Toby Burnett University of Washington

1. Studying Astrophysics and Particle Physics with Gamma Rays: what we may learn with the upcoming GLAST mission-and-The UW Contributions to GLAST Toby BurnettUniversity of Washington

2. GLAST Context: the photon spectrum (Mike Turner 1989) GAP!

3. Observer “Telescope” • EGRET / BATSE • GLAST: LAT/GBM • MILAGRO (EAS) • Whipple • HEGRA • HESS • VERITAS Satellite Cherenkov “Seeing” the Universe with gamma raysthe plot and the characters Source propagation • Massive black holes (AGN, blazars) • GRB (stellar collapse, magnetars) • Pulsars (neutron stars) • CR interactions • WIMP annihilation? • Primordial black holes? • absorption by IR • Dispersion?

4. Objective: detect gamma rays from astronomical sources with • Largest possible energy range • High acceptance, A    • A: effective area, including photon cross section • : field of view • : instrumental efficiency, including dead time • Good energy resolution for spectral measurements • Good angular resolution (buzz-word from telescopes: “point spread function”, or PSF) • Good signal/noise

5. Constraints • Good acceptance, PSF: must use pair conversion process • Compton: lose direction information, not high energy • Lower limit: ~20 MeV • Site: • Earth surface: use atmosphere as a target • Minimum energy ~100 GeV • Small , but large A • Low Earth orbit • Minimum energy 20 MeV • Large , but A limited by launch vehicle

6. Anticoincidence shield: required by very high flux of cosmic rays relative to gammas (~104) Must be very efficient Segmented to reduce self-veto Conversion foil (W): High Z thick for large A thin for good PSF Tracking (Si strips) Good efficiency, coverage Small pitch Calorimeter Thick to contain shower Thin to reduce mass for launch Segmented for shower pattern recognition  Pair-Conversion Telescope anticoincidence shield conversion foil particle tracking detectors e– • calorimeter (energy measurement) e+ Pair conversion detector design & requirements

7. Active 1991-1996 Tracking technology: 81 cm square wire spark chambers, 1 mm spacing Calorimetry: NaI crystals Triggering: Anticoincidence dome, TOF 100 ms deadtime 1970’s technology: CGRO and EGRET/BATSE • Launched on shuttle Atlantis 1991, deorbited 2001 • Instruments: • Burst And Transient Source Experiment (BATSE) (30 - 500 keV) • Compton imaging Telescope (1 - 30 MeV) • Oriented Scintillator Spectrometer Experiment (50 keV - 10 MeV) • Energetic Gamma-Ray Telescope (EGRET) (30 MeV - 30 GeV)

8. Deployment

9. Extragalactic diffuse Point things: near and far Diffuse things: CR interactions in matter 3C279 (blazar) Isolated neutron star? Geminga (radio-quiet pulsar) Vela ( radio pulsar) SN remnant? Crab (radio pulsar) LMC PKS 0202-512 (blazar) Orion Cloud EGRET’s view of the universe Galactic center EGRET all-sky survey (E>100 MeV)

10. Introducing GLAST An International Science Mission • Large Area Telescope (LAT) • GLAST Burst Monitor (GBM) Large Area Telescope (LAT) LAT: 20 MeV – >300 GeV GBM: 10 keV – 25 MeV Spacecraft (Spectrum Astro) GLAST Burst Monitor (GBM)

11. The Collaboration • US: Stanford, SLAC, GSFC, NRL, Ohio State, UCSC, Sonoma State, UW • Japan: Tokyo, Hiroshima • Italy: Bari, Padova, Perugia, Pisa, Rome, Trieste, Udine • France: Saclay, Ecole Polytechnique (Paris), Bordeau, Montpellier • Sweden: Stokholm

12. Our launch vehicle: Boeing Delta IIH Launch: from Cape Canaveral - September 2007

13. Tracker e– e+ Calorimeter Overview of the LAT  1.7 m • Precision Si-strip Tracker18 XY tracking planes. Single-sided silicon strip detectors (228 mm pitch) Measure the photon direction; gamma ID. • Hodoscopic CsI CalorimeterArray of 1536 CsI(Tl) crystals in 8 layers. (8 X0) Measure the photon energy; image the shower. • Segmented Anticoincidence Detector (ACD)89 plastic scintillator tiles. Reject background of charged cosmic rays; segmentation removes self-veto effects at high energy. • Electronics SystemIncludes flexible, robust hardware trigger and software filters. ACD

14. Performance: 1970’s vs 1990’s technology

15. Data handling and analysis • Not an imaging device – no pixels as such • Does that make it not a “telescope”? Webster says: • Telescope \Tel"e*scope\, n. [Gr. ? viewing afar, farseeing; ? far, far off + ? a watcher, akin to ? to view: cf. F. t['e]lescope. See Telegraph, and -scope.] An optical instrument used in viewing distant objects, as the heavenly bodies. • Instead of collecting photons with ccd pixels, we record “events”, caused by single incoming photons • trigger logic, including possibility of veto of background (EGRET had both “A-dome” and TOF requirement to keep rate well below 10 Hz.) • Many channels to calibrate • Pattern recognition • Event reconstruction • Discrimination against background • Calibration of response to photons

16. Software, software! • Vital part of processing. • Onboard filter to handle high trigger rate • part of extensive onboard software to control instrument, acquire data, send to “SSR”. • All in straight C, written under strict NASA rules for flight software • Ground software • Packages managed by CMT, with visual interface MRvcmt • Runtime framework: Gaudi • All code in OO C++. • gcc / emacs on linux; Visual Studio on Windows • I/O data uses ROOT • Analysis plots generated by ROOT.

17. GLAST and the UW group • We joined in the formulation phase, in 1994 • Now it is an international $500M DOE/NASA mission • Local people who have made contributions • Sawyer Gillespie, undergraduate, staff for 2 years • Sean Robinson, PhD 2004 on wavelet analysis • Theodore Hierath, REU, current graduate student • Jon Chandra, graduate student • Marshall Roth, undergraduate • Scott Haynes, undergraduate • Bruce Blesnick, masters student • Todd Olson, staff, computer support

18. Essential tools: Monte Carlo and Event visualization • Monte Carlo • geometry • XML description • managed by “visitors” (gang of 4 Visitor pattern) • particle sources • also XML • object factories • composite sources (Composite pattern) • physics of particles in matter: Geant4 (replacing THB’s Gismo) <box name="CsISeg" sensitive="intHit" detectorTypeREF="eDTypeCALXtal" XREF="CsISegLength" YREF="CsIWidth" ZREF="CsIHeight" materialREF="crystalMat" > </box> <stackX name="CsIDetector" > <axisMPos volume="CsISeg" ncopyREF="nCsISeg" > <idField name="fCALSeg" value="0" step="1" /> </axisMPos> </stackX> <source name="all_gamma" flux="1.0"> <spectrum escale="GeV"> <particle name="gamma"> <power_law emin="0.01778" emax="17.78“ gamma="1"/> </particle> <solid_angle mincos="0" maxcos="1.0"/> </spectrum> </source>

19. The Framework: combine simulation, reconstruction, event display and some analysis

20. The GLAST Data Challenge 2 We are in the midst of preparing a major end-to-end simulation: • Orbit: start 1-1-08 for 56.3 days (a precession period) • Best estimates of particle backgrounds • Use scanning/rocking mode (most likely for first year, perhaps entire mission) • Now running special Monte Carlo runs to characterize instrument • Background: ~ 1 day (all we can do!) • Photons: 10 M at all angles and energies • Use the above to define responses • Defining model of gamma ray sky, including all the known sources, some speculation. • Test with special parametric Monte Carlo based on previous analysis. • The “real” run, for later this year, will use full Monte Carlo with gamma sources, with sampling from the 1-day background

21. The orbit • Trigger rate (~8 kHz) is dominated by charged particles! Only 1-2 Hz are actual gammas from space. • Orbit and pointing mode: create 56.3 days with rocking, sun-avoidance dec ra

22. Particle fluxes: dramatic fluctuations!

23. Our current model secondary e± Albedo gamma secondary protons galactic protons He, CNO Galactic electrons E*flux, (m-2 s-1) log10(E/1 MeV)

24. Background Simulation • Select an orbit time, and a 1-second duration. • Generate the ~50 K incoming particles, with random directions, energies, and spread out over a sphere with cross sectional area 6 m2 • Send each into the detector: • Discard if no trigger (missed or hits did not satisfy a trigger condition) ~8 kHz remain (20% deadtime) • Apply the onboard filter code that checks for obvious charged, non-interacting particles: ~700 Hz remain • Fully analyze these, corresponding to the downlink rate • Run 8640 such jobs, starting every 10 sec, for 10% of a full day. (using the UW physics condor system for up to 64 jobs)

25. Invented, maintained at UW-Madison. Basis for managing jobs in much of the “grid”, now called Open Science Grid Now installed on all physics dept lab and undergraduate machines: ~60 machines, ~25 Gflops of Windows cycles available (except when the machines are used!). [Note, the UW astronomers are ‘way ahead of us in sharing desktops] All are welcome: see http://glast-ts.phys.washington.edu/condor/for instructions on how to participate What is Condor?

26. The rates, from 864 jobs run at UW

27. Also generate signal events • All-gamma sample: uniform in log(E) from 16 MeV to 160 GeV, and in the upper hemisphere • Rather different from actual source, but easy to characterize response for given incoming gammas. • Try to estimate reliability of energy and direction measurement

28. Background rejection – very difficult • Create many variables to measure gamma-like, or charged particle-like quantities • extra hits around a found track • correlation of track direction with hit ACD tile (if any) • correlation of track direction with direction of CAL shower • etc. • Feed them to a set of classification tree trainers (code written for D0 single top analysis)

29. A preliminary bottom line

30. Pixels or photons? • Astronomers prefer pixels, but physicists like photons! • Focusing devices (mirrors, lenses) convert direction to position, CCD’s collect photons, define the pixels • From SDSS web site: “On a clear, dark night, light that has traveled through space for a billion years touches a mountaintop in southern New Mexico and enters the sophisticated instrumentation of the SDSS's 2.5-meter telescope. The light ceases to exist as photons, but the data within it lives on as digital images recorded on magnetic tape. Each image is composed of myriad pixels (or picture elements); each pixel captures the brightness from each tiny point in the sky.” For astronomers, pixels are the data

31. Our data comes as individual photons • Two image processing approaches • Individual photons • Advantage: keep all the information • Disadvantage: processing time: scales with exposure • Fill pixels • Advantage: all astronomical tools work, easy to deal with:Almost all EGRET analysis was with 0.5 deg pixels • Disadvantage: loose resolution for high-energy photons

32. Resolution scale factor  (deg)  conversion Multiple scatter W Gamma energy (MeV) Problems with binning: I • Angular resolution varies dramatically with energy: • expect 1/E from multiple scattering • measure E-0.8 • Images don’t show localization without removing low energies, increasing resolution • Full information not used in point source searches 4 decades of energy: 3 decades in resolution! Note: 68% containment is ~3

33. Problems with binning: II • Need a spherical projection to 2-d that defines pixels with: • Equal area • No discontinuities (like poles, wrap-around) • Pixels ~uniform in shape (square, triangular) • Simple mapping to/from actual coordinates • Neighbors easy to find • Cartography defines ~150 including equal-area Hammer-Aitoff. • None are appropriate, really want a tesselization based on a regular polygon The Hammer-Aitoff: popular in astronomy WMAP microware

34. Hierarchical Equal Area isoLatitude Pixelization WMAP and COBE data binned this way Adopted by Planck Original code in f90, we now “wrap” C++ subset Solution from WMAP: HEALPix Level 10: 12,582,912 pixels Level 9: 3,145,728 pixels Level 3: 768 pixels Note: Npix = 12*4level

35. 1 0 3 2 5 6 7 4 11 9 8 10 12 to 48 pixels (level 0 to 1)(with “nested” indexing)

36. level 6 7 Resolution scale factor  (deg) 8 9 10 11 12 13 Gamma energy (MeV) Application to GLAST • Take advantage of Hierarchical property, easy to correlate index for contained pixels. • Create pixels in sparse structure according to 8 bins in photon energy, sorted according to position. • Make selecting subset according to outer pixel level easy for projection integrals • Numerous low energy photons are effectively binned • Rare high energy photons occupy own pixels • Can solve database indexing

37. Low levels: saturated, many photons/pixel. High levels: single photons (diffuse); multiple photons (point sources) Apply it to the 56-day simulated data set 1.7M photons w/ E>100 MeV 300 K pixels.

38. Count Map Images: 0.1 deg pixels Intensity is the number of photons in the pixel E>100 MeV ~4 M pixels for full sky, > photons, not adequate for 100 GeV. E>1 GeV

39. Healpix density image • Construct 0.1 deg image with density at center of display pixel: sum of counts/solid angle for all contained Healpix pixels in that direction.High energy photons count according to resolution

40. Image generation: define a density function • High energy photons are more localized: we express this by defining photons/area • Easily determined from the data base and the Healpix code. 3C273: density vs. all photons above 100 Mev

41. Point Source Detection: work in progress • Motivation was to create a manageable data set for study of point sources, allowing quick projection integrals for candidates • This is actually a “Hough transform”, allowing easy detection of point sources. Comparison with other fixed-scale binning methods is in progress. • Applying wavelet technology developed by Sean Robinson • Allows quick measurement of intensity, position, significance. • Precision expected to be close, within 20% of formal maximum likelihood analysis

42. Science Groups CatalogsDiffuse (Galactic & Extragalactic) and Molecular CloudsBlazars and Other AGNsPulsars, SNRs, and PlerionsUnidentified Sources, Population Studies, and Other GalaxiesDark Matter and New PhysicsGamma-Ray BurstsSources in the Solar SystemCalibration and Analysis MethodsMultiwavelength Coordinating Group