INITIAL PERFORMANCE STUDIES OF THE FORWARD GEM TRACKER
A THESIS
SUBMITTED TO THE GRADUATE SCHOOL
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE
MASTER OF SCIENCE
BY
MALORIE R. STOWE
DR. DAVID GROSNICK
BALL STATE UNIVERSITY
MUNCIE, INDIANA
DECEMBER 2012
Table of Contents
List of Figures
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List of Tables
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1
Abstract
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Chapter I
Introduction
Chapter II
Detector
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Chapter III
Data Analysis .
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III.A Cosmic Ray Data: High Voltage Off
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III.B Cosmic Ray Data: High Voltage On
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III.C STAR Data.
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Chapter IV
Conclusions
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Appendix A
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Acknowledgements
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References
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List of Figures
Figure 1
Feynman diagram showing the interaction between quarks
and antiquarks creating W bosons .
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Figure 2
The facilities of Brookhaven National Laboratory
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Figure 3
The STAR Detector
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Figure 4
Gem foil hole pattern .
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Figure 5
Gem foil holes and electric field lines
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Figure 6
Identification format of the disks and quadrants of the FGT .
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Figure 7
Example of quadrant strips. .
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Figure 8
The first disk of the FGT labeled with quadrant names,
FEE assemblies, and APVs
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Figure 9
R and φ strip locations read by a single APV .
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Figure 10
Cosmic-Ray Test Setup
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Figure 11
Pedestal histogram of channel number 048, time bin 02,
and APV 02 with Gaussian fit .
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Total ADC distribution of the Gaussian fit-means for all
combined channels, time bins, and APVs
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Figure 13
Distribution of Gaussian fit-mean per time bin
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Figure 14
Average of Gaussian fit-mean distribution per time bin
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Figure 15
Difference in average pedestal fit-mean values across the
time bins for different channels in APV02. .
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Fit-means from time bin 00 subtracted from time bin 04
as a function of channel number.
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Figure 12
Figure 16
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Figure 17
Pedestal fit-mean values for time bin 05 subtracted from time
bin 04 fit-means as a function of channel number .
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Figure 18
Pedestal fit-mean distribution per APV
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Figure 19
The mean of APV distribution as a function of APV .
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Figure 20
Total pedestal fit-sigma distribution .
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Figure 21
Fit-sigma distribution per time bin
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Figure 22
Mean of pedestal fit-sigma distribution for each time bin .
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Figure 23
Fit-sigma distribution as a function of APV .
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Figure 24
Mean from fit-sigma distributions per APV as a function of
APV number .
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Figure 25
Examples of poor Gaussian fits to the pedestal
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Figure 26
Pedestal width ADC distribution after common mode
noise subtraction
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Raw ADC spectrum of 128 channels from APV01 and
time bin04
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Figure 28
APV channel number as a function of ADC channel .
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Figure 29
Histogram of ADC values for time bin 04 and APV 01
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Figure 30
APV channel number as a function of ADC channel .
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Figure 31
Histogram of ADC data with the six-sigma cut applied
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Figure 32
Ratio of the signal to total entries as a function of the
location on the ADC pedestal cut
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Figure 33
Mean from pedestal APV fit-mean distribution
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Figure 34
Fit-mean distribution for time bin 04 .
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Figure 35
Fit-sigma distribution for time bin 04 .
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Figure 27
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Figure 36
ADC channel as a function of time bin
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Figure 37
Difference in pedestal means as a function of channel
number in APV02
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Difference in pedestal means as a function of APV channel
number for APV02 .
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Figure 39
Pedestal fit-mean as a function of electronic ID
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Figure 40
Pedestal fit-sigma as a function of electronic ID
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Figure 41
Map of R and φ strips for APV00
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Figure 42
Pedestal fit-means and fit-sigmas as a function of
strip length in the phi plane for APV00
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Pedestal fit-means and fit-sigmas as a function of
strip length in the R plane for APV 00.
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ADC distribution showing a typical pedestal for
channel 095, time bin 01, and APV 03
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Figure 38
Figure 43
Figure 44
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Figure 45
ADC distributions of “bad” pedestals considered “good”
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Figure 46
ADC distribution showing the pedestal for channel 057,
time bin 02, and APV23
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Frequency plot of the ratio of RMS to the mean of
the histogram .
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Figure 48
Pedestal fit-means as a function of time
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Figure 49
Pedestal fit-sigmas as a function of time
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Figure 50
Pedestal fit-mean as a function of voltage added to
nominal high voltage .
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Mean (of the histogram) of the fit-mean distribution per
time bin and per APV as a function of voltage added to
nominal high voltage .
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Figure 47
Figure 51
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Figure 52
Figure 53
Figure 54
Figure 55
Figure 56
Pedestal fit-sigma as a function of voltage added to
nominal high voltage .
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Mean of fit-sigma distribution per time bin and per
APV as a function of voltage added to nominal
high voltage .
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Average of the mean of the histogram from the fit-sigma
distribution per APV as a function of voltage added to
nominal high voltage
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Frequency plot of 70:30 gas mixture pedestal fit-means
divided by 90:10 gas mixture pedestal fit-means
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Frequency plot of 70:30 gas mixture pedestal fit-sigma
divided by 90:10 gas mixture pedestal fit-sigma
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vi
List of Tables
Table I
Average and standard deviation for the pedestal fit-mean values
of the time bins subtracted from pedestal fit-means of time bin 04
for all channels of APV02.
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Table II
Failure States for pedestals
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Table III
Failure rates for the pedestals
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Table IV
Nominal high voltage values per quadrant
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Table A.I
Cosmic-ray test data .
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Table A.II
STAR data
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Table A.III
Pedestal study in time.
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Table A.IV
Pedestal study with change in high voltage .
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Table A.V
Pedestal study with change in gas mixture .
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vii
Chapter I
Introduction
The proton is a subatomic particle, comprised of gluons, sea quarks, and three
valence quarks. The proton is known to have a fundamental property called spin, with
the spin of a proton measured to be ½ћ. It is natural to expect that the spin of the three
valence quarks would make up the spin of the proton, but measurements made in deepinelastic scattering (DIS) experiments have shown that these quarks only supply about
30% of the total spin of the proton [1]. This discovery led to what is known as the
proton “spin crisis,” and the need to find out what constituents are responsible for the
remaining amount of spin. The rest of the proton spin is thought to be produced by
several other constituents, including the sea quarks and antiquarks, gluons, and the
orbital angular momentum of all these potential contributors.
To investigate the contribution of these other constituents to the spin of the
proton, experiments are conducted at the Relativistic Heavy Ion Collider (RHIC) at
Brookhaven National Laboratory. RHIC has the ability to produce, accelerate, and
collide polarized-proton beams at energies of 500 GeV in the center of mass. It has
been the goal of the RHIC spin physics program to measure the contribution of gluons
and various sea quarks to the spin of the proton. This goal may be accomplished by
1
using large particle detectors, such as the Solenoidal Tracker at RHIC (STAR) to study
collisions of polarized protons. The resulting particles created in the collisions provide a
probe into the proton to investigate each of the possible spin contributors [2]. For
example, measuring the asymmetry, which is the difference between the numbers of
particles in two different spin states divided by the sum of the number of particles in the
two different spin states, of direct photons produced in polarized proton collisions will
provide information to calculate the gluon contribution to the spin.
The Forward GEM Tracker (FGT) is a detector that will be used to help determine
the spin contribution of the sea quarks by measuring the asymmetry of the production
of W bosons from collisions at 500 GeV center of mass. Specifically, the FGT will
improve previous tracking capabilities of leptons from W boson decays in the STAR
detector. The FGT operates by using gas electron multiplication (GEM) technology.
Charged particles (e.g. leptons) ionize the material they traverse and the liberated
electrons from this process are multiplied during collisions with gas-mixture atoms
within a given electric field. All of these electrons produce a pulse on two planes of
strips, providing two-dimensional information on the “hit” position of the charged
particles. Six sets of these planes (disks) are located at distances from the intersection
region. Combining hits in each disk allows the track of a lepton to be reconstructed.
The FGT is a newly-constructed detector in STAR and therefore its initial performance
needs to be studied in great detail.
The FGT will be instrumental in observing the decay leptons from W bosons,
created by the interaction of the quark of one proton and the sea antiquark of another
2
in a proton-proton collision with a center of mass (CM) energy of 500 GeV. This high CM
energy is needed to create W bosons, which have a mass around 80 GeV. Figure 1
shows that the W boson formed during the collision depends on the quark/antiquark
interaction of the colliding protons. If a valence down quark of one proton interacts in a
-
+
collision with an up antiquark of another proton, it can produce a W . A W is created
when a valence up quark of a proton interacts with a down antiquark of another proton.
These W bosons survive for only a fraction of a second until they decay into a lepton and
-
a neutrino (about 30% of the time). A W decays to an electron and an antineutrino,
+
where a W decays to a positron and a neutrino [3]. Neutrinos are very rarely detected,
so a signature in the detector for a W boson is a single, isolated lepton with an energy of
one-half of the W boson mass in its CM frame. The other one-half of undetected
“missing mass” of energy is carried off by the neutrino at 180o from the lepton in the
CM of the W boson. The lepton energy is measured by calorimeters. The sign of the
lepton can be recognized by the bend of its trajectory in the magnetic field of the STAR
Fig. 1. Feynman diagrams showing the interaction between quarks and
antiquarks creating W bosons.
3
detector. By knowing the sign of the lepton’s charge, the W boson produced in the
collision can be identified and then, ultimately which quark/antiquark interaction
occurred (see Fig. 1) [4]. The asymmetry in the production of the W bosons from
polarized-proton collisions can be measured, and from that, the spin contribution from
the sea quarks can be calculated.
The FGT is one part of a tracking upgrade for the STAR detector. Before the
installation of the FGT, tracking (finding the trajectory of charged particles) was done
primarily by the Time Projection Chamber (TPC) [5], which covers an angular range of
, where η (in units of pseudorapidity) is the angle measured from the vertical
axis, perpendicular to the beam line at the collision point, towards the incoming beam
direction. As the angle η increases, the tracking capabilities of the TPC decrease due to
a decrease in tracking volume (discussed in Chapter II). The installation of the FGT
covers the increasing η range that is missed by the TPC [6].
This thesis reports on the analysis of data taken from the initial operation of the
FGT. Chapter II provides a description of the production of high-energy polarized
protons, the STAR detector, and specifically the FGT detector. Chapter III describes the
analysis of the FGT performance, which includes investigating correlations of quantities,
such as electronic pedestal position and width, measured with both high voltage off and
on, using cosmic ray test data and data after the FGT was installed into STAR. Chapter
IV discusses the conclusions from this analysis and the possibilities of future analysis.
4
Chapter II
Detector
The Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory
(BNL) was the first facility to collide heavy ions. Normally for heavy-ion experiments at
RHIC, gold ions are accelerated, but polarized proton beams can also be accelerated and
used in spin physics experiments [2]. For a proton beam to be “polarized” means that
the proton spins are preferentially aligned in a particular direction. The polarizations of
each beam are measured at several locations in the acceleration process by
polarimeters, and the total polarization ranges on a scale from 0-100%. Typical
polarization measurements are around 50%, meaning there is a 50% excess of protons
with spin in a desired direction for the proton beam. The magnitude of the beam
polarization dilutes the measured spin effects from polarized proton collisions, so it is
important to have as large of a polarization value as possible.
An asymmetry ε, as measured by a detector system, is related to the analyzing
power A, which indicates the effect of spin on particle production through interactions,
by the equation,
, where P is the beam polarization. The asymmetry is defined
as the difference between the number of particles measured in one state and those in
an opposite or different state divided by the sum of those states, as described by
5
.
(1)
In Eq. (1), N+ is the number of particles measured with beam proton spins aligned
parallel, and N- is the number of particles measured with spins aligned antiparallel.
Asymmetry measurements lead to an understanding of the spin effects in collisions,
such as the spin contribution of constituents to the overall spin of the proton [7].
A diagram of the RHIC facility [8] is given in Fig. 2. Polarized protons are
generated at more than 1012 protons per bunch at the optically-pumped polarized ion
source [9] and are injected into a linear accelerator, where the protons are accelerated
to 200 MeV, before being sent to the booster synchrotron. In the booster, the protons
are accelerated to 1.5 GeV and then continue to the Alternating Gradient Synchrotron
(AGS). In the AGS, polarized protons are accelerated to about 25 GeV. The protons are
finally injected into RHIC and are split into two beams, called the “blue” and “yellow”
beams. Protons in the blue beam travel clockwise around RHIC, while the protons in the
yellow beam go counterclockwise. The protons reach relativistic speeds and each beam
has an energy up to 255 GeV [10].
Helical magnets called Siberian snakes [11] are located in RHIC to keep both
beams polarized. Each time the beam of protons pass through a snake magnet, the
spins are rotated by 180o to prevent accumulated depolarization as the proton beams
travel around the RHIC ring. For half of the RHIC ring, the protons are polarized spin up
and the other half, with spin down. Spin rotator magnets are used to longitudinally
polarize the protons just before the intersection or collision points of the two beams [9].
6
Fig. 2. The facilities of BNL showing the linear accelerator, the Booster
Synchrotron, the Alternating Gradient Synchrotron (AGS), and RHIC [8].
The RHIC ring has five separate polarimeters to measure beam polarization,
while the AGS, the Booster Synchrotron, and the linear accelerator each have a
polarimeter for measuring the beam polarization during each step of the acceleration
process.
The RHIC ring is 2.4 miles in circumference and has up to six intersection points
for the two beams, as shown in Fig. 2. The “6 o’clock” intersection point is the location
of the STAR detector (Solenoidal Tracker at RHIC) [12]. There are several important
components to the STAR detector: the Time Projection Chamber (TPC) [5], which is used
for detecting particle tracks after the collision; and the Barrel Electromagnetic
Calorimeter (BEMC) [13] and Endcap Electromagnetic Calorimeter (EEMC) [14], each of
which measures the energy deposition of particles produced in proton collisions [10]. A
7
new addition to the STAR detector is the Forward GEM Tracker (FGT) [4], which also
provides the tracking of charged particles from the intersection region in the forward
direction. Figure 3 shows a cut-away view of the STAR detector with the collision point
located in the center of the figure.
One of the main goals of the experiment is to determine the quark/antiquark
contribution to the spin of the proton, which comes from a measurement of the
asymmetry in the production of W bosons. Both the FGT and TPC are needed to provide
tracking within the magnetic field to identify the momentum and the sign of the lepton
from the W boson decay. This selects the
boson and hence which quark and
Fig. 3. The STAR Detector. Components include the Forward GEM Tracker
(FGT), the Time Projection Chamber (TPC), the Barrel Electromagnetic
Calorimeter (labeled EMCal), and the Endcap Electromagnetic Calorimeter
(labeled Endcap EMCal) [15].
8
antiquark were involved in the interaction. Before the FGT was installed into STAR,
tracking was done predominantly by the TPC, in which the tracking of particles after the
collision was inadequate at large η (forward angles). The FGT provides the needed
tracking at large η for charged particles before they reach the EEMC, where the energy
deposited by the charged particle is measured.
The FGT is comprised of six disks. Each disk is divided into four quadrants, and
each quadrant consists of two high voltage planes with three GEM (gas electron
multiplier) foils in between. A typical operating voltage of the high voltage planes is
around 3800 V. The GEM foils are made with chemically-formed holes, each having a
pitch of 140 μm. The holes have a double conical shape with a 50 μm inner diameter
and a 70 μm outer diameter [4], as shown in Fig. 4. The GEM foil technology was
originally developed at CERN [16], but the GEM foils used in the STAR FGT were
manufactured by Tech-Etch Inc. [17]. The foils are made from a 5 μm copper coating on
a 50 μm kapton insulator. The gas flowing through the holes is a mixture of argon and
carbon dioxide (Ar-CO2), and was designed to contain 70% argon and 30% carbon
dioxide [18]. The gas in the FGT is monitored by a bubbler to indicate flow.
Fig. 4. Gem foil hole pattern [4].
9
The FGT detects charged particles using gas electron multiplier (GEM) technology
[16]. When a charged particle traverses the FGT detector, it ionizes the gas, freeing
electrons. These electrons drift in an electric field of the quadrant until reaching holes
that are located in the GEM foils. A strong electric field is produced in each GEM foil
hole, as seen by the density of electric field lines in Fig. 5. The electrons are accelerated
in the electric field of the GEM foil holes and collide with more gas-mixture atoms,
creating an electron multiplication. The electrons proceed through three layers of GEM
foils, thus creating a large number of electrons. All of the electrons drift towards two
planes of strips providing two-dimensional readout for data acquisition. As the
electrons approach the readout plane, a charge is induced and creates the signal. The
large number of electrons can induce a charge on many strips, and these strips can then
be “clustered” to form a “hit” in the plane [19]. A “cluster” groups nearby strips with
energy deposited on them. This cluster of energy in a quadrant indicates a “hit” in the
FGT disk. By connecting “hits” from the other quadrants and disks, a particle track can
be determined.
Fig. 5. Gem foil holes and electric field lines (shown in red) [4].
10
The FGT is designed to have six, triple GEM foil disks and each disk be divided
into four quadrants. The GEM disks are numbered 1 through 6, with one being closest
to the collision point and 6 being the farthest from the collision point. The quadrants
are lettered A through D in a clockwise manner beginning with A at the “one o’clock”
position. Figure 6 indicates the naming convention and the placement of the GEM disks
and quadrants around the beam line.
Each quadrant contains ten APV25-S1 readout chips [21]. The signal pulse from
the electron multiplication is sent to a preamplifier, inverter, and shaper within the APV
chip to create an analog signal. The two-dimensional readout planes of the FGT have
been divided into radial (R) and azimuthal (φ) strips, with each strip corresponding to
one channel. Each APV chip serves 128 channels and each channel has seven time bins.
One time bin holds readout data for each strip in a period of time of approximately 25
ns. The seven time bins can be used to map out pulse shapes and adjust timing. This
design in the readout planes results in a total of 720 R strips and 560 φ strips for each
quadrant [4]. Figure 7 gives an example of the strip arrangement for one quadrant.
Fig. 6. Identification format of the disks and quadrants of the FGT [20].
11
Fig. 7. Example of quadrant strips [22].
A front-end electronics (FEE) assembly, that contains the APV chips, is located at
the border of adjacent quadrants in a disk. Each APV chip reads data from a defined
region of R and φ strips. A differential analog pulse is driven from each APV chip to the
APV readout module (ARM). In the ARM, the pulses are digitized by an analog digital
converter (ADC). The data are collected from the ARMs by the APV readout controller
(ARC) and then sent to the STAR data acquisition system. The ARC also sends
commands to the ARM cards for setting up the APV chips. Figure 8 shows the first disk
of the FGT with these pieces of hardware labeled. The time required to read out one
time bin of each channel of one APV is approximately 7 μs.
12
Fig. 8. The first disk of the FGT labeled with quadrant names, FEE assemblies (asmb),
ARMs, ARCs (shown as RDO), and APVs (numbers) [22].
Each quadrant uses ten APV chips and each chip reads data from a certain region
of R and φ strips within the quadrant. Figure 9 gives two examples of the R and φ strip
locations read by a single APV in a single quadrant.
(b)
(a)
Fig. 9. R and φ strip locations read by a single APV. Shown are the strips read by (a) APV
0 and (b) APV 1 [22].
13
The FGT was installed into STAR in 2011 with the first disk instrumented with all
four quadrants and the remaining five disks with only two quadrants each. These two
quadrant disks are aligned so that reconstruction of tracks can still be made. Data from
this configuration were analyzed and described in the next chapter.
14
Chapter III
Data and Analysis
As the Forward GEM Tracker was being built, quadrants were individually tested
using cosmic rays. The cosmic-ray test setup had one or more quadrants of the FGT
placed in between two large-area scintillator detectors. Figure 10 shows a photograph
of the FGT cosmic-ray test setup. The trigger consisted of a signal coincidence between
the two scintillators, which caused the FGT quadrants to be read out.
Scintillator
Quadrant
Quadrant
Quadrant
Scintillator
Fig. 10. Cosmic-Ray Test Setup. The black arrows indicate the location of the quadrants
and the red arrows indicate the location of the scintillator detectors [23].
15
Data were analyzed to verify that the detector works, to investigate how it
actually works, and to be sure the detector still operates in the same manner once it is
installed into STAR. The analysis also involved looking for any trends or correlations
that may exist between the channels, time bins, or APVs. These trends or correlations
could arise within individual electronic channels or by features inherent in an APV or
time bin. As an example, the order in which data are read within an APV chip may affect
the electronic pedestal width. The first data sets were collected with the high voltage to
the GEM foils turned off. This means that no signals from actual cosmic rays are read by
the FGT.
III.A Cosmic Ray Data. High Voltage Off
The first priority in the analysis was to ensure that a given quadrant was working
properly. One way to check this operation is to investigate the readout of the electronic
pedestal. A pedestal is an ADC reading of a channel in the electronics, when no energy
is deposited in the detector. Any signal from charged particles passing through the
detector should deposit energy above the pedestal value. When the high voltage on the
GEM foils is turned off, there is no signal produced by charged particles, so the only data
comes from the electronics. Figure 11 shows an ADC distribution for APV channel 048,
time bin 02, and APV 02, and the peak shown is the pedestal. Ideally, this data would
be a very narrow Gaussian peak, meaning that the electronics read a single value or ADC
channel, but instead the pedestal is observed as a wider-width Gaussian distribution.
16
This distribution is the result of noise from the electronics and small shifts in the
pedestal location in ADC channel. In Fig. 11, a Gaussian fit was made of the peak in the
distribution and the mean and width were calculated.
Understanding the pedestals is a fundamental step in testing a detector. If the
pedestal is not understood, then problems interpreting a signal in the detector could
arise. These studies were very helpful to the collaborators building and implementing
the FGT. This analysis gave an initial look at the output of the electronics to see if
behavior is as expected or if any adjustments or replacements needed to be made
before the FGT detector was installed into the larger STAR detector.
The data used for this analysis includes 30 APVs or three quadrants that were
placed in a configuration between the scintillator detectors (see Fig. 10). The analysis
involved looking at the ADC distributions for each channel (128 total for each APV), time
bin (7 total for each channel), and APV (30 total). The ADC spectra, which consist of
Fig. 11. Pedestal histogram of channel number 048, time bin 02, and APV 02
with Gaussian fit. The fit-mean is at ADC channel number 745 and the fit-sigma
(width) is 31.34 ADC channels.
17
pedestal peaks only with high voltage off, are fit with a Gaussian curve with a fit range
set to 400 ADC channels from the mean of the histogram. From this fit, three fit
parameters were found: the peak value, the mean of the fit, and the width of the fit.
The fit-mean and fit-sigma values for each channel, time bin, and APV, were used for the
subsequent analysis.
Figure 12 shows the fit-mean distribution that includes the fit-means from every
channel, time bin, and APV of three quadrants, totaling 26,880 fits. Figure 12 illustrates
the wide range of pedestal mean ADC channel values. The total distribution of the fitmeans can be separated into the seven time bins (numbered 0-6) to look for any
patterns or correlations. The fit-mean distribution per time bin is shown in Fig. 13 for
two time bins, 00 and 03, for all channels and APVs.
Only two of the seven time bins are shown in Fig. 13, but all seven were similar
in shape, meaning the fit-mean distributions did not change per time bin and all have a
Fig. 12. Total ADC distribution of the Gaussian fit-means for all combined
channels, time bins, and APVs from three quadrants.
18
(b)
(a)
Fig. 13. Distribution of Gaussian fit-mean per time bin. ADC distributions are
shown for (a) time bin 00 and (b) time bin 03.
similar shape to the total fit-mean distribution in Fig. 12. Figure 13 includes data from
all channels (128 for each APV) and all APVs (10 for each quadrant) from three
quadrants, which results in a large number of values. Any possible trends across the
time bins may be hidden or diluted within this data set.
Figure 14 shows the mean of the ADC spectra for each time bin, including the
two shown in Fig. 13. Figure 14 indicates that there is no correlation between the
pedestal fit-means and the time bins. As previously mentioned, Fig. 13 and Fig. 14
contain all channels and APVs, so the time bins needed to be investigated individually by
Mean (ADC channel)
channel and APV.
1050
1040
1030
1020
1010
1000
0
1
2
3
Time Bin
4
5
6
Fig. 14. Average of Gaussian fit-mean distribution per time bin.
19
The next analysis focused on the ADC spectra from one APV and examined each
time bin of every channel. The analysis involved the pedestal fit-means from selected
channels in APV02, and the fit-means for each time bin were compared to time bin 04.
APV02 appears to be a “normal” APV, based on other analysis. Time bin 04 was selected
because it is expected to be the middle of the seven time bins in the APV channel.
Figure 15 shows the pedestal fit-means of each time bin (subtracted from time bin 04)
for five channels of APV02 and illustrates an “oscillatory” behavior between even- and
odd-numbered time bins for certain channels. Even though this pattern exists, the
difference in pedestal fit-means between the time bins for APV02 is roughly 30 ADC
channels maximum. Figure 15 only shows five channels of one APV, but it includes the
different levels of variation in fit-mean values across the time bins seen across all the
channels.
Figure 15 indicates that time bin 04 and time bin 00 have similar ADC values
across the channels. This pattern is also seen in Fig. 16, which shows the fit-means of
Normailized fit-mean (ADC
channel)
30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
Channel 17
Channel 34
Channel 62
Channel 95
0
1
2
3
Time Bin
4
5
6
Fig. 15. Difference in average pedestal fit-mean values across the time bins for
different channels in APV02. The ADC values are compared to time bin 04. Lines
are included to guide the eye.
20
time bin 00 subtracted from time bin 04 for all channels. In Fig. 15 and Fig. 16, the error
bars are smaller than the size of the points. This flat line seen in Fig. 16 is the same in all
even numbered time bins in comparison to time bin 04, meaning that time bins 00, 02,
04, and 06 all have similar fit-mean values across the channels for APV 02.
Odd-numbered time bins subtracted from time bin 04 show a correlation in Fig.
17. Figure 17 displays a downward-sloping trend in the normalized fit-mean values
across the channel numbers for time bin 05. At channel numbers greater than about 70
in Fig. 17, the ADC values of time bin 05 are most likely greater than the ADC values in
time bin 04. This same trend is seen in all the odd-numbered time bins, but the
crossover point is not at the same channel number. In Fig. 17, the error bars are smaller
than the size of the points. Table I lists the average and standard deviation values of the
difference in the pedestal fit-mean values subtracted from the pedestal fit-mean values
Normalized fit-mean (ADC channel)
of time bin 04 for all the channels of APV 02 for all time bins.
20
Mean = 0.236
St. Dev. = 1.47
15
10
5
0
-5
-10
-15
-20
0
10
20
30
40
50
60
70
80
90 100 110 120 130
APV Channel Number
Fig. 16. Fit-means from time bin 00 subtracted from time bin 04 as a function of
channel number for APV 02.
21
Normalized fit-mean (ADC channel)
40
30
20
10
0
-10
-20
-30
-40
0
10 20 30 40 50 60 70 80 90 100 110 120 130
APV Channel Number
Fig. 17. Pedestal fit-mean values for time bin 05 subtracted from time bin 04 fitmeans as a function of channel number for APV 02.
In the previous analysis presented above, the total Gaussian fit-mean
distribution in Fig. 12 was separated by time bins. The next analysis separated the same
distribution (Fig. 12) by APVs. The data have a total of 30 APVs (numbered 0-29) and
each APV has 128 channels. Figure 18 shows two examples of the fit-mean distributions
that include all channels (128 per APV) and all time bins (7 per channel). APV11 and
APV28 were selected to show that the APVs individually cover a range of about 200 ADC
channels, but this range varies in ADC channel location. For example, APV11 has an ADC
range between about 600-800 ADC channels, and the ADC range of APV28 is between
about 1200-1400 ADC channels.
Table I. Average and standard deviation for the pedestal fit-mean values of the time
bins subtracted from pedestal fit-means of time bin 04 for all channels of APV02.
Average (ADC channel)
Standard Deviation (ADC channel)
Time Bin Subtracted from Time Bin 04
0
1
2
3
5
0.236
-0.561
0.779
-2.26
-0.519
1.47
14.07
2.44
10.21
15.22
22
6
1.07
3.25
(b)
(a)
Fig. 18. Pedestal fit-mean distribution of (a) APV11 and (b) APV28. These
distributions include all 128 channels and seven time bins.
Taking the mean values from the 30 APV fit-mean histograms, such as those
shown in Fig. 18, and plotting them as a function of APV number will illustrate any
variation in the means across the APVs. Figure 19 displays the mean value of the ADC
distribution for an APV as a function of APV number for three quadrants used in the
cosmic ray tests. The data appear similar in groups of five APVs. This pattern correlates
to the experimental setup of the APVs; each quadrant has ten APVs, in two groups of
five, located at the quadrant boundaries (see Fig. 8). The first five APVs are connected
as stated in Chapter II, and the next five are connected using a crossover cable that
connects the two sides of the FEE assemblies to the readout. This pattern then repeats
itself in all three quadrants. The error bars are on the order of a few ADC channels in
Fig. 19, so the variation is statistically significant. It is not expected for the APVs to have
the same mean (pedestal) values because each APV uses different capacitors, but the
pattern repeats based on the similar physical connections in hardware.
23
Mean Values (ADC channel)
1600
1400
1200
1000
800
600
400
200
0
0
2
4
6
8 10 12 14 16 18 20 22 24 26 28 30
APV
Fig. 19. The mean of APV distribution as a function of APV.
The ADC spectra of the pedestals were fit with a Gaussian curve and, besides the
mean of the distribution, the widths (sigma) of the distribution were found within the fit
range. Plotting all the pedestal fit-sigma values per channel, time bin, and APV gave the
total fit-sigma distribution, shown in Fig. 20.
Most of the pedestal widths have a typical fit-sigma value in the 20-40 ADC
channel range, but there are some with much larger values. A large fit-sigma
demonstrates a wide pedestal or a poor Gaussian fit to the pedestal. A wide pedestal
could be the result of large amounts of electronic noise or just a shift in the pedestal
mean value.
Separating the ADC pedestal width values in Fig. 20 into time bins or into APVs,
just as was done with the pedestal fit-means, provides additional information about the
performance of the FGT electronics. Figure 21 gives two examples of the distributions
of the pedestal fit-sigma values separated by time bin. The same issue of the dilution of
any possible effect holds for the pedestal fit-sigma distribution per time bin, as with
24
Fig. 20. Total pedestal fit-sigma distribution. The distribution in ADC channels
contains data from each channel, time bin, and APV.
the fit-means per time bin. Figure 22 displays the mean of the histogram from the
pedestal fit-sigma distribution histograms per time bin, including those in Fig. 21, as a
function of time bin. Figure 22 shows little variance in the average pedestal fit-sigma
across the seven time bins.
(b)
(a)
Fig. 21. Fit-sigma distribution per time bin. Distributions are shown for (a) time
bin 04 and (b) time bin 05 for all channels and APVs.
25
The total pedestal fit-sigma values in the distribution shown in Fig. 20 can also be
separated by APV, and these results are displayed in Fig. 23. Here it is clear that APV 28
produces pedestal fit-sigma values over a wide range, where APV 10 gives more
expected sigma values. Both Fig. 23 (a) and (b) do however have multiple peaks. This
implies that each APV has channels or time bins that produce pedestals at a range of
different widths. A narrow pedestal width could mean that a channel is not working
properly, and a wide pedestal could be the result of large amounts of noise from the
electronics or a shift from instability.
Figure 24 shows the distribution of the mean of the pedestal fit-sigma
distribution histograms per APV, including those shown in Fig. 23. In Fig. 24, it is again
possible to see the groupings of ten APV chips by quadrant for the three quadrants
studied. It also shows that the APV28 mean value does produce an abnormal
distribution of pedestal widths, as shown in Fig. 23 (b), in comparison to the other APV
Mean of the pedestal
widths (ADC channel)
chips.
45
44
43
42
41
40
39
38
37
0
1
2
3
Time Bin
4
5
6
Fig. 22. Mean of pedestal fit-sigma distribution for each time bin. Each point
includes data from 30 APVs and 128 channels per APV.
26
(b)
(a)
Fig. 23. Fit-sigma distribution as a function of APV. Distributions are shown for
(a) APV 10 and (b) APV 28. Each distribution includes all channels (128) and time
bins (7).
Some fluctuations in the data, such as a shift in the pedestal location, could
result in poor fits to the pedestals. Some abnormal ADC distributions result in the
pedestal being double-peaked or asymmetric, as displayed in Fig. 25. These shapes
Mean from Sigma Distribution
(ADC channel)
could imply a possible shift in the pedestal during the run.
90
80
70
60
50
40
30
20
10
0
0
2
4
6
8 10 12 14 16 18 20 22 24 26 28 30
APV number
Fig. 24. Means of the fit-sigma distributions from each APV as a function of APV
number.
27
(b)
(a)
Fig. 25. Examples of poor Gaussian fits to the pedestal peak shown (a) for
channel number 14, time bin 06, APV 28 and (b) for channel number 3, time bin
05, APV 02.
Another study involved looking into common mode noise. In the FGT, the
operating conditions could change and cause fluctuations event by event, creating a
type of shift in the pedestal data common to the whole detector. To investigate this
behavior, an average ADC value from all the channels of a single APV is calculated and
that average value is then subtracted from a given channel’s raw ADC value for each
event and time bin. This subtraction should result in a reduced width in the pedestals,
i.e. a smaller sigma value, because it would remove any systematic variations common
to all the channels. The ADC distribution histograms were re-created after this
subtraction for each channel, time bin, and APV. The Gaussian fit is applied over the
range of 400 ADC channels from the mean of each pedestal histogram. Figure 26
shows the new total pedestal fit-sigma distribution, after the subtraction for common
mode noise was made. A comparison of the distribution from Fig. 20, which shows the
total raw fit-sigma distribution, to Fig. 26, which shows the fit-sigma distribution after
28
Fig. 26. Pedestal width ADC distribution after common mode noise subtraction.
The distribution shows the pedestal fit-sigma values of all channels, time bins,
and APVs.
the common mode noise subtraction, gives evidence of common mode noise in the FGT.
The pedestal values decreased in width and the main peak is taller after the subtraction.
This change means that more pedestals are now in the width range of 20-40 ADC
channels, where before, as in Fig. 20, there was a “bump” around a width of 60 ADC
channels.
III.B Cosmic Ray Data. High Voltage On
By supplying high voltage to the GEM foils, ADC values larger than the pedestal
can be observed in the two-dimensional histograms of APV channel as a function of ADC
value. These larger ADC values are due to the multiplication of electrons stemming
from cosmic rays that pass through the quadrants. The same 30 APVs from the three
29
quadrants used in the cosmic ray test apparatus and from the pedestal analysis were
used for these tests. Figure 27 shows the raw ADC distribution of all the channels in
APV01 and time bin 04. The dense region around ADC channel number 700 in Fig. 27 is
produced by the pedestals and all the ADC values larger than that band represent hits
from cosmic rays. One feature of Fig. 27 is the slant or systematic shift in the pedestal
location across the channels. This characteristic presents a problem when trying to
separate the pedestal from signal. Normalizing the pedestal means to a certain value
from a single channel will “straighten” this distribution and make it easier to separate
the pedestal from signal. The lowest pedestal fit-mean value of each channel in a given
APV was used as the normalization factor. Figure 28 represents the same data as shown
in Fig. 27, only now the data are normalized to the lowest pedestal fit-mean value of a
channel for each APV.
Fig. 27. Raw ADC spectrum of 128 channels in APV01 and time bin 04.
30
(b)
(a)
Fig. 28. APV channel number as a function of ADC channel for time bin 04 and
APV 01. The values are normalized to the lowest fit-mean of the channels with
(a) high voltage on and (b) high voltage off.
The separation of the signal from the pedestal ADC values can be investigated by
analyzing the projection of Fig. 28 (a), which is given in Fig. 29 (a). Since the pedestal
dominates this histogram, Fig. 29 (b) shows the same projection with an enlarged scale
so that the signals above the large pedestal peak can be observed.
An estimate was made on a pedestal cut at ADC channel number 800 for time
bin 04 and APV01. This cut limit (location in ADC channels to remove the pedestal)
needs to be several sigma away from the pedestal mean to avoid any variation
that is still a part of the pedestal. A cut on a constant value of the ADC across all the
time bins or APVs cannot be applied due to variation in the pedestal means (see Fig. 27).
The previous study has shown that the pedestals are not in the same location for each
time bin or APV, so the cut may be made at a few sigma away from the pedestal mean.
A data cut on ADC channel number 800, for the time bin and APV shown in Fig. 29, is
31
(a)
(b)
Fig. 29. Histogram of ADC values for time bin 04 and APV 01. (a) This is the
projection of ADC channels of Fig. 28. (b) The same projection is shown with an
enlarged scale.
approximately six-sigma away from the mean of the histogram. This six-sigma cut may
then be applied across all APVs and time bins. Figure 30 displays the same data as Fig.
28, but now the six-sigma cut has been applied to the data, which removes the pedestal
from the histogram. The projection of Fig. 30 on the x axis is shown in Fig. 31, in
combination with all other time bins of one APV.
Fig. 30. APV channel number as a function of ADC channel, for time bin 04 and
APV 01. Only ADC values larger than six-sigma are shown.
32
Fig. 31. Histogram of ADC data with the six-sigma cut applied. The distribution
includes all time bins of APV 01.
The change in the number of data points representing the signal can be studied
by varying the sigma cut from the pedestal location. Figure 32 displays the ratio of
signal values to the entire ADC data sample as a function of the ADC pedestal cut. The
conclusion of this study is that as the sigma cut is changed, the number of signal values
does not change by more than 0.1%.
The six-sigma cut was also applied to the data with the high voltage off, to see
how many of the entries above six-sigma still remain due to the pedestal. For example,
the APV shown in Fig. 27 has zero entries six-sigma above the mean with the high
voltage off, while other APVs, such as APV15, have entries greater than six-sigma still
coming from the pedestal with high voltage off. In addition, the location of the
pedestals did not shift by more than a few ADC channels between high voltage on and
off for the cosmic ray test data.
33
Ratio of signal to total
entries (%)
0.2
0.15
0APV 00
1APV 01
0.1
2APV 02
0.05
3APV 03
0
4APV 04
2
3
4
5
6 7 8
Sigma Cut
9
10 11
Fig. 32. Ratio of the signal to total entries as a function of the location on the
ADC pedestal cut. The data points are summed over all time bins and are shown
for the first five APVs (00-04).
III.C STAR Data.
Once the FGT was installed into the STAR detector, some portions of the analysis
from cosmic ray data were repeated to see if the detector behaved in the same manner.
The new analysis of the data from the FGT located within the STAR detector is referred
to as “STAR data.” Pedestal data taken with the high voltage off for the cosmic ray test
setup and for the STAR data were compared, and the results were examined to see if
any shift or change occurred. It is important to note that in this comparison analysis
between cosmic ray data and STAR data, it is actually the electronic ID numbers that
remain the same, not necessarily the same quadrants or hardware. Because of this,
more changes could have been introduced than just the location of the FGT, such as
34
changes in the electronics or APV chips. Therefore, the following analysis can only give a
rough comparison between cosmic ray test data and STAR data.
Starting with the ADC distributions for both cosmic ray test data and STAR data
with the high voltage off, Gaussian fits were applied to the pedestal peaks of each
channel, time bin, and APV. These data sets included 30 APVs, each with 128 channels
and each channel with seven time bins. Taking each pedestal fit-mean from the ADC
distributions of each channel, time bin, and APV, the total fit-mean distribution of the
pedestals can be plotted. The total fit-mean distribution separated by APV will show if
the distribution has changed. Figure 33 shows the means from the APV pedestal fitmean distributions as a function of APV. The cosmic ray data in the figure are the same
as Fig. 19. The pedestal means are now smaller and more tightly-bunched with the
STAR data compared to the cosmic ray test data, and the groupings of five APVs are no
longer prominent. This difference in the data could be the result of adjustments or
Mean from APV fit-mean
distribution (ADC channels)
replacements in the APV chips. The error bars are on the order of a few ADC channels.
1600
1400
1200
1000
800
600
400
200
0
STAR
COSMIC
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
APV
Fig. 33. Mean from pedestal APV fit-mean distribution. Each point includes all
channels (128) and time bins (7). The cosmic ray data are the same as that in Fig.
19.
35
Figure 34 shows the fit-mean distributions from STAR data and cosmic ray data
for time bin 04. These histograms include every channel (128 per APV) and APV (30
total) for one time bin. The pedestal means now fall within a smaller range of ADC
channels for the time bin shown. This difference could be because of better timing of
the pulse in the time bins or a different APV chip.
The widths of the pedestal ADC distributions indicate that the fit-sigma values
remain about the same for the time bins. Figure 35 shows the fit-sigma distributions for
time bin 04 for STAR data and cosmic ray test data, and indicates that the pedestals did
not change width between the two data sets.
Figure 15 previously revealed an “oscillatory” pattern between the even- and
odd-numbered time bins in the cosmic ray data. Now using STAR data, Fig. 36 shows
the same channels, and the fit-means were normalized to time bin 04, just as in Fig. 15.
The patterns across the time bins in Fig. 36 are quite different from those in Fig. 15, and
(a)
(b)
Fig. 34. Fit-mean distribution for time bin 04. (a) The fit-mean distribution for
STAR data and (b) the same distribution for cosmic ray data are shown.
36
(b)
(a)
Fig. 35. Fit-sigma distribution per time bin (04 shown). (a) The fit-sigma
distribution for STAR data and (b) the distribution for cosmic ray data are shown.
do not present a clear pattern as they did previously. This difference again could be the
result of different APV chips used with the STAR data than those from cosmic ray test
data. The error bars are smaller than the size of the points in Fig. 36.
The pedestal means were also investigated as a function of channel. The
Difference in fit-means (ADC
channel)
pedestal means in time bin 00 were subtracted from pedestal means in time bin 04 (as
30
20
10
Channel 17
17
0
Channel 34
34
62
Channel 62
-10
Channel 95
95
-20
Channel 121
121
-30
0
1
2
3
4
5
6
7
Time Bin
Fig. 36. ADC channel as a function of time bin. The fit-means were normalized
to time bin 04 and the ADC values are shown for the same five channels of APV
02 as in Fig. 15.
37
shown in Fig. 16 for cosmic ray data). In Fig. 37, the shape of the curve is still similar for
STAR data. Looking at the pedestal means in time bin 02 subtracted from the pedestal
means in time bin 04 in Fig. 37(a), a different shape is observed at low channel numbers.
The error bars are smaller than the size of the points in both plots of Fig. 37.
Comparing the correlation between the difference in pedestal means between
time bin 04 and 05, a positive slope for the STAR data and a negative slope for cosmic
ray data can be seen in Fig. 38 and Fig. 17. This “slant” in the data was present in both
cosmic ray test data and STAR data and requires more investigation.
The sloping trend in the channels may be a result of the “electronic ID number”
from the data acquisition. The electronic ID refers to the order in which the APV
channels are read by the data acquisition electronics. Using the ADC fit-means from the
pedestals and plotting them as a function of electronic ID, a similar sloping trend is
indicated, as seen in Fig. 39. Figure 39 contains data from time bin 04 of APV00 with
(b)
Difference in pedestal fit-mean
(ADC channel)
Difference in pedestal fitmean (ADC channel)
(a)
40
30
20
10
0
-10
-20
-30
-40
0
50
100
APV Channel Number
150
40
30
20
10
0
-10
-20
-30
-40
0
50
100
APV Channel Number
150
Fig. 37. Difference in pedestal means as a function of channel number in APV 02.
(a) Pedestal means in time bin 02 subtracted from pedestal means in time bin 04
for STAR data and (b) the same formula using cosmic ray data are shown.
38
Difference in fit-mean (ADC
channel)
40
30
20
10
0
-10
-20
-30
-40
0
10 20 30 40 50 60 70 80 90 100 110 120 130
APV Channel Number
Fig. 38. Difference in pedestal means as a function of APV channel number for
time bin 05 subtracted from time bin 04 for APV 02.
the high voltage off for the FGT in the STAR detector. The pedestal fit-sigma values for
time bin 04 and APV00 do not show a strong correlation with electronic ID, as seen in
Fig. 40. Fig. 39 and Fig. 40 both have error bars smaller that the size of the points. Even
though data from only APV00 are shown here, further analysis indicated that several
Fit-mean (ADC channels)
other APVs had similar plots to those shown above.
900
800
700
600
500
400
300
200
100
0
0
10 20 30 40 50 60 70 80 90 100 110 120 130
Electronic ID Number
Fig. 39. Pedestal fit-mean as a function of electronic ID for time bin 04 of APV00.
39
Fit-sigma (ADC channels)
70
60
50
40
30
20
10
0
0
10 20 30 40 50 60 70 80 90 100 110 120 130
Electronic ID Number
Fig. 40. Pedestal fit-sigma as a function of electronic ID for time bin 04 of APV00.
A question was raised on whether the readout plane strip length could have an
effect on the pedestals, such as the slope observed in Fig. 39. APV00 was selected for
this analysis because it has strips of varying length, and the location of the R strips and φ
strips read by APV00 can be seen in Fig. 41.
R strips
φ strips
Fig. 41. Map of R and φ strips read by APV00 [22].
40
The pedestal fit-mean and fit-sigma values used in this analysis were from STAR
data with the high voltage off. Figure 42 shows the pedestal fit-mean and fit-sigma
values for time bin 04 of APV00. In Fig. 42 (a) and (b), the first vertical line in the data
comes from values with shorter φ strips and the second vertical line from the longer φ
strips (see Fig. 41). The error bars on the fit-means and fit-sigmas are on the order of a
few ADC channels. In Fig. 43, the pedestal fit-mean and fit-sigma are shown as a
function of strip length for the R plane. Most of the R strips are the same length, which
can be seen in Fig. 41. Looking at the pedestal fit-mean values in Fig. 42(a) and Fig.
43(a), there may be a small correlation between the pedestal fit-mean values and the
varying strip lengths. Both Fig. 42(b) and Fig. 43(b) appear to show no strong correlation
between strip length and the pedestal fit-sigma.
All the studies so far have examined all the pedestals from every channel, but
this leads to question, “What is a ‘good’ pedestal?” Several failure states were defined
(b)
1000
Fit-sigma (ADC channel)
Fit-mean (ADC channel)
(a)
800
600
400
200
0
70
60
50
40
30
20
10
0
0.0
10.0 20.0 30.0 40.0 50.0
Strip Length (cm)
0.0
10.0 20.0 30.0 40.0
Strip Length (cm)
50.0
Fig. 42. Pedestal fit-means and fit-sigmas as a function of strip length in the phi
plane for time bin 04 of APV00. (a) The fit-mean of the pedestal as a function of
phi plane strip length, and (b) the fit-sigma of the pedestal as a function of phi
plane strip length are shown.
41
(b)
800
Fit-sigma (ADC channels)
Fit-mean (ADC channel)
(a)
600
400
200
0
0.0
70
60
50
40
30
20
10
0
0.0
10.0 20.0 30.0 40.0 50.0
Strip Length (cm)
10.0 20.0 30.0 40.0 50.0
Strip Length (cm)
Fig. 43. Pedestal fit-means and fit-sigmas as a function of strip length in the R
plane for time bin 04 of APV 00. (a) The pedestal fit-mean as a function of the R
plane strip length, and (b) the pedestal fit-sigma as a function of the R plane strip
length are shown.
and investigated to identify pedestals that did not meet certain requirements. These
failure states are listed in Table II. Other failure states were defined, such as hardware
not being used, an APV chip ruled as bad, disconnected strips, and no ADC value from a
channel; however the information related to these states was not available for analysis.
The three states listed in Table II were the ones of focus in this analysis. The ADC
distribution for every channel, time bin, and APV were viewed to identify “good” and
“bad” pedestals. The criteria applicable to the three failure states were applied to each
pedestal and the number of failures for each state is shown in Table III. When a
pedestal does not fall within the limits listed in Table II, it is considered to be a “bad”
pedestal.
Table II. Failure States for pedestals.
Failure State
1. Pedestal mean between 100-1200 ADC channels
2. Pedestal rms between 10-80 ADC channels
3. Ratio of number of entries within 1 sigma of the mean to the
number in the total peak between 0.6-0.95
42
Table III. Failure rates for the pedestals.
Failure State
1
2
3
Failure Rate
0.41%
5.07%
0.48%
Total: 26,880
110
1363
128
When examining each of the pedestal histograms, some appear quite different
than others. A common pedestal histogram can be seen in Fig. 44. The pedestal in Fig.
44 falls within all the limits set by the failure states and is considered a “good” pedestal.
Some pedestals, however, do not look like the pedestal in Fig. 44, but are considered
“good” pedestals because they are within limits of the failure states. Two examples of
this category are shown in Fig. 45.
The pedestal in Fig. 46 gives an example of a pedestal that is considered “bad”
because the RMS value is outside the given range and fails state 2. When a pedestal
was considered “bad,” the channel could be fixed and/or not included in further data
analysis.
RMS/Mean = 0.0597
Failure State 3 = 0.7446
Fig. 44. ADC distribution showing a typical pedestal for channel 095, time bin 01,
and APV 03.
43
(b)
(a)
RMS/Mean = 0.1823
RMS/Mean = 0.1886
Failure State 3 = 0.6762
Failure State 3 = 0.8035
Fig. 45. ADC distributions of “bad” pedestals considered “good”. (a) The
pedestal for channel 000, time bin 05, and APV14 and (b) the pedestal for
channel 018, time bin 06, and APV 21 are shown.
Since the current scheme for identifying “bad” pedestals needed improvement,
the task was to define a new failure state that would remove all the abnormal pedestals
without losing good ones with the limited amount of information known. A new test
used the RMS of the pedestal peak divided by its mean for pedestals of every channel,
time bin, and APV. After examining many histograms, a rough limit of 0.17 was chosen
RMS/Mean = 0.0223
Failure State 3 = 0.7569
Fig. 46. ADC distribution showing the pedestal for channel 057, time bin 02, and
APV23.
44
for the ratio of RMS to the mean of the histogram. Figure 47 is a histogram of the
RMS/mean ratio for all channels, and the cut point of 0.17 as a maximum is indicated on
the plot. Applying this new 0.17 limit on the ratio increased the number of “bad”
pedestal histograms by 550 (2.05% of the total). In Figs. 44 – 46, the ratio of the RMS to
the mean of the histogram values are displayed, and by applying this new cut
uncommon pedestals would be removed.
In a final study using STAR data, the behavior of the pedestals were investigated
under varying operating conditions. Two FGT operating parameters are the applied high
voltage and the gas mixture, both of which would affect the electron multiplication
process. To assist in this study, a number of data runs were taken under varying
conditions.
3000
2500
Number
2000
1500
1000
500
0
0
0.025
0.05
0.075
0.1
0.125
0.15
0.175
0.2
0.225
0.25
RMS/Mean
Fig. 47. Frequency plot of the ratio of RMS to the mean of the histogram for
every pedestal in all channels, time bins, and APVs. The arrow indicates the cut
point of 0.17.
45
The first study investigated pedestal stability in time. Seven runs were selected,
ranging in time from February 28, 2012 through June 11, 2012, during which the high
voltage was turned off. ADC spectra that include pedestals per channel, time bin, and
APV were created from these seven runs. The usual Gaussian fits were applied, and the
pedestal fit-mean and fit-sigma were found. Figure 48 shows the pedestal fit-mean as a
function of time for selected channels, time bins, and APVs. In Fig. 48, the error bars are
on the order of a few ADC channels. The pedestal fit-mean values from the middle five
data sets appear to be stable in time, while the first data set is quite different and the
last set has smaller values. Since the first data set was taken earlier in the run year, it is
possible that there were adjustments made in the hardware after that run.
The pedestal fit-sigma values show slightly more variation than the pedestal fitmeans, as displayed in Fig. 49 for selected channels, time bins, and APVs. The error bars
Pedestal fit-mean (ADC channel)
are a few ADC channels. It should be noted that none of the pedestal failure-state limits
700
650
1080410
600
1080411
550
500
1080412
450
1080413
400
1080414
350
300
2/11/12
4/1/12
5/21/12
Time (month/day/year)
7/10/12
Fig. 48. Pedestal fit-means as a function of time. The pedestal fit-means are
shown for channel 108, time bin 04, and APVs 10-14 for the seven data sets.
46
Pedestal fit-sigma (ADC
channels)
45
40
35
30
25
20
15
10
5
0
2/21/12
870414
870415
870416
870417
870418
4/1/12
5/11/12
Time (month/day/year)
6/20/12
Fig. 49. Pedestal fit-sigmas as a function of time. The pedestal widths are shown
for channel 087, time bin 04, and APVs 14-18 for seven different data sets.
previously mentioned were applied to these data sets. Any large difference in the
pedestals could be the result of a bad pedestal.
The main focus of this study was to observe how the pedestals varied in time.
Ideally, the pedestal means and sigmas should not change on a short time scale, e.g. in
the middle of collecting data, because fluctuations would affect the differentiation of
signal from pedestal. The pedestal means and sigmas appear stable over the range of
time selected, and they could be studied over a smaller time scale to verify that no
fluctuations are occurring.
Another pedestal study involved changing the high voltage of the FGT and
observing any change in the pedestal fit-mean and fit-sigma values. The operating high
voltage was increased from a nominal high voltage value, which is different for each
quadrant, in 50 V increments to 250 V over the nominal high voltage. The nominal
47
Table IV. Nominal high voltage values per quadrant.
Quadrant
1A
1B
1C
1D
2A
2B
3A
3B
4A
4B
5A
5B
6A
6B
Nominal (V)
3400
3450
3250
3500
3450
3250
3250
3450
3350
3450
3420
3220
3550
3400
voltages are given in Table IV for each quadrant. For this analysis, the ADC spectra of
each channel, time bin, and APV were fit with a Gaussian curve and the fit parameters
were found for six runs with different high voltages. Figure 50 shows the pedestal fitmeans for selected channels, time bins, and APVs as a function of high voltage added to
the nominal high voltage. The error bars are only a few ADC channels in this figure.
Pedestal fit-mean (ADC
channel)
600
500
750503
400
750504
300
750505
200
750506
100
750507
0
0
100
200
300
Voltage added to nominal high voltage(V)
Fig. 50. Pedestal fit-mean as a function of voltage added to nominal high
voltage. The pedestals are shown for channel 75, time bin 05, and APVs 03-07.
48
Figure 50 shows that the pedestal fit-means are stable with a change in the high voltage
from the nominal value, meaning that the electronics are not affected by the high
voltage.
Taking all the pedestal fit-means and plotting them together will give the total
pedestal fit-mean distribution for each new high voltage setting. Separating the data by
time bin and by APV will show if there are any fluctuations that may be hidden in Fig. 50.
Figure 51 uses the mean (of the histogram) of the fit-mean distribution, separated by
time bin and APV, and displays time bin 04 for selected APVs. Figure 51 shows no sign
of global fluctuations of the pedestal means with added high voltage.
Figure 52 shows data from the pedestal widths as a function of added operating
high voltage to the nominal voltage for a given channel, one time bin, and APVs 20-24.
Mean (ADC channel)
450
400
3 APV 03
350
4 APV 04
300
5 APV 05
6 APV06
250
7 APV 07
200
0
50
100
150
200
250
Voltage added to nominal high voltage (V)
300
Fig. 51. Mean (of the histogram) of the fit-mean distribution per time bin and
per APV as a function of voltage added to nominal high voltage. Means are
shown for time bin 04 and APVs 03-07. Each data point includes all 128
channels.
49
Pedestal fit-sigma (ADC
channels)
50
40
410420
30
410421
410422
20
410423
10
410424
0
0
50
100
150
200
250
300
Voltage added to nominal high voltage(V)
Fig. 52. Pedestal fit-sigma as a function of voltage added to nominal high
voltage. Pedestal fit-sigma values are shown for channel 041, time bin 04, and
APVs 20-24.
The data shown in Fig. 52 imply slight variations in the pedestal widths as a function of
added high voltage, with the error bars being smaller than the size of the points. Taking
the total fit-sigma distribution and separating it by time bin and APV also shows larger
fluctuations. Figure 53 shows the mean of the histogram for time bin 04 and selected
APVs, and it also indicates variations in the sigma values with added high voltage.
Mean (ADC channel)
55
50
45
18APV 18
40
19APV 19
35
20APV 20
30
21APV 21
25
22APV 22
20
0
100
200
Voltage added to nominal high voltage(V)
300
Fig. 53. Mean of fit-sigma distribution per time bin and per APV as a function of
voltage added to nominal high voltage. Data shown are for time bin 04 and APVs
18-22. Each point includes 128 channels.
50
Figure 54 shows the average pedestal fit-sigma per APV, for each high voltage
run. The conclusion is that the global change (over all channels and APVs) in the sigma
values is not statistically significant. These results with the pedestal mean and sigma
were expected because the high voltage change should not necessarily affect the
pedestal, and gives an indication that the FGT was working properly.
The last study looked at the pedestal fit-mean and fit-sigma values with a change
in the gas mixture. The FGT was designed to have a gas mixture of Ar-CO2 at a 70%
argon and 30% carbon dioxide (70:30 ratio), but recent studies have shown that 90%
argon and 10% CO2 (90:10 ratio) may improve the performance of the tracking. The
pedestal fit-mean and pedestal fit-sigma values from high voltage off runs, at the two
different gas mixtures were obtained.
To investigate the pedestal fit-means as a function of gas mixture, the ratios of
Average (ADC channel)
the70:30 pedestal fit-means to the 90:10 pedestal fit-means were calculated for each
40
39
38
37
36
35
34
33
32
31
30
0
50
100
150
200
250
voltage added to nominal high voltage (V)
300
Fig. 54. Average of the mean of the histograms from the fit-sigma distribution
per APV as a function of voltage added to nominal high voltage. The data shown
are for time bin 04 and include all APVs and channels.
51
channel, time bin, and APV. All ratios are shown in Fig. 55, in which the average ratio
from Fig. 55 is
, so the ratios of pedestal fit-means do not appear to
change with gas mixture. Figure 55 only displays data for time bins 02-06 of every
channel and APV because the first two time bins do not contain data due to an issue
with timing when the data were collected.
Figure 56 displays the ratio of the 70:30 gas-mixture pedestal fit-sigma values to
the 90:10 gas-mixture pedestal fit-sigma values. The average ratio from Fig. 56 is
, but the data shown do not include the first two time bins or
approximately 50 other data points. The first two time bins were removed from the
data, again because of a timing problem when the data were collected. The other 50
data points were removed based on pedestal data. The gas mixture is again expected to
show little, if any, effect on the pedestals.
8000
Mean = 0.998 +/- 0.001
7000
Number
6000
5000
4000
3000
2000
1000
0
0
0.2
0.4
0.6 0.8
1
1.2 1.4
Ratio of fit-mean (70:30/90:10)
1.6
1.8
2
Fig. 55. Frequency plot of the ratio of the 70:30 gas mixture pedestal fit-means
to the 90:10 gas mixture pedestal fit-means.
52
4000
Mean = 0.992 +/- 0.0004
3500
Number
3000
2500
2000
1500
1000
500
0
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
Ratio of fit-sigma (70:30/90:10)
Fig. 56. Frequency plot of the ratio of the 70:30 gas mixture pedestal fit-sigma
divided to the 90:10 gas mixture pedestal fit-sigma.
All of these studies were performed to investigate the performance of the FGT,
since this is its initial year in the STAR detector. The results of these studies indicate
that the detector electronics appear to be working properly.
53
Chapter 4
Conclusions
Analysis was conducted on FGT quadrants using data from cosmic rays during
the construction phase of the FGT, and with charged particles from proton-proton beam
collisions once the FGT was installed into STAR. In both sets of data, the pedestal
location and width were analyzed to look for any trends or patterns in the channels,
time bins, and/or APVs. Since this is the commissioning run for the FGT, the electronics
that read the data needed to be examined.
For the cosmic ray tests, the pedestal results provided evidence that the
detector was indeed working. The pedestal ADC spectra could indicate a problem with a
strip or APV and the time bin analysis could check the pulse timing. A future timing goal
of the FGT is to eventually use only one time bin, so these studies helped to understand
the FGT quadrant performance during each time bin. This analysis led to changes in the
hardware and readout electronics, such as replacing a poor-performing APV chip, before
the FGT was installed into STAR, as well as an understanding of how the detector works,
in general.
Analysis results from the cosmic-ray test data showed an “oscillatory” pattern
between even- and odd-numbered time bins, possibly due to a pulse timing problem,
54
and a slight linear correlation between the pedestal means and electronic channel
number, perhaps due to strip length. Pedestal mean and sigma patterns were observed
in the quadrants, such as recognizing groups of APVs by quadrant. These patterns were
related to the physical connections of each APV to the quadrant and then to the readout
electronics.
Another cosmic ray test study investigated signals with ADC values above the
pedestal from the FGT quadrants. The data were first normalized to the lowest fit-mean
in order to remove a systematic increase in the ADC values per channel. This simplified
the process of locating a cut on the data in order to isolate a signal from charged
particles from the pedestal. A six-sigma cut on the data was found to remove most of
the pedestal and keep the signal. This cut location was selected because the number of
entries over those passing the cut changed by no more than 0.1% over a wide range.
After the FGT was installed into the STAR detector, this analysis was repeated to
see if the FGT still worked in its new location, if it worked properly, and if any other
oddities with the electronics arose. This analysis was only a rough comparison between
cosmic ray test data and STAR data because the APV chips and/or other parts of the
electronics could have been replaced or adjusted in the FGT before it was installed into
the STAR detector. Any changes in the hardware and/or software from cosmic-ray test
data may be observed in the data, but only the electronic IDs were being compared, not
necessarily the same hardware. The pedestal mean and pedestal sigma distributions
per time bin and per APV were now different and appeared narrower. The “oscillatory”
behavior between even- and odd-numbered time bins was not observed in the STAR
55
data. The sloping pattern in the pedestal fit-means as a function of channel number
seems to be a result of the electronic ID number, which is the order in which the
channels are read from each APV chip.
The pedestal fit-mean and pedestal fit-sigma values were plotted as a function of
strip length to see if there were any correlations. The plots show that the pedestal fitsigmas are independent of the strip length, but there may be a weak correlation with
the pedestal fit-means and strip length. This could be because a strip of longer length
has a larger area to pick up noise. If there had been a strong correlation, a correction
could have been implemented for this based on the length of the readout strip.
Since there are many channels, time bins, and APVs in the FGT, a system for
identifying “bad” pedestal data was established so that these may be eliminated from
the data. Three “failure states” were initially investigated to see how much pedestal
data were identified as “bad.” The states included the pedestal mean within a range of
100-1200 ADC channels, the pedestal rms (width) within the range of 10-80 ADC
channels, and the ratio of the number of entries within 1 sigma of the mean to the
number of entries in the total pedestal peak within the range of 0.6-0.95. Only 0.41% of
the total number of pedestals were considered “bad” by the mean limits, 5.07% of the
total number were considered “bad” by the rms range, and 0.48% of the total number
were considered “bad” by the ratio. Upon further investigation, some pedestals that
were observed not to have the typical Gaussian shape still survived the three failure
states, so an additional cut was designed to identify the “bad” pedestals without cutting
out the “good” pedestals. The new cut was a maximum limit of 0.17 on the ratio of rms
56
to the mean of the histogram. This limit was based solely on the observation of single
channels and the one-by-one investigation of the pedestal histograms. In the future,
this cut may be implemented in the software to automatically remove channels, APVs,
or time bins that are not functioning properly and that are not considered “bad” by the
previous failure state limits.
Lastly, studies looked into the pedestal stability under a variety of conditions.
The first study involved the pedestal mean and width stability as a function of time. The
data showed that the ADC pedestal fit-mean and fit-sigma values are indeed stable, over
the period of several months.
The next study examined the pedestal stability as a function of high voltage. The
plots again showed that ADC pedestal fit-mean and fit-sigma values remain stable,
within statistics, as the high voltage was increased from a nominal setting. This study
again confirmed that the detector was working as expected.
The final study checked the stability of the pedestal values with a change in gas
mixture. As in the previous studies, the gas mixture is expected to have little, if any,
effect on the pedestals. The results show that the average value of the ratio of the
pedestal fit-means from the 70:30 Ar-CO2 gas mixture to the pedestal fit-means from
the 90:10 Ar-CO2 gas mixture was
the pedestal fit-sigmas was
and the average value of the ratio of
. Time bins 00 and 01 were not included in
to analysis due to an issue in timing during data collection. Both of these average ratio
values implied that the pedestals were stable with the change in gas mixture.
57
Further analyses that would be performed in the future include: a calculation of
the hit efficiency of the detector, an investigation of cluster sizes, and changes in the
gain from the high voltage and gas mixture studies. A study of the hit clusters would be
needed to optimize finding tracks from charged particles in the disks. The failure states
could be implemented in the software to rule out any chance of bad data affecting the
tracking efforts and to cut out dead regions. “Bad” channels could be identified so they
could be replaced or fixed before the next run.
58
Appendix A
Listed below are the names of all the data files and run numbers used in the analysis.
Table A.I. Cosmic-ray test data. The high voltage off file contains 6,916 events
and the high voltage on file has 3,355 events.
Cosmic Ray data files
High Voltage Off FGT008_FGT018_FGT007_PEDS_400001_2011_10_06_15_52_27
High Voltage On FGT008_FGT018_FGT007_400021_2011_10_06_14_01_23
Table A.II. STAR data. This pedestal file contains 2,020 events.
Run Number
13059031
Table A.III. Pedestal study in time. All the files contain approximately 2,000
events.
Run Number
Date
13059031
2/28/2012
13068061
3/8/2012
13079063
3/19/2012
13085015
3/25/2012
13106019
4/15/2012
13108067
4/17/2012
13162065
6/11/2012
Table A.IV. Pedestal study with change in high voltage. All the files, other than
the nominal, contain approximately 14,000 events. The nominal run contains
almost 9,000 events.
Run Number
Voltage added to Nominal (V)
13161052
0
13109033
50
13109035
100
13109037
150
13109038
200
13109039
250
59
Table A.V. Pedestal study with change in gas mixture. Both runs are pedestal files and
the 70/30 run contains 4,031 events and 90/10 has 2,018 events.
Run Number
13162065
13174041
Gas Mixture
70/30
90/10
60
Acknowledgements
First, I would like to thank my research advisor, Dr. David Grosnick, for his
continuous guidance, patience, and insight on this analysis. I truly appreciate all the
knowledge and experiences he has given me in making me a part of the STAR
collaboration. A special thanks to Dr. Stephen Gliske for his assistance in the analysis
and for providing many explanations of the FGT. Thank you to Drs. Hal Spinka, Dave
Underwood, Shirvel Stanislaus, and Don Koetke for the helpful information provided
towards this analysis.
I also want to thank my family for all their support and encouragement. Thank
you to my friends, fellow graduate students, and faculty at Ball State University. Thanks
to the collaborators of Valparaiso University for providing a summer assistantship
supported by the United States Department of Energy.
61
References
[1] J. Ashman et al. (EMC Collaboration), Phys. Lett. B206, 364 (1988); Nucl. Phys B328, 1
(1989).
[2] N. Saito, Nucl. Phys. B105, 47 (2002).
[3] A. Adare et al., Phys. Rev. Lett. 106, 062002 (2011).
[4] RHIC proposal, “Forward GEM Tracker (FGT) – A Forward Tracking Upgrade Proposal
for the STAR Experiment,” H. Spinka et al., Brookhaven National Laboratory, 2008
(unpublished).
[5] M. Anderson et al., Nucl. Instrum. Methods A499, 659 (2003).
[6] F. Simon, Nucl. Instrum. Methods B261, 1063 (2007).
[7] G. Bunce, N. Saito, J. Soffer, and W. Vogelsang, Ann. Rev. Nucl. Part. Sci. 50, 525
(2000).
[8] V. Barone, F. Bradamante, and A. Martin, Prog. Part. Nucl. Phys. 65, 267 (2010).
[9] M. Harrison, S. Peggs, and T. Roser, Ann. Rev. Nucl. Part. Sci. 52, 425 (2002).
[10] I. Alekseev et al., Nucl. Instrum. Methods A499, 392 (2003).
[11] Ya.S. Derbenev, et al., Part. Accel. 8, 115 (1978).
[12] K.H. Ackermann et al., Nucl. Instrum. Methods A499, 624 (2003).
[13] M. Beddo et al., Nucl. Instrum. Methods A 499 (2003) 725.
[14] C.E. Allgower, et al., Nucl. Instrum. Methods A499, 740 (2003).
[15] J. Thomas, “STAR Mid-Rapidity Upgrades: The Detector Gets Even Better,”
RHIC News (May 8, 2007).
[16] F. Sauli, Nucl. Instrum. Methods A386, 531 (1997).
[17] Tech-Etch Corp, 45 Aldrin Rd, Plymouth, MA 02360.
62
[18] F. Simon et al., Nucl. Instrum. Methods A598, 432 (2009).
[19] F. Sauli, Nucl. Instrum. Methods A522, 93 (2004), and references therein.
[20] G. Visser, “STAR Forward GEM Tracker Numbering Conventions and Hardware Data
Format Specification,” Indiana University Document, 2012 (unpublished). See
http://npvm.ceem.indiana.edu/~gvisser/STAR/FGT/FGT_Numbering_Scheme_and_Data
_Format.pdf
[21] L. Jones, “APV25-S1 User Guide,” 2001. See http://hep.ucsb.edu/people/affolder/
User_Guide_2.2.pdf
[22] J. Balewski, “Master Mapping FGT 2012,” The STAR Experiment Drupal, 2012
(unpublished).
[23] B. Surrow, presented at FGT Schedule Meeting, Brookhaven National Laboratory,
Upton, NY, 2011 (unpublished).
63