Interactions of Neutrons with Silicon CCD Chips
MASSA CHUSETTS INSTITUTE
F TECHNOLOGY
by
O
I
JN 0 8 2011
Timur Cemal Sahin
Submitted to the Department of Physics
in partial ffnlfillment of the requirements for the degree of
LIBRARIES
ARCHIVES
Bachelor of Science in Physics
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
February 2011
0 Timur Cemal Sahin, MMXI. All rights reserved.
The author hereby grants to MIT permission to reproduce and
distribute publicly paper and electronic copies of this thesis document
in whole or in part.
A u th or ...............................
Department of Physics
7
May 18, 2010
Certified by.........
Denis Dujmic
Research Scientist
Certified by..................
Gabriella bcioia
Associate Professor of Physics
supervisor
Accepted by ......
Professor David E. Pritchard
Senior Thesis Coordinator, Department of Physics
2
Interactions of Neutrons with Silicon CCD Chips
by
Timur Cemal Sahin
Submitted to the Department of Physics
on May 18, 2010, in partial fulfillment of the
requirements for the degree of
Bachelor of Science in Physics
Abstract
Dark matter makes up approximately 22% of the energy density of the universe and
as much as 83% of its matter composition. Despite its ubiquitous nature, it remains
incredibly difficult to detect due to the weakness of its interaction with the regular
matter. The Dark Matter Time Projection Chamber (DMTPC) is an experiment
that searches for traces of ionization created by Weakly Interacting Massive Particles
(WIMP's). The detector uses a charge coupled device (CCD) camera to image the
ionization signal created in the detector gas. The CCD chip itself is also sensitive to
interactions with the WIMP's and the background radiation. In this thesis I explore
the contributions these interactions may have on the DMTPC experiment.
First, I develop an algorithm that filters out the electronic noise in the CCD chip
such that the remaining images contain true ionization events in the chip.
Second, I study insidious effects of neutron interaction with the CCD chip. I
develop a GEANT4 based Monte Carlo simulation and set up an experiment that
uses a neutron source with a known energy and measure the energy deposition in the
chip. The energy spectrum agrees with the prediction based on the elastic scattering
kinematics and the silicon ionization rate thus providing an energy calibration.
Finally, I measure the level of background in the CCD chip coming from the
inside of the camera, I set up an experiment in which outside neutrons are shielded
with layers of plastic material and x-rays are suppressed with lead bricks surrounding
the camera. Cosmic muons create particle showers that can also interact with the
CCD chip so I build an active shield using a pair of scintillating paddles. I find that
background interactions with silicon produce CCD signals that are small enough to
be eliminated by existing DMTPC cuts on interaction range.
Thesis Supervisor: Denis Dujmic
Title: Research Scientist
Thesis Supervisor: Gabriella Sciolla
Title: Associate Professor of Physics
4
Acknowledgments
I would like to thank my thesis advisor Dr. Denis Dujmic for his substantial assistance
and mentorship in this project from its inception through its completion, and for his
guidance in personally and professionally trying times. I would also like to thank
my advisor Gabriella Sciolla for her support and contributions to this work. I also
thank Shawn Henderson, Jeremy Lopez, and Cosmin Deaconu for their assistance
with matters of ROOT, Linux/Unix, and C++ programming. Finally, I would like
to extend my gratitude to the John S. Reed Foundation for providing the grant for
my original undergraduate research, from which this thesis has evolved.
6
Contents
13
1 Introduction
1.1
The Dark Matter Problem . . . . . . . . . . . . . . . . . . . . . . . .
1.2
DMTPC Experiment.....................
1.3
CCD Principles......................
.. .
. . . . ...
14
. . ...
15
19
2 Interactions in CCD
2.1
2.2
3
13
.
. . ...
19
2.1.1
Scattering Rate and Cross Section.......... .
. . ...
19
2.1.2
Elastic Scattering Kinematics..............
. . ...
20
2.1.3
Stopping Power..................
. . ...
21
. . . . ...
24
Neutron Interactions in Silicon.................
...
Cosmic Ray Interactions in Silicon.............
2.2.1
Direct Ionization by Cosmic Muons . . . . . . . . . . . . . . .
2.2.2
Ionization by Muon-Induced Showers..........
2.2.3
Cosmic Ray Coincidence Setup...........
. ...
25
. . . . ...
25
27
Data Reduction and Analysis
3.1
Processing of Scintillator Signals...............
3.2
Image Processing............ . . . . . .
24
. . ...
27
. . . . . . . . ...
27
.
3.2.1
Hot Pixels and Background Cleaning . . . . . . . . . . . . . .
27
3.2.2
Recognition of Significant Pixels... . . . . . . . . .
. . . .
30
. . . . . . . . .
32
. . . . .
35
. . . . . . . . .
36
3.3
Measurement of Neutron Interaction Spectrum. .
3.4
Measurement of Background Interaction Spectrum... . .
3.4.1
Unshielded Spectrum......... . . . . .
3.4.2
Passive Neutron and Gamma Shielding . . . . . . . . . . . . .
36
3.4.3
Active Cosmic Ray Vetoing
36
. . . . . . . . . . . . . . . . . . .
4 Conclusions
37
A The McDark Simulation
39
A.1
Detector Geometry and Hit Recording....... . . . . . .
. . ..
A.2 Physics Process Selection . . . . . . . . . . . . . . . . . . . . . . . . .
A.2.1
Electromagnetic..................
A .2.2
O ptical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A.2.3
Hadronic........................
A.2.4
Decay.
.
. . . ..
.
.........................
A.3 Event Generation....................
. . . .
. . ..
39
40
40
41
. . . .
41
. . ..
42
. . . . .
42
List of Figures
1-1
The DMTPC 1OL detector in successive stages of assembly. . . . . . .
1-2
Monte Carlo simulation of the 10L detector that I developed as a part
14
of this thesis. Plots show sensitive volumes of the TPC's and CCD
ch ip s.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15
1-3
Diagram of two adjacent CCD cells. Every third electrode is connected. 16
1-4
Diagram of CCD readout..................
1-5
Electron motion through CCD cells. . . . . . . . . . . . . . . . . . . .
18
2-1
Neutron gun opposite CCD camera . . . . . . . . . . . . . . . . . . .
20
2-2
o- for elastic scattering of neutrons on silicon v.s. energy of neutrons.
21
2-3
Quenching Factor Q(E).
22
2-4
Stopping power and ionization rate for silicon ion in silicon. .....
23
2-5
Scintillator coincidence circuit...........
. . . . ...
26
3-1
Examples of scintillator PMT response.............
. . ...
28
3-2
Distribution of significant clusters across CCD bins.....
. . ...
29
3-3
Example images of hot pixels in background runs. . . . . . . . . . . .
3-4
Frequency with which significant clusters were located in a given pixel
for one run. ...
. . . . ...
..................
. ....
. . . . .
..................
....
...
. ........
17
30
31
3-5
Neutron Interactions........... . . . . . . .
. . . . .
33
3-6
Example images from neutron interactions. . . . . . . . . . . . . . . .
34
3-7
Unshielded and shielded reconstructed background spectra
. . . . . .
35
3-8
Ratio of events from shielding and muon cuts. . . . . . . . . . . . . .
36
. . . .
10
List of Tables
2.1
Parameters used in rate calculation.
3.1
Cluster event rate with shielding.
12
Chapter 1
Introduction
1.1
The Dark Matter Problem
Current astronomical observations seem to indicate that visible light and matter
constitute a relatively small fraction of the total energy density in the universe. The
discrepency was first discovered by analyzing the velocities of galaxies in the Coma
cluster and concluding that the calculated mass exceeded the observed mass by a large
factor
[1].
Further studies have shown that the Coma cluster is by no means unique
and that similar mechanics govern the majority of observed spiral galaxies, including
the Milky Way. This unseen "dark matter" seems to comprise approximately 23% of
the total energy density or approximately 80% of the mass of the universe[2]. The dark
matter has gravitational interaction and small coupling to with regular matter, but
little else is known about it. Recent studies have focused on an attractive dark matter
candidate known as the Weakly Interacting Massive Particle (WIMP). Current direct
WIMP detection experiments attempt to identify WIMPs interacting with nuclei to
produce a low energy recoil.
Most experiments look for the energy deposited by
these recoils. Some detectors, such as the Dark Matter Time Projection Chamber
(DMTPC), also attempt to identify the the direction of the incoming WIMP in the
collision[3].
1.2
DMTPC Experiment
The Dark Matter Time Projection Chamber (DMTPC) detector consists of a stainless
steel vessel filled with CF 4 gas kept at approximately 75 Torr. The vessel is divided
into two optically isolated volumes, each housing a TPC (with fiducial volumes 14.6 x
14.6 x 19.7 cm3 and 15.9 x 15.9 x 19.7 cm3 ). A WIMP interacts with a, gas nucleus
that recoils and ionizes the residual gas molecules. In order to detect the ionization
electrons, we apply an electric field throughout the gas that drifts the electrons toward
an amplification plane where they create electron and photon avalanches. The cathode
and ground plane of the TPC are meshes with diameter 27 cm and 256im pitch [4].
The electric field is approximately uniform (0.25 kV/cm) throughout the drift volume
and sharply approaches higher values (14.4 kV/cm) near the amplification region. The
produced photons are captured optically by a Charge Coupled Device (CCD) camera
located at the top and bottom of the vessel. This setup is presented in Fig. 1-1. Part
of the Geant4 rendering is visible in Fig. 1-2.
The CCD camera images photons created in the TPC, but the CCD chip is also
sensitive to radiation that interacts with the chip directly. The goal of this thesis
is to investigate how neutron interactions with silicon CCDs can contribute to the
background in the DMTPC experiment.
Figure 1-1: The DMTPC 10L detector in successive stages of assembly.
Figure 1-2: Monte Carlo simulation of the 1OL detector that I developed as a part of
this thesis. Plots show sensitive volumes of the TPC's and CCD chips.
1.3
CCD Principles
The image area of the CCD is a silicon wafer that operates by using the photoelectric
effect to convert incoming photons into an organized electron charge. A photon striking a pixel in a CCD will excite electrons from the valence band into the conduction
band of the silicon material. An electric field pattern applied across the cells keeps the
electrons localized. The charge collected in a potential well is linearly proportional to
the amount of incident light and non-linearly dependent on wavelength[5]. Through
this process, a pixel of a CCD can collect charges directly proportional to the light
falling on that pixel. However, anything that can free electrons from the valence band
can contribute to this collection of charge. Indeed, we can measure the processes described above by exploiting this property. In addition, thermal excitations can also
be a noise source that becomes more dramatic at higher temperatures. The signal
from thermally generated electrons is known as "dark current."
The CCD collects charge during the exposure period, during which the shutter
may be left open or closed. For all these measurements, we are interested in only the
background sources so the shutter is left closed. After the exposure period, the charges
are shifted from adjacent cell to adjacent cell, with the furthest column depositing its
charge into a serial register which digitizes the signal from each pixel, one by one. This
shifting is accomplished by modulating the voltages on the electrodes connected to
each individual pixel After a row is read out, the charge again shifts one pixel towards
the register, until the entire image has been read out. This process is illustrated in
Fig. 1-4 and Fig. 1-5. It is possible for radiation interactions to occur during this
read-out phase as well as the exposure phase, so it is best to keep this read-out time
to a minimum compared to the exposure time.
Au Electrodes
- 5pm
Si
24 pm
Figure 1-3: Diagram of two adjacent CCD cells. Every third electrode is connected.
For the DMTPC experiment, we make use of an Apogee CCD camera (S/N A80333
and A80334) in order to image a region of CF 4 gas. The particular CCD cameras we
use consist of a silicon chip divided into 1024 by 1024 sections. We rebin the pixels
into a 256 by 256 matrix, such that each virtual pixel represents 16 pixels. We are
particularly concerned with nuclear recoils on the order of several keV which produce
a track length of about or less than 2 mm. These recoils can easily produce tracks
that occupy only one or two virtual pixels (particularly if their momentum is mostly
perpendicular to the CCD chip).
In principle, there are a number of sources that can deposit a great deal of energy
into one virtual pixel in the absence of a nuclear recoil within the CF 4 . The silicon
CCD chip can interact with with cosmic rays, neutrons, and x-rays and produce an
image containing a track when no event occurs within the TPC. Neutrons and x-rays
can come from external sources or from impurities within the camera itself.
Silicon CCD
Al
A2 A3
B1
B2 B3 B4
A4
C1
C2 C3
A12
Al
A2 A3
12
B1
B2 B3 B4
C6 C7 C8 C9 C10 C11 C12
C1
C2
A5 A6
A7 A8
B6 B7
B5
C4 C5
Silicon CCD
SerialRegister
A9 A101 1
B8 B9 BlOB11
A4
Serial Register
A5 A6
A7 A8 A9 A10 Al1
B8 B9 B1 B11
B5
B6
B7
C3 C4 C5
C6
C7 C8 C9 C10 C11
D7 D8 D9 Dl D11
Dl
D2
D3 D4 D5
D6 D7 D8 D9 DIOD11 D12
D1
D2 D3 D4 D5
D6
El
E2
E3 E4 E5
E6
E7
E8 E9 E10 Ell E12
El
E2
E3 E4 E5
E6
E7 E8 E9 E10 Ell
Fl
F2 F3 F4
F6
F7
F8 F9
Fl
F2 F3 F4
F5
F6
F7 F8
Gl
G2 G3 G4 G5 G6 G7
Gl
G2 G3 G4
G5 G6
HI
H2
HI
H2 H3 H4
H5
F5
H3 H4 H5
F10 Fl1F12
G8 G9 G10G11G12
H6 H7 H8 H9 H10H1Il H12
18 19 110 ill 112 ->
12 113
L
11
12 13
14
F9 F1O F1l
G7 G8 G9 GlG11
H6 H7 H8 H9
Hi H11
IS 16 17 18 19 li0 111
Ouput amplifier
Ouput amplifier
(a) An image is recorded onto the CCD silicon. (b) Extreme pixels are transferred to serial register.
Silicon CCD
Al
A2 A3
A4
Silicon CCD
SerialRegister
Serial Register
A7 A8 A9 A10 --
A2 A3
B6 B7 B8 89 B10 811
B1
B2 B3 B4
B5
B6 B7
B8 B9 B10
-
811
-
011
A7 A8 A9 Al0 All
A4
A5 A6
A1
A5 A6
All
B1
B2 B3 B4
C1
C2 C3
C4 C5
C6 C7 C8 C9 C10 C11
C1
C2 C3 C4 C5
C6 C7
C8 C9
D1
D2 D3
D4 D5
D6 D7 D8 D9 D10 D11
D1
D2 D3 D4
D5
D6 D7
D8 D9 D10 --
D11
El
E2
E3 E4
E5
E6 E7
E3 E4 E5
E6 E7
E8 E9 E10 --
Ell
F1
F2 F3 F4
F5
F6
F7 F8 F9 F10 ->
Fll
G1
G2 G3 G4 G5 G6 G7 G8
Hi
H2
H3 H4 H5
11
12
13
B5
El E2
E8 E9 E10 E11
F7 F8 F9 F10 Fli
H6 H7
G9 Gl G11
H8 H9 H1
Hi1
F2 F3 F4
F5
G1
G2 G3 G4
G5 G6 G7 G8 G9
H1
H2 H3 H4
H5
H6
14 15
6
11
1101Ill
Ouput amplifier
Fl
12 13
F6
10
10 --
H7 H8 H9 Hl
17
-
18 19 I10j-
Gll
H1l
111
Ouput amplifier
1
(c) Signal in register is digitized by output amplifier.
(d) The process repeats to completion.
Figure 1-4: Diagram of CCD readout
17
J
~
-f
.............................
---------..........
..........
...........
................
.................
(d)
...................
............
................
.................
.............
................
...
............
.................
...........
..........
-----------
%%
(g)
L
%%
411
(h)
Figure 1-5: Electron motion through CCD cells. Red coloring indicates a positive
potential on the gold electrodes.
Chapter 2
Interactions in CCD
2.1
Neutron Interactions in Silicon
Unlike charged particles, neutrons can travel long distances without interacting in
matter.
Neutrons will tend to interact with matter through either scattering or
absorption. Neutron scattering can occur elastically (where energy is conserved and
transferred into the kinetic energy of a recoiling nucleus) or inelastically (where the
recoil nucleus enters an excited state).
Absorption can result in the emission of a
wide variety of radiation or a fission reaction.
2.1.1
Scattering Rate and Cross Section
We produce neutrons through the reaction 2 H + 3 H -
He + n, producing monoener-
getic neutrons with energy 14.1 MeV[6]. The Apogee CCD camera is placed on end
opposite the neutron beam as depicted in Fig. 2-1.
We can express the elastic scattering rate R in number of reactions per unit volume
target as:
R
where <D
= <}, X JEL X PSi X
(2.1)
is the neutron flux from the source (in 1/area/time)), oEL is the elastic
scattering cross section (area), psi is the density of atoms in Silicon (1/volume), and
Q is the solid angle of the target at a distance from the source. Evaluating these
Figure 2-1: Neutron gun opposite CCD camera
quantities for our silicon CCD chip at a distance of 1.4 meters, we find a neutronsilicon interaction rate of R ~ 12 cm-3s,
or on the order of 0.035 Hz for a block of
silicon with the dimensions of our CCD chip.
0EL
psi
Q
Vsi
3.6 x 106 cm-2s-1)
0.68 b
5 x 1022 cm-3
105pm x 24mm x 24mm
Table 2.1: Parameters used in rate calculation.
2.1.2
Elastic Scattering Kinematics
For a neutron (mass mn and velocity v,) striking a nucleus at rest with mass M,
we can write the following nonrelativistic conservation of energy and momentum
relationships:
1
2
2
1
2
'2+
1MV2
2
mnevn =mnv + MV
(2.2)
(2.3)
E-5
E-4
E-3
E-2
E-1
E+O
E+1
E+2
E+3
E+4
E+5
Incident Neutron Energy (eV)
Figure 2-2: o for elastic scattering of neutrons on silicon v.s. energy of neutrons.
Where ' is the velocity of the neutron after collision and V is the velocity of the
recoil nucleus. We can solve these simple equations for v:
,
A - m,,
(2.4)
M + mi,
and then use the conservation of energy to find the maximum energy transfer from
the neutron to the recoil nucleus:
1
AEnax = -m
2
1
2
-
/2
m,v,=
2
4Mm,, £
(M + mn) 2
(2.5)
where E =mo2/2 is the neutron's initial kinetic energy. For a 14.1 MeV neutron
hitting a silicon-28 nucleus, AEmax ~ 1.10 MeV.
2.1.3
Stopping Power
We also need to understand the rate at which charged particles lose energy in silicon.
The stopping power (-dE/dx) is the instanteneous energy loss per unit length of a
particle travelling through a medium. In general, the quantity dE/dx depends on
the energy already lost, so we are interested in the graph dE/dx vs.
E. Though
in principle one can utilize the Bethe equation to calculate the stopping power, it
suffices to use the databases provided by software like SRIM and Geant4. The energy
lost by charged particles travelling through the silicon in this way is deposited locally
resulting in ionization. We see in Fig. 2-4 for recoil energies above 1 MeV, the elastic
component of the stopping power is the dominating factor. We are also interested
in the quenching factor, or the efficiency of conversion of nuclear recoil energy into
light relative to electrons. The form of this quenching factor was extrapolated from
Dougherty's data using an empirically determined functional form Q(E)
= (1 -
exp (-aE))[8]. This form allows for the slow expontential rise and has an upper
bound of unity. We find a = 0.164 and b = 0.302. A plot of the quenching factor is
available in Fig. 2-3.
0.6
0.4
0.2k
0
Energy (keV)
Figure 2-3: Quenching Factor Q(E)
E
E
x
106
10
102
103
104
Energy (keV)
Figure 2-4: Stopping power and ionization rate for silicon ion in silicon.
2.2
Cosmic Ray Interactions in Silicon
In order to identify any correlation between incident cosmic rays and the appearance
of one-pixel artifacts, we isolate the CCD camera from the TPC and construct a
simple coincidence setup. We place a small plastic Hamamatsu scintillator above our
TPC and a large liquid scintillator undernearth. The Hamamatsu scintillator has a
width and depth just greater than the side length of the CCD chip, and a length that
far exceeds that of the chip and the camera itself. The face of the liquid scintillator is
much greater than the area of the chip (Fig. 2-5). We synchronize digitizers and the
camera such that the signals from the scintillators are digitized and recorded during
any particular CCD exposure.
In order to study the effects of external neutrons and x-rays, we also construct a
shield out of polyethylene boards and lead bricks. A cavity holds the CCD camera
and optionally the scintillators, with approximately one inch of polyethylene and two
inches of lead on any side of the setup.
2.2.1
Direct Ionization by Cosmic Muons
Because muons and ions are heavy charged particles, they can interact electromagnetically with the silicon target atoms. For muons with high velocities (high enough
to reach the surface of the earth), the majority of their energy loss will occur through
ionization and excitation of atoms. The equation governing the maximum energy
transfer kinematically identical to Eq. 2.5. We can evaluate this equation for a muon
striking an electron:
A Emax
4mem 22 E ~ 0.019E
(me + mP)
(2.6)
Which tells us that the muon loses only a small fraction of its energy per electronmuon collision. If we wish to consider the relativistic effects, we can expand Eq. 2.6
and recover
AEmax
-
2V
2- 2 mc2
2
(2.7)
where in the last step we used the approximation y}m/I << 1. For a typical
1 GeV muon travelling at 99% the speed of light, AEmax/E a 0.05.
1/
1 -/32
and /3
where -y =
V/c. This low fractional energy deposition per collision indicates
that these particles will, in the absence of any external electric fields, travel in fairly
straight lines through the medium.
2.2.2
Ionization by Muon-Induced Showers
here is also the possibility of ionization from pt showers rather than direct ionization.
The expected rate of muons at sea level is approximately 1 cm-2 min-.
For our CCD
chip this equals approximately 0.1 per second. Assuming the branching fraction for
muons to neutrons is approximately the same as the fraction for muons to charged
particles, we expect something on the order of 10-' g-1 cm
rate of neutron production from muons R,-,,,
2
neutrons per muon. The
in a material is then:
R,~,~R~x10c 2 xP x Ad
R(_.n = R xP (g/cm2)
(2.8)
where RP is the rate of muons entering the medium, p is the medium's density and
Ad is the penetration depth. For a silicon chip (p = 2.3 g/cm 3 , Ad = 5 x 10-4 cm11),
R-~0/s. For a lead brick (p = 11.9 g/cm3 , Ad = 5 cm), R,
2.2.3
5 x 10/s.
Cosmic Ray Coincidence Setup
A long, thin Hamamatsu scintillator rests atop the Apogee camera located above the
CCD chip. Underneath we have placed a large oil scintillator. PMTs are connected
to amplifiers and digitizers which read out and record the amplified output signal. At
sea level, we expect a muon to penetrate the top scintillator at a rate of approximately
one per second. The actual rate taking into account the possibility of oblique muons
is closer to 1.3 per second, however these oblique muons are less likely to penetrate the
Figure 2-5: Scintillator coincidence circuit.
ccd chip after striking the scintillator. A muon passing through the top scintillator will
trigger readout on the bottom scintillator. Due to the large size of the oil scintillator,
it is almost guaranteed that muons penetrating the top scintillator will go on to
penetrate the bottom. The area of the top scintillator far exceeds the area of the
CCD chip. Only about 7% of the cosmic rays responsible for coincidence triggers
should penetrate the CCD chip.
Chapter 3
Data Reduction and Analysis
3.1
Processing of Scintillator Signals
We scan the waveforms on the scintillators for photopeaks and determine the time
difference between peak locations on the top and bottom scintillators. We collect all
waveforms that appear in the scintillator during the exposure. The top scintillator
acts as a trigger which begins the readout and digitization of signals from both top
and bottom scintillators. Examples coinciding and noncoincident peaks are available
in Fig. 3-1.
3.2
3.2.1
Image Processing
Hot Pixels and Background Cleaning
Impurities in the silicon chip can cause the presence of "hot pixels," or pixels that
consistently record a high number of counts regardless of photon absorption or other
external energy deposition. We employ a number of methods in order to account for
these hot pixels and remove them from our data set.
As a relatively simple first cut, we can attempt to identify hot pixels by studying
images taken with the camera shutter closed. In these "background runs" we expect
the mean number of counts collected in each CCD pixel to be relatively low. If this
Time (s)
Time (s)
0
0
-0. -
-Wm
-0.2 -
-0.2-0.4 --
.04
0
0.05
0.1
S10
02.3-f
-
0
0.05
Time(s)
(a) Coincident case
0.1
10
Time(s)
(b) Anticoincident case
Figure 3-1: Examples of scintillator PMT response. Top and bottom graphs represent
top and bottom PMTs, respectively.
is the case, we can look for hot pixels by taking all the exposures in a background
run and summing them pixel for pixel. As the appearance of true one-pixel events
should be distributed evenly throughout the area of the CCD chip, the vast majority
of pixels in the summed image tend to have approximately identical number of ADU
counts. Hot pixels, however, can accumulate orders of magnitude more counts in this
process. We find the mean of number of counts in the histogram, as well as the RMS
deviation from the mean, and identify pixels whose values are more than 5 x RMS
greater than the mean. These pixels are discounted from analysis.
Although this method is effective at removing the majority of hot pixels, it does
not completely eliminate hot pixels. The remaining hot pixels were discerned using
frequency analysis on the significant clusters. They get recognized as significant onepixel clusters and have their location recorded. If we assume that the appearance of
such events is again statistically uniform across the CCD, we expect to see a Poisson
distribution with most pixels having zero events, a few having one, even fewer having
two, and so on. The expected value for the number of counts is calculated by dividing
the number of worms surviving the first cut by the total number of pixels. We then
cut out all events located in clusters which recorded more than 5c- events from this
mean. Though the vast majority of pixels follow this distribution, hot pixels can have
as many as several hundred such recorded events. These pixels are discounted from
the analysis.
For example, Fig. 3-2 shows the number of worms found in each pixel across 5000
1-second exposures. Each pixel is uniquely numbered between 0 and 2582 (256 pixels
+ 2 underflow/overflow bins that are an artifact of the format used to store the
histogram).
Un
E
I
I
20000
40000
I
0
z
L_
10 3
102
10
60000
Pixel No.
Figure 3-2: Distribution of significant clusters across CCD bins
Identifying hot pixels is necessarily a multi-pass process, in part because the
threshold for identifying these pixels is in part influenced by their presence. Discarding outliers while setting the threshold will keep the worst offenders from interfering,
but hot pixels with far fewer counts are still present after the first pass. In addition
to the threshold-setting component, a hot pixel is not always in an "active" state. A
hot pixel can "turn on" and "turn off" during the course of a run. Fig. 3-4 illustrates
the frequency with which a given pixel of the CCD camera was identified as being
-r250
.200
3150
-100
-
50
0
290
300
8 0
830
310
320
330
-_50
. . . 50 , , 8 ,60
840
80
80
90
100
110
120
310
320
330
340
Figure 3-3: Example images of hot pixels in background runs.
part of a significant cluster throughout one given run of 5000 one-second exposure.
Hot pixels are easily identified as the long horizontal streaks with high counts. As
stated, they have periods of high and low activity even over the course of a few hours.
Because there is no guarantee that a hot pixel is in its active state during any particular run (or even part of a run), we must perform a frequency analysis to ensure
that we account for hot pixels beneath the threshold.
3.2.2
Recognition of Significant Pixels
For each exposure in each run, we must determine which pixels or clusters of pixels
are significant and should be recorded as events or worms. We first remove all hot
pixels using the method above then recalculate the mean and RMS deviation of the
image histogram (discounting outliers). We use as our threshold the mean plus five
times the RMS.
-O
60000
---. --.-------------- .. --.
-
C~ 40000 -
.----
-1000D030013131:11.1.1
an00.
.
20000 -3
00000.
O0n a
o o.
n.
.0.
-
-
0
-
0
0.....
0 0
-
,
-
0
o .0
'
.O'
1000
a
0000
o
.00~~
.
.00.000.00000000000000.0
.00000
.000.
.
..
0.
00
I"' o .'"'O"
,""'",""
2000
00000.
0000000000
.
.
00.0000.00.
n~.
.
..... .
.
.
"1 ""1"
3000
4000
5000
Exposure number
Figure 3-4: Frequency with which significant clusters were located in a given pixel
for one run.
Starting from the pixel with the highest number of ADU counts, we check to see
if this pixel exceeds our threshold. If it does, we register it as part of a cluster and
check its neighbors (the adjacent eight pixels in each cardinal and ordinal direction)
to see if they pass the threshold. We perform this operation recursively for every
neighbor passing the thresholds, adding each such pixel to the cluster. When we have
exhausted all the neighbors, we record the total number of pixels and the sum of the
counts in each pixel. For clusters made up of more than two pixels, we attempt to
calculate the principal axes of inertia of the cluster. The cluster is then eliminated
from the image and then identification starts again from the next pixel with the next
highest counts. We repeat this process until we have exhausted all clusters in one
exposure, and again for each exposure in each run.
3.3
Measurement of Neutron Interaction Spectrum
Neutron data was collected using the method described in Chapter 2. The exposures
were run through the hot pixel process and cluster recognition algorithm.
Using
the sum of the counts from the clusters present in those images, we can rebuild
the energy spectrum. We use empirically measured ADU to energy calibration and
quenching factor to recover the following spectra. For a given number of ADU, we
work backwords knowing that
E1
NADU
X
Q(E)
x
(3.1)
W x G
Where NADU is the number of ADU recorded in the cluster,
Q is the quenching
factor
which, in general, depends on the energy, W is the work function of the electron
in silicon and G is the empirically measured gain for our particular camera. W
3.6eV/e~ and we measure our gain for this CCD camera to be G = 1.1e~/ADU.
We fired deuterons with an energy of 14.1 MeV at the CCD camera for 5000
consecutive one-second exposures. The reconstructed spectrum agrees with GEANT4
monte carlo. The Monte Carlo simulation measures the energy deposition of 14.1 MeV
neutrons into a five micron thick sheet of silicon. Here we use the Q(E) found in Fig. 23 in our conversion from ADU to energy. We scale the Geant4 energy profile such
that it has the mean rate calculated by Eq. 2.1. The measured energy spectra agree
quantitatively well with monte carlo data above 100 keV with the exception of an
aberrant peak in the measured event rate that occurs at approximately 230 keV. This
peak is present only in the measured data when the neutron source is activated. It is
unclear as to whether this is a true neutron-silicon interaction, or whether neutrons are
activating or exciting some short-lived isotope which also interacts with the CCD. The
interaction produces ADU corresponding very sharply to a 230 keV neutron event.
GEANT4 simulations of neutrons interacting with aluminum and gold (present in the
CCD camera) do not reproduce this peak. There is a qualitative agreement in the
lower-energy spectra, though measured event rates are about an order of magnitude
higher than what one calculates from GEANT4.
-
...
-
-
.........
I
-
10-1
DT (data)
DT (Geant4)
10-2
-
I
~
10-3
9
10~44
200
400
600
800
1000
Er (keV)
(a) Reconstructed Neutron Spectrum
3000
(D
LL
2000
1000
H
2
0,
0.
4
6
8
10
No. pixels in cluster
(b) Reconstructed Neutron Energy vs. Npi,
Figure 3-5: Neutron Interactions
200
-
530
540
550
560
1190
20
200
210
20
220
20
600
610
620
630
140-
130-
120
110-
100
490
500
510
Figure 3-6: Example images from neutron interactions.
520
6z
150
3.4
Measurement of Background Interaction Spectrum
In order to measure the level of background radiation in the CCD, I take data with all
sources removed from the vicinity of the camera. The remaining events in the camera
come from eitheT surrounding radiation in nature, or from the camera material itself.
In order to distringuish the two sources, I apply shielding against the environmental
radiation.
The results are summarized in Table 3.1 and Figure 3-7.
Unshielded
Shielded
Shielded with rejection
Rate (s- 1 )
30.78 x 102
6.88 x 10-2
0.19 x 10-2
Table 3.1: Cluster event rate with shielding.
.1-11
1
-
0
- - *-
-
Unshielded
-
Shielded
ShieldedwithCoincidence
Rejection
-- - ~ t 4i
10-3
I
I
10~4
10-6
10~5
I
I
. I ,,
102
103
Er (keV)
Figure 3-7: Unshielded and shielded reconstructed background spectra
3.4.1
Unshielded Spectrum
The unshielded spectrum is shown in Figure 3-7. The rate in the graph is normalized
taking into account the total exposure time. The total rate is given in Table 3.1.
3.4.2
Passive Neutron and Gamma Shielding
I surround the camera with 50 cm of Ricorad (boron-rich plastic) as a passive shielding
against neutrons, and 20 cm of lead bricks as a shielding against the gammas. The
rate normalized to the exposure time is shown in Figure 3-7, and the total rate is
give in Table 3.1. The ratio between shielded and unshielded event rates is shown in
Figure 3-8.
3.4.3
Active Cosmic Ray Vetoing
A cosmic-ray veto is set up with two scintillator paddles above and below the camera. Rejecting those events with activity in both scintillators within approximately a
microsecond, we recover the blue spectrum in Fig. 3-7. with and without coincidence
rejection are available in Fig. 3-8.
The ratio between shielded and no-coincidence
event rates is shown in Figure 3-8. The measured ratio is consistent with the geometric considerations from Section 2.2.3
600
800
101
Energy (keV)
Figure 3-8: Ratio of events from shielding and muon cuts.
Chapter 4
Conclusions
I have built a Monte Carlo model in GEANT4 that accounts for particle interactions
in both the TPC and the CCD chip of the DMTPC experiment.
I have tested
experimentally that neutron interactions in the silicon chip agree with our Monte
Carlo simulation. The majority of background interactions with silicon result in lowenergy (< 200 keV) clusters with a range of one to several pixels (Fig. 3-5).
This
overlaps partially with the spectrum we expect from dark matter candidate particle
interactions in CF 4 . However, running this neutron silicon background data through
the DMTPC cuts ([4]) reveals that no background events survive in the 80 - 200 keV
range. This is due principally to the DMTPC's range requirement and the relatively
small clusters produced by silicon CCD chip interactions. While other studies have
used radioactive sources to study interactions within the TPC gas, this thesis is the
first study on interactions directly with the CCD chip.
38
Appendix A
The McDark Simulation
A.1
Detector Geometry and Hit Recording
The geometry of the detector is described in the McDarkDetectorConstruction class.
The detector geometry includes most of the TPC vessel as well as the enclosed CF 4
gas and the silicon chip of the imaging camera.
The silicon chip is set up as a
"sensitive detector," as described in McDarkTpcSD. The inner part of the drift cage
is also set up as a sensitive detector.
Particles travelling through these "sensitive
detector" region will automatically have have their track information and energy
deposition information recorded when they interact. These interactions are saved as
hits (McDarkHit).
Electrons and photons have their quenching factor set to 1.0, whereas nuclei have
their quenching factor calculated from the relationship
Q
(0.3 xSn Se)
Sn +Se
(A.1)
where Sn is the quenching factor calculated from the nuclear stopping model from
ICRU report 49 and Se is the quenching factor for an electronic loss model calculated
by the SRIM2000 software.
All hits in these sensitive regions are converted into a representation of a digital signal (McDarkTpcDigi). The McDarkTpcDigitizer govern the details of this conversion
taking into account the area imaged by the CCD camera. The McDarkTpcDigitizer
accesses the geometry and identifies the energy deposited towards electrons and photons and the location of the ionization. The McDarkTpcDigitzer uses the McDarkTpcGas
class to perform calculations of the electron transport. This information is used to
produce an equivalent charge readout, PMT readout, and CCD signal response for
the ionization event. The virtual digitizer will loop through all PMTs and CCDs and
record this information for each one.
A.2
Physics Process Selection
The various physics processes implemented in the McDark simulation can be found in
the McDarkPhysicsList class. Our own process models are in the McDarkIonMultipleScattering
and McDarkUrbanMscModel classes, as described below.
A.2.1
Electromagnetic
We have chosen to use the various G4LowEnergy packages for electromagnetic processes, being that low energy details could affect our recovered energy spectra. For
the G4LowEnergyPhotoElectric class, this means that the simulation takes into account the relative cross-sections of all sub-shells when deciding which should release
an electron in a photoelectric interaction. The G4LowEnergyIonisation calculates
the continuous energy loss due to electron ionisation and simulates the production of
electrons from secondary ionizations. We are especially interested in the production
and energy loss of these secondaries as they contribute to the various signals in our
experiment.
This energy loss is calculated with the G4LowEnergyBremsstrahlung
class, which simulates the continuous energy loss from low energy gamma emission.
We set a lower production threshold of 250 eV, which represents the lower end of the
spectrum for which the reference data is available and reliable. Gamma interactions
also use the G4LowEnergyRayleigh and G4LowEnergyCompton processes which take
into account Hubbel's form factor for scattering, and G4LowEnergyGammaConversion
which uses the Bethe-Heitler differential cross-section with Coulomb correction for
sampling the probability of a photon to produce a given pair of particles.
Elec-
trons utilize the standard G4eMultipleScattering process in addition to the low
energy ionisation and low energy bremsstrahlung.
Muons and antimuons use the
standard G4MuMultipleScattering, G4MuIonisation, G4MuBremmstrahlung, and
G4MuPairProduction packages. In addition, the G4MuonMinusCaptureAtRest process accounts for the possibility of negative muon capture. Light ions such as protons,
alphas, and deutrons use the G4MultipleScattering and G4hLowEnergyIonisation
processes. Other nuclei, such as carbon and fluorine, use the McDarkIonMultipleScattering
particle written specifically for this simulation which incorporates the McDarkUrbanMscModel.
This class is an implementation of the multiple scattering model from H. W. Lewis
in Phys. Rev. 78 (1950). The model takes into account corrections on cross sections
and path lengths for the nuclei of interest.
A.2.2
Optical
The most important optical process for our simulation is scintillation, for which
we use the G4Scintillation class, adjusting its parameters as necessary for alphas and heavy nuclei. In addition, optical photons- use the G40pAbsorption and
G40pBoundaryProcess processes to govern their interactions.
A.2.3
Hadronic
The various mesons (pions, kaons) utilize both the appropriate low to high energy inelastic processes specified by their own GEANT4 classes (e.g. G4PionMinusInelastic,
G4LEPionMinusInelastic, and G4HEPionMinusInelastic. Protons and antiprotons
also follow this scheme. In neutrons, we consider the low to high energy processes for
both elastic and inelastic cases. We also allow for the possibility of neutron capture
with G4HadronCaptureProcess and G4NeutronHPCapture.
Deutrons, alphas, and
tritons also utilize their appropriate inelastic scattering processes.
A.2.4
Decay
All particles utilize the standard G4Decay process if decay is applicable. In addition,
ions that engage in radioactive decay use the G4RadioactiveDecay process.
A.3
Event Generation
Per GEANT4 standards, event generation is handled through the McDarkPrimaryGeneratorAction
class. This class contains the various distributions that are relevant to the experiment.
The class currently contains spectra for a particle gun with variable en-
ergy and direction, an isotropic source of variable energy, a Cf-252 source, a Co57 source, and a DT source. Additionally, the "Spergel distribution" is defined in
McDarkSpergelDistribution which implements the dark matter energy and direction dustribution described by Spergel in 1988.
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