Transcript PPT - Florida Institute of Technology

Status of Muon Tomography with SRS at FIT
and some early beam results with SRS
Michael Staib, Marcus Hohlmann
Florida Institute of Technology
Kondo Gnanvo
University of Virginia
RD51 Mini Week WG5
June 13, 2012
Muon Tomography for Homeland Security
• More than 23 million cargo containers and 93 million privately-owned vehicles were
processed by U.S. Customs and Border Protection in the last year.
• New requirement: 100% scanning of all U.S.-bound containers using non-intrusive
imaging equipment and radiation detection equipment to search for a nuclear threat.
Radiation
Detectors
But it is easy to avoid
passive detection of nuclear
threat material that is
looking for radiological
signatures.
Just add shielding!
Photo: Sci. Am., 04/2008
There may be a solution...
Muon Tomography Concept
Incoming muons (from
μ natural cosmic
μ rays)
μ
μ
Uranium
Iron μ
Small
Scattering
μ
Fe
U
Small
Scattering
Large
Scattering
Large
Scattering
Note: Angles
Exaggerated!
Tracking
detectors
Multiple Coulomb scattering to 1st order produces Gaussian
distribution of scattering angles θ with width σ = Θ0:
0 
13.6 MeV
cp
x
[1  0.038ln(x / X 0 )]
X0
𝑋0 =
716.4 g cm-2 ∙ A
Z Z + 1 ln⁡
(287
𝑍)
Muon Tomography with Drift Tubes
INFN
Pb W
Brass Cu
1.4 m
4.3 m
Fe
Al
3
1
2
Decision Sciences Corp.: Multi-Mode Passive
Detection System, MMPDSTM
Reconstruction of 1 inch thick Pb letters
CMS
Original idea from Los Alamos (2003):
Muon Tomography with Drift Tubes
J.A. Green, et al., “Optimizing the Tracking
Efficiency for Cosmic Ray Muon Tomography”,
LA-UR-06-8497, IEEE NSS 2006.
INFN : Muon Tomography with spare CMS
Muon Barrel Chambers (Drift Tubes)
S. Presente, et al., Nucl. Inst. and Meth.
A 604 (2009) 738-746.
Decision Sciences prototype using drift
tubes large enough to scan a vehicle.
C. Milner, et al., “Non-Invasive Imaging of
Reactor Cores Using Cosmic Ray Muons”, SMU
Physics Department Seminar, March 2012.
Compact Cubic-Foot Muon Tomography Station with GEMs
Plastic Scintillator
Triple-GEM Detector
~ 1 ft3
Two of the GEM detectors
used were assembled at
Florida Tech
Discriminator and
coincidence card
SRS for Muon Tomography
Current station configuration with 8 detectors:
• 96 APV Hybrid (48 M/S pairs)
• 6 ADC/FEC cards
• 2 Gigabit network switches
Six 25 ns frames of data recorded for each APV
per trigger yields event size of ~200kb @ 30
Hz.
DATE for data acquisition.
AMORE for data decoding, event monitoring
and data analysis.
6
Tomographic POCA Reconstructions of Target Scenarios
Tomographic Reconstructions Presented
• Material discrimination performance using five
targets.
Object
Reconstruction Algorithm
Point of Closest Approach
(POCA)

• Depleted uranium shielded with medium-Z
shielding.
POCA Reconstruction Limitations
𝜃 = cos −1
𝑨 ∙𝑩
𝑨 𝑩
The POCA can be found using the
fact that the shortest line segment
joining the incoming and outgoing
vectors will be orthogonal to both.
• Assumes multiple scattering is well approximated
by a single point.
• Not valid in the case of large amounts of material!
Statistical methods must be employed.
• Does not take into account the momentum of the
muon.
Five-Target Scenario
Five 75 cm3 targets were placed inside the imaging volume at three different Z locations.
Lead
Z = 82
ρ = 11.4 g/cm3
X0 = 0.56 cm
Depleted Uranium
Z = 92
ρ = 19.0 g/cm3
X0 = 0.32 cm
Tungsten
Z = 74
ρ = 19.3 g/cm3
X0 = 0.35 cm
6mm Al shielding
Tin
Z = 50
ρ = 7.3 g/cm3
X0 = 1.21 cm
Iron
Z = 26
ρ = 7.9 g/cm3
X0 = 1.76 cm
Five-Target Scenario
Results are good!
W
Pb
U
Can discriminate between high/low Z as
well as high/medium Z.
Tungsten vs. Uranium not so easy...
Results match 1/X0
dependence quite well
Sn
Single cluster track selection
155,104 reconstructed tracks
NNP cut = 5
2 mm x 2 mm x 40 mm voxels
Fe
Single cluster track selection
155,104 reconstructed tracks
NNP cut = 5
2 mm x 2 mm x 40 mm voxels
Five-Target Scenario
XZ Slices
Sn
Fe
U
Pb
W
+Y
+X
-70 mm < Y < -30 mm
-20 mm < Y < 20 mm
30 mm < Y < 70 mm
Pb
W
Sn
Fe
YZ Slices
Sn
Pb
-70 mm < X < -30 mm
U
-20 mm < X < 20 mm
Fe
W
30 mm < X < 70 mm
Stacked Five-Target Scenario
• Stacks of each of the five materials were imaged using the MTS
• Targets vary in size from 27 cm3 to 150 cm3
• 175,022 tracks reconstructed using single cluster selection
Stacked Five-Target Scenario
40 mm XY slice descending in Z
by 5 mm per frame
40 mm slice
Simple Scattering Density [deg/cm3]
Uranium
Tungsten
Lead
Tin
Iron
152.8
140.6
112.2
72.9
64.1
We are able to discriminate between the low/medium/high-Z
materials!
Single cluster track selection
175,022 reconstructed tracks
NNP cut = 6
2 mm x 2 mm x 40 mm voxels
Stacked Five-Target Scenario
XZ Slices
Sn
Single cluster track selection
175,022 reconstructed tracks
NNP cut = 6
2 mm x 2 mm x 40 mm voxels
U
Pb
W
U
Fe
W
Fe
YZ Slices
Sn
Pb
Depleted Uranium with Bronze Shielding
40 mm XY slice with NNP cut increasing by 1 per frame
The shielded uranium can
be discriminated from the
bronze shielding using
POCA reconstruction
Mixed track selection
187,731 reconstructed tracks
2 mm x 2 mm x 40 mm voxels
Depleted Uranium with Bronze Shielding
What about the side views?
XZ slice with NNP cut increasing by 1 per frame
The shielded uranium can
be discriminated from the
bronze shielding using
POCA reconstruction
YZ slice with NNP cut increasing by 1 per frame
Mixed track selection
187,731 reconstructed tracks
2 mm x 2 mm x 40 mm voxels
Status of Muon Tomography
• We have shown the ability of the MTS using GEMs to discriminate
between materials of similar volume with different Z, even as
shielding.
• SRS is working very well!
• Still unresolved issue of network switch requirements and exact
cause of missing triggers.
• Will try to implement the zero suppression firmware soon and work
on clock synchronization.
• Plans to possibly scale to ~1 m3 active volume in the future.
• Many thanks to Sorin, Hans, Filippo and Leszek for their help
throughout the process.
Beam Test 2012
Zig-Zag (Chevron) strips to reduce readout channels while maintaining spatial resolution
2 mm
2 mm
CAD Design by C. Pancake, Stony Brook
Preliminary
Results
Zero Suppression
Raw Data
48 Zig-Zag
RO Strips
Pedestal Subtracted Data
Floating channels
(not connected)
Zero Suppressed (5σ RMS) Data
Strip Number
Time Evolution of Zero Suppressed Signal
Pedestal Noise
Cluster Size Distribution
Cluster Charge Distribution
Cluster Multiplicity
Mean = 1.1 Clusters
Mean = 2.7 Strips
Beam Test 2012
New RD51 tracker with resistive strip MicroMegas and SRS APV readout
Readout Strips parallel to resistive strips
Readout perpendicular to resistive strips
Thanks!
Questions?
Backup Slides
Post-Processing to Remove Noise
• A “number of neighboring POCA ” (NNP) cut is made in order to improve the quality of the
reconstructions.
• There is also a cut removing all voxels with mean scattering angle less than 2 degrees.
Method
V
• Add up the total number of POCA
points in the blue voxels surrounding
voxel V, this is the NNP.
• If the NNP is less than a threshold,
remove the contents of voxel V.
• Repeat for all voxels in the histogram.
Results