Component Characterization and Simulations of Light Collection Efficiency
Component Characterization and
Simulations of Light Collection Efficiency
For the Aerogel Kaon Cherenkov Detector for JLab Hall C
Laura Rothgeb
Catholic University of America
Advisor: Dr. Tanja Horn
Abstract: The purpose of this project is to build a Silica Aerogel Cherenkov detector
capable of identifying kaon particles. This detector will be installed in Hall C of the Jefferson
National Accelerator Facility (JLab). The detector is designed to detect particles moving
with momenta ranging from 2 GeV to 8 GeV. At this stage in the project it is necessary to
test the various components that will be used in the detector. For example, the voltages for
the PMTs will be calibrated and the gain of each PMT tested. A proper ratio for the mixing
of the glue used to attach the PMTs to the scintillators used for testing must be found.
Finally, a modified Monte Carlo simulation will be employed to simulate the behavior of the
experimental setups and study the effect of light guides on the efficiency of the detector.
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Component Characterization and Simulations of Light Collection Efficiency
1. INTRODUCTION
Quantum chromo-dynamics (QCD) is the theory of the strong force. It describes how
quarks interact and build larger sub-atomic particles. In order to understand the strong
force and QCD it is important to have a clear picture of the structure of nucleons such as the
proton. Generalized Parton Distributions (GPDs) describes the placements, movements and
momenta the quarks inside a nucleon. The GPD is expressed in terms of x, a fraction of the
momentum of the quarks over the momentum of the proton, an illustration of which can be
found in Figure 1.
Figure 1: Generalized Parton Distributionsi
Understanding the GPD of the proton is the key to understanding the strong force
and how quarks, and larger particles, bond together. However, it is incredibly difficult to
study the GPD of a nucleon such as the proton. In order to do this it is necessary to study
the meson particles, such as kaons, that are produced in hard electron scattering
experiments with the proton. Figure 2 shows an illustration of this process. These
experiments allow for the determination of the form factor (a static picture of charge
distribution, density and internal structure of a particle), which enables us to learn more
about the proton prior to the reaction.
Figure 2: Meson Electroproduction
In order for the data from such experiments to be used to model the GPD of the
proton, however, it must match the hard model of QCD scattering. As shown in Figure 3,
the current model projections do not predict a favorable kaon form factor.
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Component Characterization and Simulations of Light Collection Efficiency
FIGURE 3: MESON FORM FACTORSii
However, because there is no direct experimental data for the kaon form factor
beyond a resolution of Q2=1 GeV2, it is vital to calculate the actual kaon form factor to
determine if the model itself is correct. In order to study kaons and gather this data, there
must be a device capable of detecting the kaons resulting from the hard electron scattering.
2. BACKGROUND
The nuclear physics group at the Catholic University of America is building an
aerogel Cherenkov detector to detect kaons. This detector works by detecting particles that
pass through the aerogel faster than light moves through that same material. When this
happens, a process called Cherenkov radiation takes place, in which light is emitted by the
aerogel in a manner similar to a sonic boom. An index of refraction for the aerogel of 1.03
has been chosen that give the strongest signal for kaons at momenta ranging from 2-8
GeViii. The light from is then collected by the PMTs along the sides of the detector, where it
is converted to an electric signal via the photoelectric effect.
In order to build this detector, several stages must be completed. The design must
be modeled and optimized, prototypes are to be built and components must be tested. In
this document I will discuss my contribution to this stage of the process in the areas of
component characterization and evaluation, as well as experimental simulations, focusing
on a study of light collection efficiency.
3. COMPONENT TESTING
3.1 PMT Testing and Procedure
Component testing began with the construction of several simple cosmic muon
detectors. These detectors consisted of plastic scintillator material, measuring
approximately 1”x6”, attached to 2” diameter Phillips Scientific model XP226/B PMTs using
electrical tape and Styrofoam stabilizers. The scintillator pieces were cut and sanded using
320, 600 and 800 grit sandpaper and aluminum oxide powder to ensure a smooth surface
for ideal scintillation. The bases used for the PMTs had been previously verified by
Nathaniel Hlavin using an LED test set up with a constant PMT for strong signal output.iv
Each PMT was assigned a specific base for consistency during the testing. These detectors
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Component Characterization and Simulations of Light Collection Efficiency
were then placed in a dark box and connected to the Power Designs Pacific high voltage
regulated DC power supply. The signal from the PMT was relayed to a Phillips Scientific
710 discriminator, which determined whether the signal is within the predetermined
threshold of 15 mV. If so, the signal was then sent to an Ortec 994 Dual Counter/Timer
module, which counts the number of muon events during a certain timeframe.
A series of double-coincidence level runs were also performed, in which two
detectors were set up parallel to one another. The signals from both PMTs were sent from
the discriminator through a Phillips Scientific 754 Quad Four-Fold logic unit that
determined whether both signals had been produced by the same muon passing through
both scintillators. These coincidence events were then counted by the Ortec counting
module.
For both the single coincidence and the double coincidence runs, counts ranging
from 10 minutes to one hour in duration were run on voltages ranging from 1500V to
2200V. By counting the number of muons detected and comparing that to the accepted
cosmic muon rate, we were able to determine the quality of the PMTs used. The voltages of
each PMT were calibrated by finding where the number of muon events leveled out,
representing the ideal cut-off range for the voltage of that PMT. These tests allowed us to
determine experimental procedures and troubleshoot equipment errors before testing the
components that will be used in the actual kaon detector.
3.2 Results: PMT Individual Calibration
Using one 2” diameter Phillips Scientific PMT with a 1”x6” plastic scintillator, we
performed four 10-minute runs over a range of voltages from 2000 to 2200 volts. Figure 4
summarizes our results. No plateau was observed, but one can see that the rate increases
above an applied high voltage of 2100 V. This suggests that the optimal operating high
voltage may be within the range we tested. While further tests over a wider range are
needed to determine a more accurate result, we are able to use the present results to
proceed with the development of additional detector component testing procedures.
FIGURE 4: EXAMPLE OF SMALL-SCALE PMT VOLTAGE CALIBRATION
Voltage vs. Counts (Muons)
700
600
Counts
500
400
300
Series1
200
100
0
2000
2050
2100
2150
2200
Voltage (V)
3.3 GLUE RATIOS
In order to refine the PMT-scintillator testing procedure for later detector and
component testing, we used Sylguard 184 Silicone Elastomer glue to attach the scintillators
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Component Characterization and Simulations of Light Collection Efficiency
to the PMT window. This glue, comprised of a base and a curing agent, forms a secure bond
between the PMT window and the scintillator panel, eliminating the need for the bulky
electrical tape and Styrofoam connections used previously, as described in section 2.1.
However, because the suggested ratio of 10:1, base to curing agent, produced a glue
mixture that was overly brittle, a proper ratio of the two components of the glue needed to
be determined. It was important to find a ratio that yielded glue that was both strong
without being brittle, and that did not decrease the efficiency of the PMT. Several
combinations were tested. The ratio that made the most stable glue was 7.5:1, base to
curing agent.
4. EXPERIMENTAL SIMULATIONS
The Monte Carlo Fortran simulation SimCherenkov, originally written by Douglas
Higinbotham, has been used to model the kaon aerogel Cherenkov detector.v SimCherenkov
calculates the total number of photoelectrons produced by the PMT. It does this by
calculating the number of photons emitted in the Cherenkov radiation process, then
tracking each of those photons as they move through the detector, repeating this process in
an iterative Monte Carlo loop. This simulation has been used to optimize the conceptual
design characteristics of the detector, including the size, index of refraction and placement
of the aerogel, as well as the geometry of the light box and the number and placement of
the PMTs.
The SimCherenkov program has been modified further to model a small-scale
cosmic ray detector that was built at Jefferson Lab to study the effect of light guides on the
efficiency of light collection in aerogel detectors like the kaon aerogel Cherenkov detector.
The comic muon detector used for this study was designed by Kevin R. Wood, a student in
our collaboration from University of South Carolina, under the mentorship of Dr. Yordanka
Ilieva. This experimental set-up, as shown in Figure 5, consists of three main boxes and one
5” diameter PMT. The aerogel is positioned in a chamber directly over a Millipore-lined
light diffusion box. Attached to the diffusion box, at a right angle to the aerogel chamber, is
an extension box lined with Mylar. This extension creates a large, asymmetrical light guide
between the diffusion box and the PMT. The signals received from the PMT during cosmic
ray testing were very weak and hard to discriminate, suggesting that the geometry of the
detector was affecting the efficiency of the light collection.
Figure 5: Experimental Set-up at Jefferson Lab for Cosmic Ray Detection
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Component Characterization and Simulations of Light Collection Efficiency
We thus investigated the effect of the efficiency of the light collection using a
simulation to model the detector to determine how the addition of the light guide was
affecting the efficiency and to verify the empirical findings from the experimental set-up.
SimCherenkov was already coded to model a detector in which the PMT is at a right angle
to the diffusion box using the layout called ONESIDE. The main modification was the
addition of the extension box, the geometry of which could be changed to better study the
effects of light guides. In the following sections we will describe details of this simulation
and the study of the light guide efficiency.
4.1 Building a New Simulation Configuration: EXTENSION
In order to model the addition of the extension volume, it was necessary to write a new
configuration option. This option allows the user to choose the height, length and width of the
extension box, in addition to the other characteristics and parameters of the detector. New
variables were created to model the walls of the extension box and track the movement of the
photons within that volume. This was achieved by the creation of a nested If statement block
within the section of code that determines which walls each of the photons collides with,
allowing for the photon to pass into the extension volume.
Additionally, the difference in the reflective surfaces of the diffusion box and the
extension volume had to be taken into account. This was achieved by introducing a variable that
allowed the reflectivity index of the extension box to be varied by the user. Millipore, with a
reflectivity of 96% (the lining of the diffusion box) is more diffusely reflective than Mylar (the
lining of the extension box), which has a reflectivity of 94%. This modification to the code
allowed us to more accurately track the number of photons that were absorbed in each of the
chambers.
4.2 Light Guide Simulation Study
To study the efficiency of the light collection of light guides in an aerogel detector, we
used the modified version of SimCherenkov with the EXTENSION configuration. We tested a
range of widths, lengths and heights of the extension box to simulate light guides of different
geometries. For each run we held the other two dimensions of the extension box constant at
11.6cm, the actual dimensions of the experimental set-up. The light diffusion box measured
8.8cmx8.8cmx8.8cm. One 5” diameter PMT and one 8.8cmx8.8cm, 1cm thick panel of new
Aerogel were also used in all of the simulations.
4.2.1 Results: Light Guide Width
The ideal width of the extension box (distance from the diffusion box to the PMT
window) was 0cm. An extension box measuring 0cm wide produced the same number of
photoelectrons as the detector without the extension volume, as modeled by the
ONESIDE configuration. As the width increased the number of photoelectrons decreased
rapidly in a negative exponential manner. At 11.6cm wide, the extension box on the
experimental set-up at JLab is only 23% efficient. This study shows, and was empirically
verified by Kevin Wood using the experimental set-up at JLab, that light guides
dramatically reduce the efficiency of aerogel detectors.
Figure 6 below shows the efficiency curve of the width of the extension volume.
The red point marks the maximum efficiency, and the width of the extension of the
experimental set-up is denoted by the green point.
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Component Characterization and Simulations of Light Collection Efficiency
Figure 6: Distance vs. Photoelectrons
# of Photoelectrons
1.4
1.2
1
0.8
0.6
0.4
0.2
0
0
5
10
15
EXTENDW (cm)
20
25
30
4.2.2 Results: Light Guide Length and Height
It was found that as the values of the length and height of the extension box
increased, the number of photoelectrons increased until the entire window of the PMT
plus the rim of the PMT casing was exposed to the extension box, at which point the
efficiency decreased linearly. The ideal length of the extension box for a detector with a
5” diameter PMT is 12cm and the ideal height is 14cm. Because the actual dimensions of
the experimental set-up at JLab are so close to these values, little detector efficiency is
lost due to the length and width of the extension volume.
# of Photoelectrons
Figure 7: Length vs. Photoelectrons
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0
5
10
15
20
25
EXTENDL (cm)
30
35
40
# of Photoelectrons
Figure 8: Height vs. Photoelectrons
0.4
0.3
0.2
0.1
0
0
5
10
15
20
25
EXTENDH (cm)
7
30
35
40
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Component Characterization and Simulations of Light Collection Efficiency
4.2.3 Results: Loss of Photons in Detector
We also tracked where and how the individual photons were absorbed or
otherwise terminated. The majority of the lost photons were absorbed in the Mylar lining
of the extension box. With the geometry set to the dimensions of the experimental
detector, 37% of the total photons emitted as Cherenkov radiation are lost in the
extension box. This is due to both the increased surface area over which the photons are
likely to be absorbed and the less diffusely reflective material lining the extension box.
The high percentage of lost photons within the extension volume supports the finding that
large light guides are detrimental to the efficiency of the light collection system and the
total efficiency of the detector as a whole. Figure 9 illustrates the distribution of photons
lost in the detector.
FIGURE 9: PHOTONS LOST IN DETECTOR
5. SUMMARY AND OUTLOOK
In conclusion, by writing a new configuration for the FORTRAN simulation program
SimCherenkov to model the experimental cosmic muon detector built by Kevin Wood at
Jefferson Lab, we were able to study the efficiency of light guides on aerogel detectors. We were
able to determine, by using the EXTEND configuration, that with an 11.6cm extension cube the
experimental set-up at Jefferson Lab is only 23% efficient. It was concluded that light guides
have a highly detrimental effect on the efficiency of this detector. These findings were confirmed
empirically, as the detector produced only a very weak photoelectric signal. Also determined
were procedural methods for component testing by performing cosmic ray tests using 2”
diameter PMTs and plastic scintillators, and the proper ratio of base to curing agent to produce a
strong glue mixture for further PMT testing with scintillators.
Additionally, we plan to implement a GEANT4vi simulation called GEMCvii, authored by Dr.
Maurizio Ungaro of Jefferson Lab to simulate the kaon aerogel Cherenkov detector. This
detailed program will allow us to model the detector using real-world environment, and will
provide an animated simulation of the particles moving through the detector’s components. This
simulation has yet to be fully written and, as such, results are pending.
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Component Characterization and Simulations of Light Collection Efficiency
Acknowledgements: The author would like to thank Dr. Tanja Horn for her mentorship and
support throughout the research and experimentation process, and The Catholic University of
America for providing the opportunity for this research.
References:
i
T. Horn et al., Proposal to JLab PAC 34, Studies of L-T separated Kaon Electroproduction at
5-11 GeV, December 15, 2008
ii
T. Horn et al., Phys. Rev. Lett. 97 (2006) 192001.; T. Horn et al., arXiv:0707.1794 (2007). ;
A.P. Bakulev et al, Phys. Rev. D70 (2004)]
iii
N. Hlavin, Computational Design Optimizations for Aerogel Kaon Cherenkov Detector for
JLab Hall C., August 2010
iv
Studies by Nathaniel Hlavin, Catholic University of America Nuclear Physics Group, 2011
v
Dr. Douglas H. Higinbotham, Program SimCherenkov 3.0, Jefferson Lab 2001
vi
CERN, European Organization for Nuclear Research, GEANT4, 2006
vii Dr. Maurizio Ungaro, GEMC: GEant4 Monte-Carlo, Jefferson Lab 2011
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