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Fermi-LAT: A Retrospective on Design, Construction, and Operation and a Look Towards the Future Bill Atwood Dec 6, 2011 HSTD-8. Gamma Ray Pair Conversion. e-. High Electric Field. Pair. e+. High Energy Gamma Ray. Z=74 Tungsten. Energy loss mechanisms. e-. e+. g. Z. QED Process. - PowerPoint PPT Presentation
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Fermi-LAT: A Retrospective on
Design, Construction, and Operation and a
Look Towards the Future
Bill AtwoodDec 6, 2011
HSTD-8
1
Plastic Scintillation counters to veto entering charged particles
e+ e–
Tungsten Conversion Foils
Position Measuring DetectorsMeasured Track
co-ordinates
Total Absorption Calorimeter tomeasure gamma ray energy
Z
e+e-
Energy loss mechanisms
Pair Cross-Section saturates at E > 1 GeV
Gamma Ray Pair Conversion
Z=74Tungsten
e+e-High Electric
FieldHigh EnergyGamma Ray
Pair
QED Process
Splitting Function
Ee+/E
E ( = 10 MeV)
Eme
Open4
Opening Angle
Energy
From Rossi, High Energy Particles, 1952
At 100 MeVOpen ~ 1o
2
3
Previous Satellite Detectors
• 1967-1968, OSO-3 Detected Milky Way as an extended -ray source
621 -rays• 1972-1973, SAS-2, ~8,000 -rays• 1975-1982, COS-B orbit resulted in a large and
variable background of charged particles
~200,000 -rays• 1991-2000, EGRET Large effective area, good PSF,
long mission life, excellent background rejection
>1.4 × 106 -rays
SAS-2
COS-B
EGRET
OSO-3SAS-2
COS-B
EGRET
4
ConceptionGLAST was the amalgamation of many ideas and concepts from the Experimental Particle Physics in the 1980’s and early 1990’s
MACRO – Grand Saso
Modularity
ALEPH SSD Detector
Xtal CalorimeterHodoscopic Design
P. Persson – P. Carlsen
EGRET onboard CGRO
For Space Instruments: Solid State DetectorsSilicon Strip Detector: SSD
5
Evolution of GLAST• April, 1991 CGRO (with EGRET on board) Shuttle Launch• May, 1992 NASA SR & T Proposal Cycle
3. Pick the Rocket
Delta II (launch of GP-B)
4. Fill-it-up!
RocketPayload Fairing
Diameter sets transverse size
Lift capacity to LEO sets depth of Calorimeter
2. Make it Modular1. Select the Technologies
Large area SSD systemsand CsI Calorimetersresulted from SSC R&D
Another lesson learnedin the 1980's: monolithicdetectors are inferior to Segmented detectors
Cheap, reliable Communication satellite launch vehicle
Original GISMO 1 Event Displays from the first GLAST simulations
6
First Oral Presentation of GLAST: HSTD-1May, 1993
7
At this point there were just 10 collaborators!
and the Conference Proceedings…
Now over 400 and from 7 countries
8
Overview of GLAST- LAT
e+ e–
• Tracker 18 XY tracking planes
with interleaved W conversion foils. Single-sided silicon strip detectors (228 μm pitch) Measure the photon direction; gamma ID.
• Calorimeter 1536 CsI(Tl) crystals in 8 layers; PIN photodiode readouts. Hodoscopic: Measure the photon energy; image the shower.
• Anticoincidence Detector (ACD) 89 plastic scintillator tiles. Reject background of charged cosmic rays; segmentation removes self-veto effects at high energy.
Calorimeter
Tracker
ACD
• Electronics System Includes flexible, robust hardware trigger and software filters.
9
And… After 2 Years
10
Silicon Detectors: the choice that keeps on giving!
Thin detectors leads to optimal arrangement of radiators Near 100% efficiency leads to new tracking paradigms and
more Extremely low noise results in few false triggers and low
confusion in tracking Long term stability promotes optimal recon strategies Fine granularity allows for a precision snap shot of the
conversion and resulting tracks
What follows are several examples capitalizing on these properties, which were not anticipated from the outset.
Detector Layout and the PSFMultiple Scattering limits tje resolution over much of the High Energy Band
))log(038.1(014.0 RadRadp
MS in a single Converter:
Y3
Y2
Y1
X3
X2
X1
High EnergyGamma Ray
X1 is not usable
By Y1 MS =
Error Y1 – Y2:
Y Error by Y2:
X Error by X2:
Error Box Area:
01 31 Y
065 Y
034 X
2018
20 Yx
X1, Y1
X2, Y2
X3, Y3
021 YX
2
20 Yx
Ratio: Distrib./ Discrete = 1.9 (if X1 usable: Ratio =1.05)
021
The elimination of lever-arms between radiators and detectors minimizes MS effects!
Distributed Detector Discrete Detector
11
Tracking: Tracker Design and Analysis BasicsPair Conversion Telescope Layout
Effγ
Effo χ.5E
GeV14mradχpβ
GeV14mradθ
Multiple Scattering
Trim Radiator tiles tomatch active SSD area
Close spacing of Radiatorsto SSDs minimizes multiple scattering effects
mrad(100MeV)δθMS 38o
MS 3.154mradmradSpaceδθ 382)(
oDet
Det
.162.8mrad632.9mm
m228δθ
d12Pitch
dδθ
22SSD
Plane-to-plane spacingand SSD strip pitch setsmeas. precision limit
Tungsten Radiator
Si Strip Detector
converts ½ through radiator
0θ
2θ0
d
Angular Resolution Parameters
.025χ22χ(MS)χ SSDWeff
Data Analysis Techniques for High Energy Physics, R. Fruhwirth et al., (Cambridge U. Press , 2000, 2nd Edition)
Track parameters (position, angles, error
matrix) at a plane
Propagation of parameters
Multiple Scattering -- depends on energy!
Propagation of parameters
Predicted parameters
at next plane
Measurement with errorNew parameters at
next plane
Kalman Tracking/Fitting Trade-off Between Aeff & PSF
Radγ χN RadχPSFSource Sensitivity Photon Density
2γ
PSFN
Sens. Doesn't depend on Rad !
2-Source Separation pushes for thin radiators
Transient sensitivity pushes forthick radiators
12
13
Low Noise & High Efficiency Enables Trigger
*using ACD veto in hardware trigger
Hardware Trigger
Instrument Total Rate: <3 kHz>*
First Light
3-in-a-Row Rate: ~ 8 kHz
TKR trigger uses fast OR’d signals of all strips in a single plane.Coincidence formed with pair plane (x•y pairs)3 x•y pairs form the Tkr Trigger
XY
XY
XY
Tungsten Conversion FoilsConversion Point
SSD Planesx•y pairs
3-In-A-Row~ 2-3 noise hit per readout!
14
Low Noise & High Efficiency Determines Track Length
“Missing Hits” on tracks not easily excused. Check closeness to gaps Check on presences of dead strips No excuse – Track terminated at last hit
Allows testing of track hypothesis – improves track finding accuracy by eliminating false solutions
15
12.Width
Meas
12thClusterWid
Cluster
mmPitchStrip 8.6512
22812
1/2-1/2
Gaussian Equivalent for a Square Distribution
121
3
2/1
2/1
322
xdxx
-1/2
1/2
Hence
Actual “hits” on tracks are in general Clusters of Strips. Naively expect
SSD Measurement Errors
Dependence on cos()
1 GeV Muons
2 Depends on Angle
Large angles too narrow!!
…Suspect Meas. Errors
16
SSD Measurement ErrorsSSDLayer
Can move track left-rightby at most 1 strip pitch!
Fitted TrackBut…
12StripPitch
Cluster Suggests (!)
12thClusterWid
Cluster 12
StripPitchCluster
Success! 2 Distributions – Near Text-Book!-1 < cos() < 0cos() = -1
Notice the Binning Effects?<Nhits> = 36
<2> = 1.05
<Nhits> = 22<2> = 1.06
17
There’s More: Slope Dependent Hit Errorscredit: Leon Rochester
You might expect delta to be uniformly
distributed in each strip, so that the
error on each measurement would
12StripPitch
Cluster
δ
Slope is in units of stripPitch/siliconHeight(Both slopes and deltas are folded around zero.)
and
SSD Magniified
Slope
StripPitchDeviation
Distribution of vs Track Slope
18
What’s happening?There are magic slopes…
We know exactly wherethese tracks went.
1 2 3 4 5 etc.
This is the factor by which the error is less than
12StripPitch
Coupling of Slope error to position error finite – but - small
19
Backup to the ACD: SSD Veto The Anti-Coincidence Detector for the LAT is a wave-
shifting fiber based scintillation system. Science requirement was for ~ 104 : 1 rejection of entering charged particles.
Vulnerability is the accuracy of Track Finding Near 100% efficiency of the SSDs can be used to
verify the neutrality of the incoming particle Invoking the tightest cuts on the ACD only when there
were 2 - or less - “veto” SSD planes preserves efficiency
20
105 MeV Gamma
Count number of planes with hits inside cone
Tile
Ene
rgy
(MeV
)
Dist. from Tile Edge (mm)
Background
Gamma Rays
0 1&2 3&4 5&6
No. of SSD Veto Planes
Using SSD Vetos Extend Track solution backwards towards
ACD For each SSD plane crossed search of hits
within expanding cone Count No. of (SSD Veto) Planes – reset
counter to ZERO when hit plane encountered
Allows for looser ACD Cuts Preserves Efficiency (~ 95%) of ACD
cuts for Gamma Rays Results in > 104 : 1 rejection of
entering charged particles
PINK: events rejected
BLUE: events kept
21
Background Rejection via -RaysElectrons (positrons) produce more and more
energetic “knockon” electrons (-rays) then Cosmic Rays (protons)
This is just a result of “billiard-ball kinematics” and dE/dX’s relativistic rise
Granularity of SSDs allows the observance of excess hits around track
Adds considerably to Background Rejection
1 GeV e+
-Ray
Extra SSD Hits
Cosmic Rays (protons)Gamma Rays
22
Details for Counting -Ray HitsEnergy DependenceCounts Distributions
5 mm
10 mm
20 mm
The distribution of -Ray counts depends on energy. Core-Hit counts becomes very useful for -rays above ~ 300 MeV
Counts saturates at ~ 10 mm from track
Cosmic Rays
Gamma RaysEx
cess
Hits
/Tra
ck H
its
Exce
ss H
its
Z=74Tungsten
e+e-High Electric
FieldHigh EnergyGamma Ray
Pair
If the incident Gamma Ray is linearly polarized, the plane of the e+,e- pair shows a modulation in azimuth, f, about the direction of the Gamma Ray..
Details of the LAT Conversion Telescope
SUPPORT TRAY
SILICON STRIP DETECTORS
TUNGSTEN RADIATOR
Tungsten Conversion Silicon Conversions
fe+ e-
Polarization
RecoilNucleus
First 12 LAT Bi-PlanesRadiator = 2.8% (68% Convert Here)
Silicon = 2 x .4% (20% Convert Here)
Trays = .5% (12% Convert Here)
OP
TOP Conversions
BOTTOM Conversions
Detailed Vertex Topology: Polarization?
23
24
Separation of Silicon Conversions
Monte Carlo location of conversions
Overall
Tray Level
ReconstructionThe reconstruction places the start of the track in the middle of the lower SSD measuring plane or in the middle of the tungsten radiator above the upper SSD measuring plane.
THIN THICKTOP
BOTTOM
Separation Analysis
Bottom CT (easy)
TOP CT(HARD)
These include the Tungsten Conversions
25
Use Classification Trees to do separation!
26
mradEme
op 204
E = 100 MeVop = .017))ln(038.1(
26.13
EMS
MS in mrad, E in GeV, in rad. Len.
MS = 21.1 mrad for Silicon Conversions! (34.5 mrad for Tungsten Conversions)
(E = 100 MeV)
Other Angles in the Problem
All Conversions Top Silicon Conversions
27
Putting It All Together …
GammaRaysPurityQEDObs AAAA
WrongRightWrongRightAPurity
= .76
Efficiency: 294 events / 5076 events = 5.8% (Max possible: 21%) Analysis Efficiency = 27%
GammaRaysGammaRaysObs AAA 038.76.05.
This is probably a bit high as the average Xo is > .4% … As a Polarimeter, LAT has an “analyzing power” of ~ 3%
EventsNAA 1
And so it will take 111103.
1122
AnalyzerEvents A
N
to measure AGammaRays (assumed = 1.0) to 1
28
Summary & Conclusions
Thin detectors optimizes PSF by minimizing multiple scattering level arms.
Low noise and near 100% efficiency Main Instrument Trigger SSD Vetoes Track Validation
Fine granularity allows for a precision snapshot of the conversion and resulting tracks Background Rejection via -ray identification Detailed vertex topology and hit structure leads to silicon conversion separation –
Polarization? In-flight Performance: see talk by Luca Baldini