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thesis/chapters/chap5_alcap_setup.tex
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@@ -2,9 +2,8 @@
\label{cha:the_alcap_run_2013}
\thispagestyle{empty}
The first run of the AlCap experiment was performed at the $\pi$E1 beam line
area, PSI from November 26 to December 23,
2013. The goal of the run was to measure protons rate and spectrum following
muon capture on aluminium.
area, PSI from November 26 to December 23, 2013. The goal of the run was to
measure protons rate and their spectrum following muon capture on aluminium.
\section{Experimental set up}
\label{sec:experimental_set_up}
@@ -56,7 +55,7 @@ One of the main requirements of the AlCap experiment was a low energy muon beam
with narrow momentum bite in order to achieve a high fraction of stopping muons
in the very thin targets. In this Run 2013, muons from
\SIrange{28}{45}{\mega\electronvolt\per\cc} and momentum spread of 1\% and
3\%were used.
3\%, respectively, were used.
For part of the experiment the target was replaced with one of the silicon
detector packages allowed an accurate momentum and range calibration
@@ -84,8 +83,9 @@ as a function of momentum for two different momentum bites.
The targets and charged particle detectors are installed inside the vacuum
chamber as shown in \cref{fig:alcap_setup_detailed}. The muon beam enters
from the right of the image and hits the target, which is placed at the
centre of the vacuum chamber and orientated at 45 degrees to the beam axis.
from the right of \cref{fig:alcap_setup_detailed} and hits the target, which is
placed at the centre of the vacuum chamber and orientated at 45 degrees to the
beam axis.
The side walls and bottom flange of the vessel provide several
vacuum-feedthroughs for the high voltage and signal cables for the silicon and
scintillator detectors inside the chamber.
@@ -207,7 +207,7 @@ proportional chamber (\Pmu{}PC) that uses 24 X wires and 24 Y wires at
2~\si{\milli\meter}~intervals.
The upstream detectors provide signal of an incoming muon as coincident hits on
the muon trigger and the wire chamber in anti-coincident with the muon
the muon trigger and the wire chamber in anti-coincidence with the muon
anti-coincidence counter.
This set of detectors along with their read-out system
belong to the MuSun experiment, which operated at the same beam line just
@@ -326,7 +326,7 @@ lead to the use of several sampling frequencies from 17~\si{\mega\hertz}\ to
250~\si{\mega\hertz}, and three types of digitisers were employed:
\begin{itemize}
\item custom-built 12-bit 170-MHz FADCs which was designed for the
MuCap experiment. Each FADC board has dimensions the same as those of
MuCap experiment. Each FADC board has the same dimensions as those of
a single-width 6U VME module, but is hosted in a custom built crate due to
its different power supply mechanical structure. The FADC communicates with
a host computer through a 100-Mb/s Ethernet interface using a simple
@@ -367,7 +367,7 @@ model V767 which was kindly provided by the MuSun experiment.
The Data Acquisition System (DAQ) of the AlCap experiment, so-called AlCapDAQ,
provided the readout of front-end electronics, event assembling, data logging,
hardware monitoring and control, and the run database of the experiment
(\cref{fig:alcapdaq_pcs}). It was based on MIDAS framework~\footnote{
(\cref{fig:alcapdaq_pcs}). It was based on the MIDAS framework~\footnote{
MIDAS is a general purpose DAQ software system developed at PSI and TRIUMF:\\
\url{http://midas.triumf.ca}} and consisted of two circuits, {\em i})
a detector circuit for synchronous data readout from the front-end electronics
@@ -411,7 +411,7 @@ rollover on any digitiser (a FADC runs at its maximum speed of
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 starts a new run with the same parameters after about 6 seconds.
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.
@@ -435,11 +435,12 @@ run, by:
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 and a tail pulse generator, A tail pulse with amplitude of
\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;
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
\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.
@@ -453,6 +454,10 @@ run, by:
\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}.
@@ -472,6 +477,11 @@ The calibration coefficients for the silicon channels are listed in
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}
@@ -534,13 +544,14 @@ Following corrections for the peak areas are considered:
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.
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 dead time.
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 count under the two
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}
@@ -568,7 +579,7 @@ an exponential background gives the actual reset pulse length of
$1947.34\times 10^{-6} \times 2335.0 = 4.55$ \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 so correction for amplifier resets is not applied.
uncertainty of peak areas.
\begin{figure}[htb]
\centering
@@ -590,8 +601,12 @@ 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. As shown in \cref{fig:ge_eff_cal}, the
differences are in line with the uncertainties of the measured efficiencies.
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
@@ -599,9 +614,12 @@ differences are in line with the uncertainties of the measured efficiencies.
\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, the fit was done with
7 energy points from 244~keV, the shaded area is
95\% confidence interval of the fit.}
\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}
@@ -770,8 +788,8 @@ sets are shown in \cref{tb:stat}.
\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 physics events correlated to
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.
@@ -786,9 +804,9 @@ analysis could be done online for monitoring and diagnostic during the run.
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 a second
passes its ROOT data output to the second
stage, \rootana{}, where most of the physics analysis is performed.
Both programs were designed to be modularised, which allowed us to develop
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.
@@ -908,14 +926,14 @@ update the plots to reflect real-time status of the detector system.
%\hl{Screen shots}
\subsection{Offline analyser}
\label{sub:offline_analyser}
Some offline analysis modules has been developed during the beam time and could
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
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]
@@ -1000,7 +1018,7 @@ the beam rate was generally less than \SI{8}{\kilo\hertz}.
%\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 plotting the variations of basic
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
@@ -1026,13 +1044,13 @@ shown in \cref{fig:lldq}.
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 as detailed as possible and could be modified via configuration script at
run time. Descriptions of the muon beam came from the beam line optic
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 helps make sense of observed results during the run and data
It also helped make a sense of the observed results during the run and data
analysing.
% chapter the_alcap_run_2013 (end)