Fermi-LAT: A Retrospective on

Design, Construction, and Operation and a

Look Towards the Future

Bill Atwood

Dec 6, 2011HSTD-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-

g

Energy loss mechanisms

Pair Cross-Section saturates at Eg > 1 GeV

Gamma Ray Pair Conversion

Z=74Tungsten

e+e-High Electric

FieldHigh EnergyGamma Ray

Pair

QED Process

Splitting Function

Ee+/Eg

Eg ( = 10 MeV)

E

meOpen

4

Opening Angle

Energy

From Rossi, High Energy Particles, 1952

At 100 MeVqOpen ~ 1o

2

3

Previous Satellite Detectors

• 1967-1968, OSO-3 Detected Milky Way as an extended g-ray source

621 g-rays• 1972-1973, SAS-2, ~8,000 g-rays• 1975-1982, COS-B orbit resulted in a large and

variable background of charged particles

~200,000 g-rays• 1991-2000, EGRET Large effective area, good PSF,

long mission life, excellent background rejection

>1.4 × 106 g-rays

SAS-2

COS-B

EGRET

OSO-3

SAS-2COS-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 3

1 Y

06

5 Y

03

4 X

2018

20 Yx

X1, Y1

X2, Y2

X3, Y3

02

1 YX

2

20 Yx

Ratio: Distrib./ Discrete = 1.9 (if X1 usable: Ratio =1.05)

02

1

The elimination of lever-arms between radiators and detectors minimizes MS effects!

Distributed DetectorDiscrete Detector

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Tracking: Tracker Design and Analysis BasicsPair Conversion Telescope Layout

Effγ

Effo χ.5E

GeV14mradχ

pβ

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

d

12Pitch

dδθ

22SSD

Plane-to-plane spacingand SSD strip pitch setsmeas. precision limit

Tungsten Radiator

Si Strip Detector

g 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

PSF

NSens. Doesn't depend

on cRad !

2-Source Separation pushes for thin radiators

Transient sensitivity pushes forthick radiators

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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

g

XY

XY

XY

Tungsten Conversion FoilsConversion Point

SSD Planesx•y pairs

3-In-A-Row

~ 2-3 noise hit per readout!

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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

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12.

WidthMeas

12

thClusterWidCluster

mmPitchStrip

8.6512

228

12

1/2-1/2

Gaussian Equivalent s for a Square Distribution

12

1

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(q)

1 GeV Muons

c2 Depends on Angle

Large angles too narrow!!

…Suspect Meas. Errors

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SSD Measurement ErrorsSSDLayer

Can move track left-rightby at most 1 strip pitch!

Fitted TrackBut…

12

StripPitchCluster Suggests (!)

12

thClusterWidCluster

12

StripPitchCluster

Success! c2 Distributions – Near Text-Book!-1 < cos(q) < 0cos(q) = -1

Notice the Binning Effects?<Nhits> = 36

<c2> = 1.05

<Nhits> = 22

<c2> = 1.06

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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

12

StripPitchCluster

δ

Slope is in units of stripPitch/siliconHeight

(Both slopes and deltas are folded around zero.)

and

SSD Magniified

Slope

StripPitch

Deviation

d

Distribution of d vs Track Slope

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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

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StripPitch

Coupling of Slope error to position error finite – but - small

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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

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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

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Background Rejection via d-RaysElectrons (positrons) produce more and more

energetic “knockon” electrons (d-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+

d-Ray

Extra SSD Hits

Cosmic Rays (protons)Gamma Rays

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Details for Counting d-Ray HitsEnergy DependenceCounts Distributions

5 mm

10 mm

20 mm

The distribution of d-Ray counts depends on energy. Core-Hit counts becomes very useful for g-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-

g

Polarization

RecoilNucleus

First 12 LAT Bi-PlanesRadiator = 2.8% (68% Convert Here)

Silicon = 2 x .4% (20% Convert Here)

Trays = .5% (12% Convert Here)

qOP

TOP Conversions

BOTTOM Conversions

Detailed Vertex Topology: Polarization?

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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

mradE

meop 20

4

Eg = 100 MeVqop = .017))ln(038.1(

2

6.13

EMS

qMS in mrad, Eg in GeV, c in rad. Len.

qMS = 21.1 mrad for Silicon Conversions! (34.5 mrad for Tungsten Conversions)

(Eg = 100 MeV)

Other Angles in the Problem

All Conversions Top Silicon Conversions

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Putting It All Together …

GammaRaysPurityQEDObs AAAA

WrongRight

WrongRightAPurity

= .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%

EventsNA

A 1

And so it will take 111103.

1122

AnalyzerEvents A

N

to measure AGammaRays (assumed = 1.0) to 1s

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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 d-ray identification Detailed vertex topology and hit structure leads to silicon conversion

separation – Polarization? In-flight Performance: see talk by Luca Baldini