 1\% and
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3\%, respectively, were used.
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For part of the experiment the target was replaced with one of the silicon
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detector packages allowed an accurate momentum and range calibration
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%(via range-energy relations)
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of the beam at the target. \Cref{fig:Rates} shows the measured muon rates
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as a function of momentum for two different momentum bites.
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\Cref{fig:Beam} shows an example of the resulting energy spectra.
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\begin{figure}[btp]
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\centering
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\includegraphics[width=0.6\textwidth]{figs/Rates.png}
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\caption{Measured muon rate (kHz) at low momenta. Momentum bite of 3 and 1 \%
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FWHM, respectively.}
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\label{fig:Rates}
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\end{figure}
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\begin{figure}[btp]
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\centering
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\includegraphics[width=0.9\textwidth]{figs/beam.pdf}
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\caption{Energy deposition at \SI{36.4}{/c} incident muon beam in an
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\SI{1500}{\micro\meter}-thick active target. The peak at low energy is due
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to beam electrons, the peaks at higher energies are due to muons. Momentum
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bite of 1 and 3\% FWHM on left and right hand side, respectively.}
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\label{fig:Beam}
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\end{figure}
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The targets and charged particle detectors are installed inside the vacuum
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chamber as shown in \cref{fig:alcap_setup_detailed}. The muon beam enters
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from the right of \cref{fig:alcap_setup_detailed} and hits the target, which is
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placed at the centre of the vacuum chamber and orientated at 45 degrees to the
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beam axis.
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The side walls and bottom flange of the vessel provide several
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vacuum-feedthroughs for the high voltage and signal cables for the silicon and
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scintillator detectors inside the chamber.
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In addition, the chamber is equipped with several lead collimators
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%so that muons that are not captured in the target would quickly decay.
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to quickly capture muons that do not stop in the actual target.
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%\begin{figure}[btp]
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%\centering
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%\includegraphics[width=0.55\textwidth]{figs/SetupOverview.jpg}
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%\caption{Vacuum chamber in beam line}
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%\label{fig:SetupOverall}
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%\end{figure}
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%It is known fact that there is a risk of sparkling between the electrodes of
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%a silicon detector in the low vacuum region of $10^{-3}$ mbar.
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%An interlock mechanism was installed to prevent the bias of the
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%silicon detectors from being applied before the safe vacuum level.
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For a safe operation of the silicon detector, a vacuum of \SI{e-4}{\milli\bar}
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was necessary. With the help of the vacuum group of PSI, we could consistently
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reach the required vacuum level within 45 minutes after closure of the
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chamber's top flange.
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\subsection{Silicon detectors}
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The main detectors for proton measurement in the Run 2013 were four large area
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silicon detectors. The silicon detectors were grouped into two detector
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packages located symmetrically at 90 degrees of the nominal muon beam path, SiL
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and SiR in \cref{fig:alcap_setup_detailed}. Each arm consists of: one
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$\Delta$E counter, a \SI{65}{\micro\meter}-thick silicon detector, divided into
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4 quadrants; one E counter made from \SI{1500}{\micro\meter}-thick silicon; and
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one plastic scintillator to identify electrons or high energy protons that
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pass through the silicon. The area of each of these silicon detectors and the
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scintillators is $50\times50 \textrm{mm}^2$. There is a dead layer of
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\SI{0.5}{\micro\meter} on each side of the silicon detectors according to the
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manufacturer Micron Semiconductor
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\footnote{\url{http://www.micronsemiconductor.co.uk/}}.
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The detectors were named according to their positions relative to the muon
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view: the SiL package contains the thin
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detector SiL1 and thick detector SiL2; the SiR package has SiR1 and SiR2
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accordingly. Each quadrant of the thin detectors were also numbered from 1 to
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4, i.e. SiL1-1, SiL1-2, SiL1-3, SiL1-4, SiR1-1, SiR1-2, SiR1-3,
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SiR1-4.
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Bias for the four silicon detectors was supplied by an ORTEC 710 NIM module,
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which has a vacuum interlock input to prevent biasing before the safe vacuum
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level has been reached. Typical voltage to fully depleted the detectors were
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\SI{-300}{\volt} and \SI{-10}{\volt} for the thick and thin silicon detectors
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respectively. The leakage currents at the operating voltages are less than
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\SI{1.5}{\micro\ampere} for the thick detectors, and about
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\SI{0.05}{\micro\ampere} for the thin ones (see \cref{fig:si_leakage}).
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\begin{figure}[btp]
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\centering
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\includegraphics[width=0.85\textwidth]{figs/si_leakage}
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\caption{Leakage currents of the silicon detectors under bias.}
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\label{fig:si_leakage}
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\end{figure}
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The fact that a detector were fully depleted was checked by putting
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a calibration source $^{241}\textrm{Am}$ at its ohmic side, and observing the
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output
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pulse height on an oscilloscope. One would expect that the maximum pulse height
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increases as the bias is raised until the voltage of fully depleted. The effect
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can also be seen on the pulse height spectrum as in
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\cref{fig:sir2_bias_alpha}.
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\begin{figure}[btp]
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\centering
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\includegraphics[width=0.75\textwidth]{figs/sir2_bias_alpha}
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\caption{$^{241}\textrm{Am}$ spectra in cases of fully depleted (top), and
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partly depleted (bottom).}
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\label{fig:sir2_bias_alpha}
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\end{figure}
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%It is known that the noise level of a silicon detector increases linearly with
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%its capacity. So both noise and pick-up suppression had been carefully
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%optimised in the real PSI accelerator environment, particularly for the thin
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%silicon detectors which have a large capacity of 1~\nano\farad~in each
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%quadrant.
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%After improving the feed-through flanges during the set-up phase of the
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%experiment with isolated ground connections, good electronic resolution of
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%55--76~\kilo\electronvolt\ FWHM was achieved in the thin silicon detectors.
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%So achieving good energy resolution was particularly challenging
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%for the thin silicon detector, as each quadrant had a large capacity of
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%1~\nano\farad. Both
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%noise and pick-up suppression had been carefully optimized in the real PSI
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%accelerator environment.
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%Optimization of the fast timing signals proved another challenge.
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%The energy calibration for the silicon detectors were done
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%by several means:
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%\begin{enumerate}
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%\item An $^{241}\textrm{Am}$ alpha source: the main alpha
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%particles have energies of 5.484~\mega\electronvolt\ (85.2\%) and
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%5.442~\mega\electronvolt\ (12.5\%). The source emits 79.5
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%$\alpha\per\second$ in 2$\pi$~\steradian.
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%\item Test pulse with a fixed amplitude: the preamplifiers used for the
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%silicon detectors are come with the manufacturer's specification on the
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%response, namely a 66 \milli\volt\ fed into the test input will produce an
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%output equivalent to that of a 1 \mega\electronvolt\ energy deposition.
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%\item Minimum ionisation particles
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%(MIPs): electrons in the beam are MIPs with a nominal deposit energy of
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%388~\electronvolt\per\micro\meter\ Si. This is only applicable for thick
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%silicon detectors because the energy deposit is large enough and the energy
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%resolution is good enough. During the run, this peak was observed to make
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%sure the stability of the electronics.
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%\item Muons with different momenta: the thick silicon detectors were placed
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%at the target position during beam tuning period, allowed an accurate
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%momentum and range calibration. This also only works with thick silicon
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%detectors.
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%\end{enumerate}
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% subsection silicon_detectors (end)
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\subsection{Upstream counters}
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\label{sub:upstream_counters}
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The upstream detector consists of three counters: a \SI{500}{\micro\meter}-thick
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scintillator muon trigger counter (\Pmu{}SC); a muon anti-coincidence counter
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(\Pmu{}SCA) surrounding the trigger counter with a hole
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of 35 \si{\milli\meter}\ in diameter to define the beam radius; and a multi-wire
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proportional chamber (\Pmu{}PC) that uses 24 X wires and 24 Y wires at
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2~\si{\milli\meter}~intervals.
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The upstream detectors provide signal of an incoming muon as coincident hits on
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the muon trigger and the wire chamber in anti-coincidence with the muon
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anti-coincidence counter.
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This set of detectors along with their read-out system
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belong to the MuSun experiment, which operated at the same beam line just
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before our run. Thanks to the MuSun group, the detectors were well-tuned and
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ready to be used in our run without any modification.
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% subsection upstream_counters (end)
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\subsection{Germanium detector}
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%\begin{figure}[btp]
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%\centering
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%\includegraphics[width=0.9\textwidth]{figs/neutron.png}
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%\caption{Setup of two
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%liquid scintillators outside the vacuum envelope for neutron detection.}
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%\label{fig:neutron}
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%\end{figure}
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We used a germanium detector to normalise the number of stopped muons by
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measuring characteristics muon X-rays from the target material. The primary
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X-rays of interest are the 346.828~keV line for aluminium targets, and the
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400.177 line for silicon targets. The energies and intensities of the X-rays
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listed in \cref{tab:xray_ref} follow measurement results from
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Measday and colleagues~\cite{MeasdayStocki.etal.2007}.
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\begin{table}[btp]
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\begin{center}
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\begin{tabular}{c l l l l }
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\toprule
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\textbf{Elements} & \textbf{Transition}
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& \textbf{Energy} & \textbf{Intensity}\\
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\midrule
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$^{27}\textrm{Al}$ & $2p-1s$ & $346.828 \pm 0.002$ & $79.8\pm 0.8$\\
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& $3p-1s$ & $412.87 \pm 0.05$ & $7.62\pm 0.15$\\
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\midrule
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$^{28}\textrm{Si}$ & $2p-1s$ & $400.177 \pm 0.005$ & $80.3\pm 0.8$\\
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& $3p-1s$ & $476.80 \pm 0.05$ & $7.40 \pm 0.20$\\
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\bottomrule
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\end{tabular}
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\end{center}
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\caption{Reference values of major muonic X-rays from aluminium and silicon.}
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\label{tab:xray_ref}
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\end{table}
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The germanium detector is
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a GMX20P4-70-RB-B-PL, n-type, coaxial high purity germanium detector produced
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by ORTEC. The detector was optimised for low energy gamma and X-rays
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measurement with an ultra-thin entrance window of 0.5-mm-thick beryllium and
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a 0.3-\si{\micro\meter}-thick ion implanted contact (\cref{fig:ge_det_dimensions}).
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This detector is equipped with a transistor reset preamplifier which,
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according to the producer, enables it to work in an ultra-high rate environment
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up to $10^6$ counts\si{\per\second} at \SI{1}{\mega\electronvolt}.
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\begin{figure}[btp]
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\centering
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\includegraphics[width=0.9\textwidth]{figs/ge_det_dimensions}
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\caption{Dimensions of the germanium detector}
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\label{fig:ge_det_dimensions}
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\end{figure}
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The detector was installed outside of the vacuum chamber at 32 cm from the
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target, seeing the target through a 10-mm-thick aluminium window, behind
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a plastic scintillator counter used to veto electrons. Liquid nitrogen
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necessary for the operation of the detector had to be refilled every 8 hours.
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A timer was set up in the data acquisition system to remind this.
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\subsection{Plastic and liquid scintillators}
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\label{sub:plastic_scintillators}
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Apart from the scintillators in the upstream group, there were four other
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plastic scintillators used as veto counters for:
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\begin{itemize}
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\item punch-through-the-target muons, ScVe
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\item electrons and other high energy charged particles for germanium
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detector (ScGe) and silicon detectors (ScL and ScR)
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\end{itemize}
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The ScL, ScR and ScVe were installed inside the vacuum vessel and were
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optically connected to external PMTs by light-guides at the bottom flange.
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We also set up two liquid scintillation counters for neutron measurements in
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preparation for the next beam time where the neutron measurements will be
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carried out.
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% subsection plastic_scintillators (end)
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\section{Front-end electronics and data acquisition system}
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The front-end electronics of the AlCap experiment was simple since we employed
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a trigger-less read out system with waveform digitisers and flash ADCs
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(FADCs). As shown in \cref{fig:alcapdaq_scheme}, all plastic
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scintillators signals were amplified by PMTs, then fed into the digitisers. The
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signals from silicon and germanium detectors were preamplified, and
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subsequently shaped by spectroscopy amplifiers and timing filter amplifiers
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(TFAs) to provide energy and timing information.
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\begin{figure}[btp]
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\centering
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\includegraphics[width=0.99\textwidth]{figs/alcapdaq_scheme}
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\caption{Schematic diagram of the electronics and DAQ used in the Run 2013}
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\label{fig:alcapdaq_scheme}
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\end{figure}
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The germanium detector has its own transistor reset preamplifier
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installed very close to the germanium crystal. Two ORTEC Model 142
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preamplifiers were used for the thick silicon detectors. The timing outputs of
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the preamplifiers were fed into three ORTEC Model 579 TFAs.
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We used an ORTEC Model 673 to shape the germanium signal with 6~\si{\micro\second}
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shaping time.
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A more modern-style electronics was used for thin silicon detectors where the
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preamplifier, shaping and timing amplifiers were implemented on one compact
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package, namely a Mesytec MSI-8 box. This box has 8 channels, each channel
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consists of one preamplifier board and one shaper-and-timing filter board which
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can be fine-tuned independently. The shaping time was set to 1~\si{\micro\second}\
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for all channels.
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The detector system produced signals that differs significantly in time scale,
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ranging from very fast (about 40~\si{\nano\second}\ from scintillators) to very slow
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(several \si{\micro\second}\ from shaping outputs of semiconductor detectors). This
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lead to the use of several sampling frequencies from 17~\si{\mega\hertz}\ to
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250~\si{\mega\hertz}, and three types of digitisers were employed:
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\begin{itemize}
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\item custom-built 12-bit 170-MHz FADCs which was designed for the
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MuCap experiment. Each FADC board has the same dimensions as those of
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a single-width 6U VME module, but is hosted in a custom built crate due to
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its different power supply mechanical structure. The FADC communicates with
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a host computer through a 100-Mb/s Ethernet interface using a simple
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Ethernet-level protocol. The protocol only allows detecting
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incomplete data transfers but no retransmitting is possible due to the
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limited size of the module's output buffer. The FADCs accept clock signal
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at the frequency of 50~\si{\mega\hertz}\ then multiply that internally up to
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170~\si{\mega\hertz}. Each channel on one board can run at different sampling
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frequency not dependent on other channels. The FADC has 8 single-ended
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LEMO inputs with 1~\si{\volt} pp dynamic range.
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\item a 14-bit 100-MS/s CAEN VME FADC waveform digitiser model V1724. The
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module houses 8 channels with 2.25~Vpp dynamic range on single-ended MCX
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coaxial inputs. The digitiser features an optical link for transmission of
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data to its host computer. All of 8 channels run at the same sampling
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frequency and have one common trigger.
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\item a 12-bit 250-MS/s CAEN desktop waveform digitizer model DT5720. This
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digitiser is similar to the V1724, except for its form factor and maximum
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sampling frequency. Although there is an optical link available, the module
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is connected to its host computer through a USB 2.0 interface where data
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transfer rate of 30 MB/s was determined to be good enough in our run
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(actual data rate from this digitiser was typically about 5 MB/s during the
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run). Communication with both CAEN digitisers was based on CAEN's
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proprietary binary drivers and libraries.
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\end{itemize}
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All digitisers were driven by external clocks which were derived from the same
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500-\si{\mega\hertz}\ master clock, a high precision RF signal generator Model SG382
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of Stanford Research System.
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The silicon detectors were read out by FADC boards feature network-based data
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readout interface. To maximize the data throughput, each of the four FADC
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boards was read out through separate network adapter.
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The CAEN digitisers were used to read out
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the germanium detector (timing and energy, slow signals) or scintillator
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detectors (fast signals). For redundancy, all beam monitors (\Pmu{}SC, \Pmu{}SCA
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and \Pmu{}PC) were also read out by a CAEN time-to-digital converter (TDC)
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model V767 which was kindly provided by the MuSun experiment.
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The Data Acquisition System (DAQ) of the AlCap experiment, so-called AlCapDAQ,
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provided the readout of front-end electronics, event assembling, data logging,
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hardware monitoring and control, and the run database of the experiment
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(\cref{fig:alcapdaq_pcs}). It was based on the MIDAS framework~\footnote{
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MIDAS is a general purpose DAQ software system developed at PSI and TRIUMF:\\
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\url{http://midas.triumf.ca}} and consisted of two circuits, {\em i})
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a detector circuit for synchronous data readout from the front-end electronics
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instrumenting detectors, and {\em ii}) a slow control circuit for asynchronous
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periodic hardware monitoring (vacuum, liquid nitrogen
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filling). The detector circuit consisted of three computers, two front-end
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computers and one computer serving both as a front-end and as a back-end
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processor. The slow circuit consisted of one computer. All computers were
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running Linux operating system and connected into a private subnetwork.
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%\hl{TODO: storage and shift monitor}
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\begin{figure}[btp]
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\centering
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\includegraphics[width=0.95\textwidth]{figs/alcapdaq_pcs}
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\caption{AlCapDAQ in the Run 2013. The {\ttfamily fe6} front-end is
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a VME single board computer belongs to the MuSun group, reads out the
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upstream detectors.}
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\label{fig:alcapdaq_pcs}
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\end{figure}
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The data were collected as dead-time-free time segments of 110~ms, called
|
|
``block'', followed by about 10-ms-long time intervals used to complete data
|
|
readout and synchronize the DAQ. Such data collection approach was chosen to
|
|
maximize the data readout efficiency. During each 110-ms-long period, signals
|
|
from each detector were digitized independently by threshold crossing. The data
|
|
segment of each detector data were first written into on-board memories of
|
|
front-end electronics and either read out in a loop (CAEN TDCs and CAEN
|
|
digitizers) or streamed (FADCs) into the computer memories. The thresholds were
|
|
adjusted as low as possible and individually for each detector. The time
|
|
correlation between detectors would be established in the analysis stage.
|
|
|
|
At the beginning of each block, the time counter in each digitiser is reset to
|
|
ensure time alignment across all modules. The period of 110~ms was chosen to be:
|
|
{\em i}) long enough compared to the time scale of several \si{\micro\second}\
|
|
of the physics of interest, {\em ii}) short enough so that there is no timer
|
|
rollover on any digitiser (a FADC runs at its maximum speed of
|
|
\SI{170}{\mega\hertz} could handle up to about \SI{1.5}{\second} with its
|
|
28-bit time counter).
|
|
|
|
To ease the task of handling data, the data collecting period was divided into
|
|
short runs, each run stopped when the logger had recorded 2 GB of data.
|
|
The data size effectively made each run last for about 5 minutes. The DAQ
|
|
automatically started a new run with the same parameters after about 6 seconds.
|
|
The short period of each run also allows the detection, and helps to reduce the
|
|
influence of effects such as electronics drifting, temperature fluctuation.
|
|
|
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
\section{Detector calibration}
|
|
\label{sec:detector_calibration}
|
|
The calibration was done mainly for the silicon and germanium detectors
|
|
because they would provide energy information. The plastic scintillators were
|
|
only checked by oscilloscopes to make sure that the minimum ionisation
|
|
particles (MIPs) could be observed. The upstream plastic scintillation
|
|
counters and wire chamber, as mentioned, were well-tuned by the MuSun group.
|
|
|
|
\subsection{Silicon detector}
|
|
\label{sub:silicon_detector}
|
|
The energy calibration for the silicon detectors were done routinely during the
|
|
run, by:
|
|
\begin{itemize}
|
|
\item a \SI{79.5}{\becquerel} $^{241}\textrm{Am}$ alpha source. The most
|
|
prominent alpha particles have energies of \SI{5.484}{\MeV} (85.2\%)
|
|
and \SI{5.442}{\MeV} (12.5\%). The alpha particles from the source
|
|
would lose about \SI{66}{\kilo\eV} in the \SI{0.5}{\um}-thick dead layer,
|
|
and the peak would appear at \SI{5418}{\kilo\eV} (\cref{fig:toyMC_alpha});
|
|
|
|
\item a tail pulse generator, A tail pulse with amplitude of
|
|
\SI{66}{\milli\volt}~was used to simulate the response of the silicon
|
|
detectors' preamplifiers to a particle with \SI{1}{\MeV} energy
|
|
deposition; and
|
|
|
|
\item during data taking period, electrons in the beam were were also used
|
|
for energy calibration of thick silicon detectors where energy deposition
|
|
is large enough. The muons at different momenta provided another mean of
|
|
calibration in the beam tuning period.
|
|
\end{itemize}
|
|
|
|
\begin{figure}[htb]
|
|
\centering
|
|
\includegraphics[width=0.6\textwidth]{figs/toyMC_alpha}
|
|
\caption{Energy loss of the alpha particles after a dead layer of
|
|
\SI{0.5}{\um}.}
|
|
\label{fig:toyMC_alpha}
|
|
\end{figure}
|
|
|
|
The conversion from ADC value to energy is done with a first-order polynomial:
|
|
\begin{equation}
|
|
\textrm{E [keV]} = \textrm{Slope} \times \textrm{ADC} + \textrm{Offset}.
|
|
\end{equation}
|
|
The calibration coefficients for the silicon channels are listed in
|
|
\cref{tab:cal_coeff}.
|
|
|
|
\begin{table}
|
|
\begin{center}
|
|
\pgfplotstabletypeset[
|
|
% separator
|
|
col sep=comma,
|
|
% columns displayed
|
|
display columns/0/.style={column name = \textbf{Detector}, string type,
|
|
column type=l},
|
|
display columns/1/.style={column name = \textbf{Slope}, column type=c,
|
|
dec sep align},
|
|
display columns/2/.style={column name = \textbf{Offset}, column type=r,
|
|
dec sep align},
|
|
% format the line breaks
|
|
every head row/.style={
|
|
before row={\toprule},
|
|
after row={\midrule},
|
|
%%TODO unit of coeffcients
|
|
%after row={ \arraybackslash
|
|
%{ }& { keV/channel } & { keV }\\
|
|
%\midrule},
|
|
%{}& {(keV/channel)} & {(keV)}\\ \midrule},
|
|
columns/Detector/.style={column type=c},
|
|
columns/Slope/.style={column type=c},
|
|
columns/Offset/.style={column type=c}
|
|
},
|
|
every last row/.style={after row=\bottomrule},
|
|
]{raw/si_cal_effs.csv}
|
|
\caption{Calibration coefficients of the silicon detector channels}
|
|
\label{tab:cal_coeff}
|
|
\end{center}
|
|
\end{table}
|
|
% subsection silicon_detector (end)
|
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
\subsection{Germanium detector}
|
|
\label{sub:germanium_detector}
|
|
The germanium detector was calibrated using a $^{152}\textrm{Eu}$
|
|
source
|
|
\footnote{Energies and intensities of gamma rays are taken from the
|
|
X-ray and Gamma-ray Decay Data Standards for Detector Calibration and Other
|
|
Applications, which is published by IAEA at \\
|
|
\url{https://www-nds.iaea.org/xgamma_standards/}},
|
|
the recorded pulse height spectrum is shown in \cref{fig:ge_eu152_spec}. The
|
|
source was placed at the target position so that the absolute efficiencies can
|
|
be calculated. The peak centroids and areas were obtained by fitting a Gaussian
|
|
peak on top of a first-order polynomial background. The only exception is the
|
|
\SI{1085.84}{\keV} line because of the interference of the \SI{1089.74}{\keV}
|
|
gamma, the two were fitted with two Gaussian peaks on top of a first-order
|
|
polynomial background.
|
|
|
|
The relation between pulse height in ADC value and energy is found to be:
|
|
\begin{equation}
|
|
\textrm{ E [keV]} = 0.1219 \times \textrm{ADC} + 1.1621
|
|
\end{equation}
|
|
The energy resolution (full width at half maximum - FWHM) was better than
|
|
2.6~\si{\keV}\ for all the $^{152}\textrm{Eu}$ peaks. It was
|
|
a little worse at 3.1~\si{\keV}~for the annihilation photons at
|
|
511.0~\si{\keV}.
|
|
|
|
\begin{figure}[htb]
|
|
\centering
|
|
\includegraphics[width=0.70\textwidth]{figs/ge_eu152_spec}
|
|
\caption{Energy spectrum of the $\rm^{152}\textrm{Eu}$ calibration source
|
|
recorded by the germanium detector. The most prominent peaks of
|
|
$^{152}\textrm{Eu}$ along with their energies are
|
|
annotated in red; the 1460.82 \si{\keV}~line is background from
|
|
$^{40}\textrm{K}$; and the annihilation 511.0~\si{\keV}~photons
|
|
come both from the source and the surrounding environment.}
|
|
\label{fig:ge_eu152_spec}
|
|
\end{figure}
|
|
|
|
\begin{figure}[htb]
|
|
\centering
|
|
\includegraphics[width=0.89\textwidth]{figs/ge_ecal_fwhm}
|
|
\caption{Germanium energy calibration and resolution.}
|
|
\label{fig:ge_fwhm}
|
|
\end{figure}
|
|
|
|
Following corrections for the peak areas are considered:
|
|
\begin{enumerate}
|
|
\item Correction for counting loss due to finite response time of the
|
|
detector system, where two gamma rays arrive at the detector within a time
|
|
interval short compared to that response time. This correction is
|
|
significant in our germanium system because of the current pulse
|
|
information extracting method does not count the second pulse (see
|
|
\cref{sub:offline_analyser}).
|
|
\item Correction of counting time loss in the reset periods of the transistor
|
|
reset preamplifier. A preamplifier of this type would reset itself after
|
|
accumulating a predetermined amount of charge. During a reset, the
|
|
preamplifier is insensitive so this can be counted as a dead time.
|
|
\item True coincidence summing correction: two cascade gamma rays hit the
|
|
detector at the same time would cause loss of counts under the two
|
|
respective peaks and gain under the sum energy peak.
|
|
\item Correction for self-absorption of a gamma ray by the source itself.
|
|
\end{enumerate}
|
|
|
|
The corrections for the first two mechanisms can be estimated by examining
|
|
pulse length and intervals between two consecutive pulses in the germanium
|
|
detector (\cref{fig:ge_cal_rate_pulselength}). The average pulse
|
|
length is \SI{45.7}{\um}, the average count rate obtained from the decay rate
|
|
of the interval spectrum is \SI{240}{\per\s}.
|
|
|
|
The correction factor for the finite response time of the detector system is
|
|
calculated as:
|
|
\begin{align}
|
|
k_{\textrm{finite response time}} &= e^{2\times \textrm{(pulse length)}
|
|
\times \textrm{(count rate)}}\\
|
|
&= e^{2\times 47.5\times10^{-6} \times 241} \nonumber\\
|
|
&= 1.02 \label{eqn:finite_time_response}
|
|
\end{align}
|
|
|
|
The resets of the preamplifier show up as a peak around \SI{2}{\ms},
|
|
consistent with specification of the manufacturer. Fitting the peak on top of
|
|
an exponential background gives the actual reset pulse length of
|
|
\SI{1947.34}{\us} and the number of resets during the calibration runs is
|
|
2335.0. The total time loss for resetting is hence:
|
|
$1947.34\times 10^{-6} \times 2335.0 = 4.55$ \si{\s}. That is a 0.14\% loss
|
|
for a measuring time of \SI{3245.5}{\s}. This percentage loss is insignificant
|
|
compared with the loss in \eqref{eqn:finite_time_response} and the statistical
|
|
uncertainty of peak areas.
|
|
|
|
\begin{figure}[htb]
|
|
\centering
|
|
\includegraphics[width=0.95\textwidth]{figs/ge_cal_rate_pulselength}
|
|
\caption{Germanium detector pulse length (left) and intervals between pulses
|
|
on that detector (right). The peak around \SI{2}{\ms} corresponds to the
|
|
resets of the preamplifier. The peak at \SI{250}{\us} is due to triggering
|
|
by the timing channel which is on the same digitiser.}
|
|
\label{fig:ge_cal_rate_pulselength}
|
|
\end{figure}
|
|
|
|
The true coincidence summing probability is estimated to be very small, about
|
|
\num{5.4d-6}, thanks to the far geometry of the calibration. The absorption in
|
|
the source cover made of \SI{22}{\mg\per\cm^2} polyethylene is less than
|
|
\num{4d-4} for a \SI{100}{\keV} photon. Therefore these two corrections are
|
|
omitted.
|
|
|
|
The absolute efficiencies of the reference gamma rays show agreement with those
|
|
obtained from a Monte Carlo (MC) study where a point source made of $^{152}$Eu
|
|
is placed at the target position (see \cref{fig:ge_eff_cal}). A comparison
|
|
between efficiencies in case of the point-like source and a finite-size
|
|
source is also done by MC simulation. The differences between the two sources
|
|
are generally smaller than 3\%, which are comparable with the uncertainties of
|
|
the efficiency calibration. That means the point-like efficiencies can be used
|
|
for a finite-sized source without correction.
|
|
%As shown in \cref{fig:ge_eff_cal}, the
|
|
%differences are in line with the uncertainties of the measured efficiencies.
|
|
%The dimensions of the latter are set to
|
|
%resemble the distribution of muons inside the target: Gaussian spreading
|
|
%\SI{11}{\mm} vertically, \SI{13}{\mm} horizontally, and \SI{127}{\um} in
|
|
\begin{figure}[htb]
|
|
\centering
|
|
\includegraphics[width=0.40\textwidth]{figs/ge_eff_cal}
|
|
\includegraphics[width=0.40\textwidth]{figs/ge_eff_mc_finitesize_vs_pointlike_root}
|
|
\caption{Absolute efficiency of the germanium detector (right) and
|
|
MC comparison of efficiencies in case of point-like and finite-sized
|
|
sources (left). The efficiencies curve is fitted on
|
|
7 measured energy points from \SIrange{244}{1408}{\keV}, the shaded area is
|
|
95\% confidence interval of the fit. The ratios on the left plot are
|
|
normalised to the efficiencies of the point-like case at each energy point.}
|
|
%because it is known that the linearity between
|
|
%$ln(\textrm{E})$ and $ln(\textrm{eff})$ holds better.
|
|
\label{fig:ge_eff_cal}
|
|
\end{figure}
|
|
The absolute efficiencies of the referenced points, and calculated efficiencies
|
|
at X-rays of interest are listed in \cref{tab:xray_eff}.
|
|
\begin{table}[htb]
|
|
\begin{center}
|
|
\pgfplotstabletypeset[
|
|
% separator
|
|
col sep=comma,
|
|
% columns displayed
|
|
% column type={S} means leave formatting to siunitx
|
|
display columns/0/.style={column name = \textbf{Photons (\si{\keV})},
|
|
string type,
|
|
column type={S[table-format=4.3, table-alignment=center]}},
|
|
display columns/1/.style={column name = \textbf{Efficiency},
|
|
string type,
|
|
column type={S[parse-numbers = true,
|
|
round-precision=3,
|
|
round-mode=figures,
|
|
fixed-exponent=-4,
|
|
scientific-notation=fixed,
|
|
table-format=1.2e-1,
|
|
%table-omit-exponent,
|
|
]}},
|
|
display columns/2/.style={column name = \textbf{Uncertainty},
|
|
string type,
|
|
column type={S[parse-numbers = true,
|
|
round-precision=3,
|
|
round-mode=figures,
|
|
fixed-exponent=-5,
|
|
scientific-notation=fixed,
|
|
table-format=1.3e-1,
|
|
%table-omit-exponent,
|
|
]}},
|
|
% format the line breaks
|
|
every head row/.style={
|
|
before row={\toprule},
|
|
after row={
|
|
%\textbf{\si{\keV}} & \textbf{\num{E-4}} & \textbf{\num{E-4}}\\
|
|
\midrule},
|
|
columns/0/.style={column type=r},
|
|
columns/1/.style={column type=c},
|
|
columns/2/.style={column type=c}
|
|
},
|
|
every last row/.style={after row=\bottomrule},
|
|
every nth row={8}{before row={\midrule}},
|
|
]{raw/ge_eff.csv}
|
|
\end{center}
|
|
\caption{Absolute efficiencies of the germanium detector in case of
|
|
a point-like source placed at the centre of the target (upper half), and
|
|
the calculated efficiencies for the X-rays of interest (lower half).}
|
|
\label{tab:xray_eff}
|
|
\end{table}
|
|
|
|
% subsection germanium_detector (end)
|
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
%\subsection{Beam tuning and muon momentum scanning}
|
|
%\label{sub:muon_momentum_scanning}
|
|
%Before taking any data, we carried out the muon momentum scanning to understand
|
|
%the muon beam, as well as calibrate the detector system. The nominal muon
|
|
%momentum used in the Run 2013 had been tuned to 28~MeV\cc\ before the run. By
|
|
%changing simultaneously the strength of the key magnet elements in the $\pi$E1
|
|
%beam line with the same factor, the muon beam momentum would be scaled with the
|
|
%same factor.
|
|
|
|
%The first study was on the range of muons in an active silicon target. The SiL2
|
|
%detector was placed perpendicular to the nominal beam path, after an oval
|
|
%collimator. The beam momentum scaling factor was scanned from 1.10 to 1.60,
|
|
%muon momenta and energies in the measured points are listed in
|
|
%\cref{tab:mu_scales}.
|
|
%\begin{table}[htbp]
|
|
%\begin{center}
|
|
%\begin{tabular}{c c c c}
|
|
%\toprule
|
|
%\textbf{Scaling} & \textbf{Momentum} & \textbf{Kinetic energy}
|
|
%& \textbf{Momentum spread}\\
|
|
%\textbf{factor} & \textbf{(MeV\per\cc)} & \textbf{(MeV)}
|
|
%& \textbf{(MeV\per\cc, 3\% FWHM)}\\
|
|
%\midrule
|
|
%1.03 & 28.84 & 3.87& 0.87\\
|
|
%1.05 & 29.40 & 4.01& 0.88\\
|
|
%1.06 & 29.68 & 4.09& 0.89\\
|
|
%1.07 & 29.96 & 4.17& 0.90\\
|
|
%1.10 & 30.80 & 4.40& 0.92\\
|
|
%1.15 & 32.20 & 4.80& 0.97\\
|
|
%1.20 & 33.60 & 5.21& 1.01\\
|
|
%1.30 & 36.40 & 6.09& 1.09\\
|
|
%1.40 & 39.20 & 7.04& 1.18\\
|
|
%1.43 & 40.04 & 7.33& 1.20\\
|
|
%1.45 & 40.60 & 7.53& 1.22\\
|
|
%1.47 & 41.16 & 7.73& 1.23\\
|
|
%1.50 & 42.00 & 8.04& 1.26\\
|
|
%\bottomrule
|
|
%\end{tabular}
|
|
%\end{center}
|
|
%\caption{Muon beam scaling factors, energies and momenta.}
|
|
%\label{tab:mu_scales}
|
|
%\end{table}
|
|
|
|
% subsection muon_momentum_scanning (end)
|
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
% section detector_calibration (end)
|
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
\section{Data sets and statistics}
|
|
\label{sec:data_sets}
|
|
|
|
The main goal of this Run 2013 was to measure the rates and energy spectra of
|
|
protons following muon capture on aluminium. Also for normalisation and cross
|
|
checking against the existing experimental data, two types of measurements with
|
|
different targets were carried out for silicon targets:
|
|
\begin{itemize}
|
|
\item[(a)] an active, thick target similar to the set up
|
|
used by Sobottka and Wills~\cite{SobottkaWills.1968}. This provides
|
|
a cross-check against the existing experimental data. The silicon detector
|
|
package at the right hand side was moved to the target position with the
|
|
thick detector facing the muon beam in this set up.
|
|
\item[(b)] a passive, thin target and heavy charged particles were observed
|
|
by the two silicon packages. The measurement serves multiple purposes:
|
|
confirmation that the particle identification by dE/dx actually works,
|
|
separation of components of heavy charged particles emitted from the
|
|
silicon target.
|
|
\end{itemize}
|
|
|
|
As the emitted protons deposit a significant amount of energy in the target
|
|
material, thin targets and thus excellent momentum resolution of the low energy
|
|
muon beam are critical, aluminium targets of 50-\si{\micro\meter}\ and
|
|
100-\si{\micro\meter}\ thick were used. Although a beam with low momentum
|
|
spread of 1\% is preferable, it was used for only a small portion of the run
|
|
due to the low beam rate (see \cref{fig:Rates}). The beam momentum for each
|
|
target was chosen to maximise the number of stopped muons. The collected data
|
|
sets are shown in \cref{tb:stat}.
|
|
|
|
\begin{table}[btp!]
|
|
\begin{center}
|
|
\vspace{0.15cm}
|
|
\begin{tabular}{l c c c}
|
|
\toprule
|
|
\textbf{Target} &\textbf{Momentum} & \textbf{Run time} & \textbf{Number}\\
|
|
\textbf{and thickness}&\textbf{scaling factor} & \textbf{(h)} &\textbf{of muons}\\
|
|
\midrule
|
|
Si 1500 \si{\micro\meter}& 1.32& 3.07& $2.78\times 10^7$\\
|
|
& 1.30& 12.04& $2.89 \times 10^8$\\
|
|
& 1.10& 9.36& $1.37 \times 10^8$ \\
|
|
\midrule
|
|
Si 62 \si{\micro\meter} & 1.06& 10.29& $1.72 \times 10^8$\\
|
|
\midrule
|
|
Al 100 \si{\micro\meter}& 1.09& 14.37&$2.94 \times 10^8$\\
|
|
& 1.07& 2.56& $4.99 \times 10^7$\\
|
|
\midrule
|
|
Al 50 \si{\micro\meter} & 1.07& 51.94& $8.81 \times 10^8$\\
|
|
\bottomrule
|
|
\end{tabular}
|
|
\end{center}
|
|
\caption{Run statistics. Momentum scaling factors are normalised to
|
|
\SI{28}{\MeV\per\cc}.}
|
|
\label{tb:stat}
|
|
\end{table}
|
|
|
|
% section data_sets (end)
|
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
\section{Analysis framework}
|
|
\label{sec:analysis_framework}
|
|
\subsection{Concept}
|
|
\label{sub:concept}
|
|
Since the AlCapDAQ is a trigger-less system, it stored all waveforms of the
|
|
hits occured in 100-ms-long blocks without considering their physics
|
|
significance. The analysis code therefore must be able to extract parameters of
|
|
the waveforms, then organises the pulses into the physics events correlated to
|
|
stopped muons (\cref{fig:muon_event}). In addition, the analyser is
|
|
intended to be usable as a real-time component of a MIDAS DAQ, where simple
|
|
analysis could be done online for monitoring and diagnostic during the run.
|
|
|
|
\begin{figure}[btp]
|
|
\centering
|
|
\includegraphics[width=0.9\textwidth]{figs/muon_event.pdf}
|
|
\caption{Concept of the AlCap analysis code: pulses from individual detector
|
|
in blocks of time are analysed, then sorted centred around stopped muons.}
|
|
\label{fig:muon_event}
|
|
\end{figure}
|
|
|
|
The analysis framework of the AlCap consists of two separate programs.
|
|
A MIDAS-based analyser framework, \alcapana{}, processes the raw data and
|
|
passes its ROOT data output to the second
|
|
stage, \rootana{}, where most of the physics analysis is performed.
|
|
Both of the programs were designed to be modularised, which allowed us to develop
|
|
lightweight analysis modules that were used online to generate plots quickly,
|
|
while more sophisticated modules can be applied in offline analysis.
|
|
|
|
The DAQ system generated MIDAS files which stores the data as a stream of MIDAS
|
|
``banks''. In the AlCapDAQ, each bank corresponds to a single channel on
|
|
a digitizer and was named according to a predefined convention. The map between
|
|
detector channels and MIDAS bank names was stored in the MIDAS online database
|
|
(ODB), along with other settings such as sampling frequencies, timing offsets,
|
|
thresholds and calibration coefficients of each channel.
|
|
%These can then be
|
|
%accessed by both \alcapana{} and \rootana{} for either online or offline
|
|
%analysis.
|
|
|
|
The first step
|
|
of the analysis framework is to convert the raw MIDAS data into waveforms,
|
|
series of digitised samples continuous in time corresponding to pulses from the
|
|
detector. The waveform is called \tpulseisland{}s, which contain the bank name,
|
|
the ADC values of the samples and the time stamp of the first sample. This
|
|
conversion is performed in \alcapana{} and the resulting objects are stored in
|
|
a ROOT output file as a {\ttfamily TTree}.
|
|
|
|
The next step of the analysis is to obtain summary parameters of the pulses
|
|
from the digitized samples. The parameters of primary interest are the
|
|
amplitude and time of the peak and the integral of the pulse. This extraction
|
|
of parameters is done by a \rootana{} module, and the objects produced by this
|
|
stage are called \tanalysedpulse{}s. Currently, we have a usable and simple
|
|
algorithm that takes the pulse parameters from the peak of the waveform. In
|
|
parallel, a pulse finding and template fitting code is being developed because
|
|
it would provide more accurate pulse information. The first iteration of this
|
|
code has been completed and is being tested.
|
|
\begin{figure}[btp]
|
|
\centering
|
|
\includegraphics[width=0.85\textwidth]{figs/analysis_scheme}
|
|
\caption{Concept of the analysis framework in \rootana{}}
|
|
\label{fig:rootana_scheme}
|
|
\end{figure}
|
|
|
|
After obtaining pulse parameters for individual channel, the pairing up of
|
|
fast and slow pulses from the same physical detector needs to be done. This
|
|
entails looping through all fast and slow pulses from each detector,
|
|
checking for correlated pulses in time and amplitude, creating
|
|
{\ttfamily TDetectorPulse}s. The {\ttfamily TDetectorPulse}s allow better
|
|
understanding of the hits on the detector by combining timing information from
|
|
the fast channel and amplitude information from the slow channel. It also helps
|
|
reduce the impact of pile-up on the amplitude measurement, where the
|
|
improved time resolution of the fast channels can be used to separate the
|
|
overlapping amplitudes in the slow channels. The pulse pairing are applicable to
|
|
the silicon and germanium channels only. The scintillator channels provide only
|
|
fast timing signals which can be used as {\ttfamily TDetectorPulse}s directly.
|
|
|
|
The detector pulses are subsequently used to identify particles that hit the
|
|
detectors. These particle hits are still stored in the time-ordered tree
|
|
corresponds to the 110 ms block length from the AlCapDAQ. By iterating through
|
|
the tree to find stopped muons and taking any hits within a certain window
|
|
around this muon from every detector, a stopped-muon-centred tree shown in
|
|
\cref{fig:muon_event} can be produced. This will make it much easier to
|
|
look for coincidences and apply cuts, thereby bringing the end
|
|
goal of particle numbers and energy distributions.
|
|
|
|
% subsection concept (end)
|
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
|
|
\subsection{Online analyser}
|
|
\label{sub:online_analyser}
|
|
The online analyser was developed and proved to be very useful during the run.
|
|
A few basic modules were used to produce plots for diagnostic purposes
|
|
including: persistency view of waveforms, pulse height
|
|
spectra, timing correlations with respect to the upstream counters. The
|
|
modules and their purposes are listed in \cref{tab:online_modules}.
|
|
\begin{table}[btp]
|
|
\begin{center}
|
|
\begin{tabular}{l p{6cm}}
|
|
\toprule
|
|
\textbf{Module name} & \textbf{Functions}\\
|
|
\midrule
|
|
common/MUnCompressRawData & decompress raw MIDAS data\\
|
|
\midrule
|
|
FADC/MOctalFADCProcessRaw & \multirow{3}{6cm}{convert raw data to
|
|
{\ttfamily TPulseIsland}s}\\ v1724/MV1724ProcessRaw& \\
|
|
dt5720/MDT5720ProcessRaw&\\
|
|
\midrule
|
|
muSC\_muPC/MCaenCompProcessRaw& \multirow{4}{6cm}{decompress data from
|
|
{\ttfamily fe6}, make coincidence in upstream counters} \\
|
|
muSC\_muPC/MMuPC1AnalysisC&\\
|
|
muSC\_muPC/MMuPC1AnalysisMQL&\\
|
|
muSC\_muPC/MMuSCAnalysisMQL&\\
|
|
\midrule
|
|
diagnostics/MCommonOnlineDisplayPlots& produce plots of interest\\
|
|
\midrule
|
|
FADC/MOctalFADCBufferOverflow& \multirow{2}{6cm}{diagnostics for FADCs}\\
|
|
FADC/MOctalFADCPacketLoss&\\
|
|
\midrule
|
|
common/MExpectedIslands&\multirow{4}{6cm}{diagnostics in general}\\
|
|
common/MMuSCTimeDifferences&\\
|
|
common/MNumberIslands&\\
|
|
common/MPulseLengths&\\
|
|
\midrule
|
|
common/MTreeOutput& save {\ttfamily TPulseIsland}s tree\\
|
|
\bottomrule
|
|
\end{tabular}
|
|
\end{center}
|
|
\caption{Online analysis modules in the Run 2013.}
|
|
\label{tab:online_modules}
|
|
\end{table}
|
|
|
|
The \alcapana{} served the plots on port 9090 of the {\ttfamily abner}
|
|
via the ROOT socket protocol. We then used a ROOT-based program called
|
|
{\ttfamily online-display} to display the plots on the shift terminal
|
|
({\ttfamily alcap}). The {\ttfamily online-display} simply executed ROOT macros
|
|
which retrieved plots from the ROOT server, sorted then drew them in
|
|
groups such as upstream counters, silicon arms. It could also periodically
|
|
update the plots to reflect real-time status of the detector system.
|
|
%Screen
|
|
%shots of the {\ttfamily online-display} with several plots are shown in
|
|
%\cref{fig:online_display}.
|
|
|
|
%\hl{Screen shots}
|
|
\subsection{Offline analyser}
|
|
\label{sub:offline_analyser}
|
|
Some offline analysis modules have been developed during the beam time and could
|
|
provide quick feedback in confirming and guiding the decisions at the time. For
|
|
example, the X-ray spectrum analysis was done to confirm that we could observe
|
|
the muon capture process and to help in choosing optimal momenta which
|
|
maximised the number of stopped muons.
|
|
|
|
Although the offline analyser is still not fully available yet, several modules
|
|
are ready (\cref{tab:offline_modules}). An initial analysis is possible using
|
|
the existing modules thanks to the modularity of the analysis framework.
|
|
|
|
\begin{table}[htb]
|
|
\begin{center}
|
|
\begin{tabular}{l p{8cm}}
|
|
\toprule
|
|
\textbf{Module name} & \textbf{Functions}\\
|
|
\midrule
|
|
MakeAnalysedPulses & make a pulse with parameters extracted from
|
|
a waveform\\
|
|
MaxBinAPGenerator & simplest algorithm to get pulse information\\
|
|
TSimpleMuonEvent & sort pulses occur in a fixed time window around the
|
|
muon hits\\
|
|
ExportPulse \& PulseViewer & plot waveforms for diagnostics\\
|
|
PlotAmplitude & plot pulse height spectra\\
|
|
PlotAmpVsTdiff & plot pulse correlations in timing and amplitude\\
|
|
EvdE & plot \sdEdx histograms\\
|
|
\bottomrule
|
|
\end{tabular}
|
|
\end{center}
|
|
\caption{Available offline analysis modules.}
|
|
\label{tab:offline_modules}
|
|
\end{table}
|
|
|
|
The MakeAnalysedPulses module takes a raw waveform, calculates the pedestal
|
|
from a predefined number of first samples, subtracts this pedestal taking
|
|
pulse polarity into account, then calls another module to extract pulse
|
|
parameters. At the moment, the simplest module, so-called MaxBinAPGenerator,
|
|
for pulse information calculation is in use. The module looks for the
|
|
sample that has the maximal deviation from the baseline, takes the deviation as
|
|
pulse amplitude and the time stamp of the sample as pulse time. The procedure
|
|
is illustrated on \cref{fig:tap_maxbin_algo}. This module could not handle
|
|
pile-up or double pulses in one \tpulseisland{} in \cref{fig:tap_maxbin_bad}.
|
|
\begin{figure}[htb]
|
|
\centering
|
|
\includegraphics[width=0.85\textwidth]{figs/tap_maxbin_algo}
|
|
\caption{Pulse parameters extraction with MaxBinAPGenerator.}
|
|
\label{fig:tap_maxbin_algo}
|
|
\end{figure}
|
|
\begin{figure}[htb]
|
|
\centering
|
|
\includegraphics[width=0.47\textwidth]{figs/tap_maxbin_bad}
|
|
\includegraphics[width=0.47\textwidth]{figs/tap_maxbin_bad2}
|
|
\caption{Double pulse and pile up are taken as one single pulse by the
|
|
MaxBinAPGenerator}
|
|
\label{fig:tap_maxbin_bad}
|
|
\end{figure}
|
|
|
|
The TSimpleMuonEvent first picks a muon candidate, then loops through all
|
|
pulses on all detector channels, and picks all pulses occur in
|
|
a time window of \SI{\pm 10}{\si{\us}} around each candidate to build
|
|
a muon event. A muon candidate is a hit on the upstream plastic scintillator
|
|
with an amplitude higher than a threshold which was chosen to reject MIPs. The
|
|
period of \SI{10}{\si{\us}} is long enough compared to the mean life time of
|
|
muons in the target materials
|
|
(\SI{0.758}{\si{\us}} for silicon, and \SI{0.864}{\si{\us}}
|
|
for aluminium~\cite{SuzukiMeasday.etal.1987}) so practically all of emitted
|
|
charged particles would be recorded in this time window.
|
|
%\begin{figure}[htb]
|
|
%\centering
|
|
%\includegraphics[width=0.85\textwidth]{figs/tme_musc_threshold}
|
|
%\caption{Pulse height spectrum of the $\mu$Sc scintillator}
|
|
%\label{fig:tme_musc_threshold}
|
|
%\end{figure}
|
|
|
|
A pile-up protection mechanism is employed to reject multiple muons events: if
|
|
there exists another muon hit in less than \SI{15}{\us} from the
|
|
candidate then both the candidate and the other muon are discarded. This
|
|
pile-up protection would cut out less than 11\% total number of events because
|
|
the beam rate was generally less than \SI{8}{\kilo\hertz}.
|
|
|
|
%In runs with active silicon targets, another requirement is applied for the
|
|
%candidate: a prompt hit on the target in $\pm 200$ \si{\ns}\ around the
|
|
%time of the $\mu$Sc pulse. The number comes from the observation of the
|
|
%time correlation between hits on the target and the $\mu$Sc
|
|
%(\cref{fig:tme_sir_prompt_rational}).
|
|
%\begin{figure}[htb]
|
|
%\centering
|
|
%\includegraphics[width=0.85\textwidth]{figs/tme_sir_prompt_rational}
|
|
%\caption{Correlation in time between SiR2 hit and muon hit}
|
|
%\label{fig:tme_sir_prompt_rational}
|
|
%\end{figure}
|
|
|
|
To make sure that we will analyse good data, a low level data quality checking
|
|
was done on the whole data sets. The idea is to plot the variations of basic
|
|
parameters, such as noise level, length of raw waveforms, pulse rate, time
|
|
correlation to hits on the muon counter on each channel during the data
|
|
collecting period. Runs with significant difference from the averaging
|
|
values were further checked for possible causes, and would be discarded if such
|
|
discrepancy was too large or unaccounted for. Examples of such trend plots are
|
|
shown in \cref{fig:lldq}.
|
|
\begin{figure}[htb]
|
|
\centering
|
|
\includegraphics[width=0.47\textwidth]{figs/lldq_noise}
|
|
\includegraphics[width=0.47\textwidth]{figs/lldq_tdiff}
|
|
\caption{Example trend plots used in the low level data quality checking:
|
|
noise level in FWHM (left) and time correlation with muon hits (right). The
|
|
noise level was basically stable in in this data set, except for one
|
|
channel. On the right hand side, this sanity check helped find out the
|
|
sampling frequency was wrongly applied in the first tranche of the data
|
|
set.}
|
|
\label{fig:lldq}
|
|
\end{figure}
|
|
% subsection offline_analyser (end)
|
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
\section{Monte Carlo simulation}
|
|
\label{sec:monte_carlo_simulation}
|
|
|
|
A full Monte Carlo (MC) simulation of the experimental set up has been developed
|
|
based on Geant4~\cite{Agostinelli.etal.2003}. The geometrical implementation
|
|
was detailed as much as possible and could be modified via configuration
|
|
scripts at run time. Descriptions of the muon beam came from the beam line optic
|
|
calculation provided by the accelerator experts at PSI.
|
|
|
|
The MC model greatly assisted the design of the experiment, such as alignment
|
|
of the detectors with respect to the target, and shielding of scattered muons.
|
|
It also helped make a sense of the observed results during the run and data
|
|
analysing.
|
|
|
|
% chapter the_alcap_run_2013 (end)
|
|
|