Fermi-LAT: A Retrospective on Design, Construction, and Operation and a Look Towards the Future Bill Atwood Dec 6, 2011

1. Fermi-LAT: A Retrospective on Design, Construction, and Operation and a Look Towards the Future Bill Atwood Dec 6, 2011 HSTD-8

2. 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 Pair Cross-Section saturates at Eg > 1 GeV  Tungsten Conversion Foils Energy Splitting Function Opening Angle Position Measuring Detectors Measured Track co-ordinates Plastic Scintillation counters to veto entering charged particles At 100 MeV qOpen ~ 1o e– e+ Eg ( = 10 MeV) Total Absorption Calorimeter to measure gamma ray energy Ee+/Eg From Rossi, High Energy Particles, 1952

3. 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 × 106g-rays Previous Satellite Detectors COS-B SAS-2 OSO-3 SAS-2 COS-B EGRET EGRET

4. Conception GLAST was the amalgamation of many ideas and concepts from the Experimental Particle Physics in the 1980’s and early 1990’s For Space Instruments: Solid State Detectors MACRO – Grand Saso Silicon Strip Detector: SSD EGRET onboard CGRO Modularity ALEPH SSD Detector Xtal Calorimeter Hodoscopic Design P. Persson – P. Carlsen

5. Evolution of GLAST • April, 1991 CGRO (with EGRET on board) Shuttle Launch • May, 1992 NASA SR & T Proposal Cycle 1. Select the Technologies 2. Make it Modular Another lesson learned in the 1980's: monolithic detectors are inferior to Segmented detectors Large area SSD systems and CsI Calorimeters resulted from SSC R&D Original GISMO 1 Event Displays from the first GLAST simulations 4. Fill-it-up! 3. Pick the Rocket Cheap, reliable Communication satellite launch vehicle Diameter sets transverse size Rocket Payload Fairing Lift capacity to LEO sets depth of Calorimeter Delta II (launch of GP-B)

6. First Oral Presentation of GLAST: HSTD-1 May, 1993

7. and the Conference Proceedings… At this point there were just 10 collaborators! Now over 400 and from 7 countries

8.  e– e+ Overview of GLAST- LAT • Tracker18 XY tracking planes with interleaved W conversion foils. Single-sided silicon strip detectors (228 μm pitch) Measure the photon direction; gamma ID. • Calorimeter1536 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. Tracker ACD Calorimeter • Electronics SystemIncludes flexible, robust hardware trigger and software filters.

9. And… After 2 Years

10. Silicon Detectors: the choice that keeps on giving! What follows are several examples capitalizing on these properties, which were not anticipated from the outset. 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

11. Detector Layout and the PSF Multiple Scattering limits tje resolution over much of the High Energy Band MS in a single Converter: Distributed Detector Discrete Detector High Energy Gamma Ray X1 X1, Y1 Y1 X2 X2, Y2 Y2 X3 X3, Y3 Y3 Ratio: Distrib./ Discrete = 1.9 (if X1 usable: Ratio =1.05) X1 is not usable By Y1 MS = Error Y1 – Y2: Y Error by Y2: X Error by X2: Error Box Area: The elimination of lever-arms between radiators and detectors minimizes MS effects!

12. Multiple Scattering Tracking: Tracker Design and Analysis Basics Angular Resolution Parameters Pair Conversion Telescope Layout g converts ½ through radiator Close spacing of Radiators to SSDs minimizes multiple scatteringeffects Tungsten Radiator Si Strip Detector Plane-to-plane spacing and SSD strip pitch sets meas. precision limit d Trim Radiator tiles to match active SSD area Kalman Tracking/Fitting Trade-off Between Aeff& PSF Track parameters (position, angles, error matrix) at a plane Source Sensitivity Photon Density Propagation of parameters Doesn't depend on cRad ! Multiple Scattering -- depends on energy! Propagation of parameters 2-Source Separation pushes for thin radiators Transient sensitivity pushes for thick radiators • Measurement with error Predicted parameters at next plane New parameters at next plane Data Analysis Techniques for High Energy Physics, R. Fruhwirth et al., (Cambridge U. Press , 2000, 2nd Edition)

13. X X Y X Y Y Low Noise & High Efficiency Enables Trigger g First Light Hardware Trigger Tungsten Conversion Foils Conversion Point TKR trigger uses fast OR’d signals of all strips in a single plane. Coincidence formed with pair plane (x•y pairs) 3x•ypairs form the Tkr Trigger x•y pairs SSD Planes 3-In-A-Row 3-in-a-Row Rate: ~ 8 kHz Instrument Total Rate: <3 kHz>* ~ 2-3 noise hit per readout! *using ACD veto in hardware trigger

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. SSD Measurement Errors Gaussian Equivalent s for a Square Distribution 1 GeV Muons Hence 1/2 Dependence on cos(q) -1/2 1/2 -1/2 Actual “hits” on tracks are in general Clusters of Strips. Naively expect c2 Depends on Angle Large angles too narrow!! …Suspect Meas. Errors

16. SSD Measurement Errors But… Fitted Track SSD Layer Suggests (!) Can move track left-right by at most 1 strip pitch! q < 45 q > 45 q > 45 q < 45 Success! c2 Distributions – Near Text-Book! -1 < cos(q) < 0 cos(q) = -1 Notice the Binning Effects? <Nhits> = 22 <c2> = 1.06 <Nhits> = 36 <c2> = 1.05

17. There’s More: Slope Dependent Hit Errorscredit: Leon Rochester Distribution of dvs Track Slope SSD Magniified d δ You might expect delta to be uniformly distributed in each strip, so that the error on each measurement would Slope Slope is in units of stripPitch/siliconHeight (Both slopes and deltas are folded around zero.) and

18. What’s happening?There are magic slopes… 5 3 4 etc. 2 1 We know exactly where these tracks went. This is the factor by which the error is less than 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. 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 Count number of planes with hits inside cone 105 MeV Gamma No. of SSD Veto Planes 5&6 0 1&2 3&4 Background PINK: events rejected Tile Energy (MeV) • Allows for looser ACD Cuts • Preserves Efficiency (~ 95%) of ACD cuts for Gamma Rays • Results in > 104 : 1 rejection of entering charged particles Gamma Rays BLUE: events kept Dist. from Tile Edge (mm)

21. Background Rejection via d-Rays • Electrons (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+ Extra SSD Hits d-Ray Gamma Rays Cosmic Rays (protons)

22. Details for Counting d-Ray Hits Counts Distributions Energy Dependence • 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 5 mm Gamma Rays 10 mm Excess Hits Excess Hits/Track Hits Cosmic Rays 20 mm

23. e- e+ f Recoil Nucleus g Polarization Detailed Vertex Topology: Polarization? 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.. e- High Electric Field Pair e+ High Energy Gamma Ray Z=74 Tungsten Details of the LAT Conversion Telescope qOP Silicon Conversions Tungsten Conversion TOP Conversions TUNGSTEN RADIATOR SILICON STRIP DETECTORS First 12 LAT Bi-Planes Radiator = 2.8% (68% Convert Here) Silicon = 2 x .4% (20% Convert Here) Trays = .5% (12% Convert Here) BOTTOM Conversions SUPPORT TRAY

24. Separation of Silicon Conversions Tray Level Monte Carlo location of conversions THIN THICK TOP Overall BOTTOM Reconstruction The 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.

25. Separation Analysis Use Classification Trees to do separation! TOP CT (HARD) Bottom CT (easy) These include the Tungsten Conversions

26. Other Angles in the Problem (Eg = 100 MeV) Eg = 100 MeV qop = .017 qMS in mrad, Eg in GeV, c in rad. Len. qMS = 21.1 mrad for Silicon Conversions! (34.5 mrad for Tungsten Conversions) All Conversions Top Silicon Conversions

27. Putting It All Together … = .76 This is probably a bit high as the average Xo is > .4% … As a Polarimeter, LAT has an “analyzing power” of ~ 3% Efficiency: 294 events / 5076 events = 5.8% (Max possible: 21%) Analysis Efficiency = 27% And so it will take to measure AGammaRays(assumed = 1.0) to 1s

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 d-ray identification • Detailed vertex topology and hit structure leads to silicon conversion separation – Polarization? • In-flight Performance: see talk by Luca Baldini