N.Omodei GLAST LAT full simulation 1 GLAST LAT SIENA2004 conference May 23 – 26, 2004 GLAST LAT full GLAST LAT full simulation simulation Nicola Omodei University of Siena, INFN Pisa Francesco Longo University and INFN Trieste and the GLAST LAT Italian SW group (INFN Bari, Padova, Perugia, Pisa, Trieste, Udine) P. Boinee , G. Cabras , A. De Angelis , D. Favretto , M. Frailis , R. Giannitrapani , E. Milotti , F. Longo , M. Brigida , F. Gargano , N. Giglietto , F. Loparco , M. N. Mazziotta , C. Cecchi , M. Fiorucci, F.Marcucci, P. Lubrano , M. Pepe , G.Tosti, L. Baldini , J. Cohen- Tanugi , M. Kuss , L. Latronico , Gamma-ray Large Gamma-ray Large Area Space Area Space Telescope Telescope
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N.Omodei GLAST LAT full simulation 1 GLAST LAT SIENA2004 conference May 23 – 26, 2004 GLAST LAT full simulation Nicola Omodei University of Siena, INFN.
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N.Omodei GLAST LAT full simulation 1
GLAST LAT SIENA2004 conference May 23 – 26, 2004
GLAST LAT full simulationGLAST LAT full simulationNicola Omodei
University of Siena, INFN PisaFrancesco Longo
University and INFN Triesteand the GLAST LAT Italian SW group
(INFN Bari, Padova, Perugia, Pisa, Trieste, Udine)P. Boinee, G. Cabras, A. De Angelis, D. Favretto, M. Frailis, R. Giannitrapani, E. Milotti, F. Longo, M. Brigida, F. Gargano, N. Giglietto, F. Loparco,
M. N. Mazziotta, C. Cecchi, M. Fiorucci, F.Marcucci, P. Lubrano, M. Pepe, G.Tosti, L. Baldini, J. Cohen-Tanugi, M.
Kuss, L. Latronico, P.Majumdar, N. Omodei, M.Razzano, C.Sgrò, G. Spandre, D. Bastieri, R. Rando
On behalf of the GLAST LAT collaborationThanks to T.Burnett, R.Dubois, B.Giebels, H.Kelly,
S.Ritz, L.Rochester, M.Strickman, T.Usher
Gamma-ray Large Gamma-ray Large Area Space Area Space TelescopeTelescope
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OutlineOutline
• Description of the mission and instrument• Scientific goals• Software infrastructure• MonteCarlo simulations:GEANT4• Digitization and Reconstruction•High level data analysis: DC 1•Conclusions
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The GLAST MissionThe GLAST Mission
GLAST measures the direction, energy and arrival time of celestial gamma rays
-LAT measures gamma-rays in the energy range ~20 MeV - >300 GeV
- There is no instrument now covering this range!!
- GBM provides correlative observations of transient events in the energy range ~20 keV – 20 MeV
• Physics in regions of strong gravity, huge electric & magnetic fields: e.g. particle production & acceleration near the event horizon of a black hole.
• Use gamma-rays from AGNs to study evolution of the early universe.
• Physics of gamma-ray bursts at cosmological distances.
• Probe the nature of particle dark matter: e.g., wimps, 5-10 eV neutrino.
• GLAST pulsar survey: provide a new window on the galactic neutron star population.
• “Map” the pulsar magnetosphere and understand the physics of pulsar emission.
• Origin of cosmic-rays: characterize extended supernovae sources.
• Determine the origin of the isotropic diffuse gamma-ray background.
discove
ry
reachA
rea
(sq
uar
e cm
)
Energy (GeV)
GLAST
EGRET
0.01 0.1 1 10 100 10000.01 0.1 1 10 100 1000
1010
1010
1010
44
33
22
AGNSupernova Remnants
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-pair conversion “telescope”
Csi Calorimeter (energy measurement)
Si strip detectors
Conversion foils (W)
tiled scintillation detectors
e+ e-
Characteristics
• Low profile for wide f.o.v.
• Segmented anti-shield to minimize self-veto at high E.
• Finely segmented calorimeter for enhanced background rejection and shower leakage correction.
• High-efficiency, precise track detectors located close to the conversions foils to minimize multiple-scattering errors.
• Modular, redundant design.
• No consumables.
• Low power consumption (580 W)
Pair production is the dominant photon interaction above 10 MeV
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GLAST Large Area Telescope (LAT)GLAST Large Area Telescope (LAT)
2.0 x 2.7 x 33.6 cm cosmic-ray rejection shower leakage correction
ACDSegmented scintillator tiles0.9997 efficiency
minimize self-veto
Data acquisition
16 identical towers30 Hz average downlink
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Why we need SimulationWhy we need Simulation
• Calibration, assessment of pattern recognition, track fitting strategies
• Predict the following figures of merit, depend on incoming photon energy E and angle :
– Effective area Aeff: depends on geometric area, conversion probability, reconstruction efficiency
– Point Spread Function (PSF): depends on multiple scattering, detector resolution, pattern recognition accuracy
• Develop a strategy and assess its effectiveness in suppressing the background from hadronic interactions. (Average trigger rate: 4 kHz: science rate: <10 Hz)
Visual C++/gnu Development envs World standards In use
CMT Code mgmt tool HEP standard In use
cvsweb cvs web viewer HEP standard In use
cvs File version mgmt World standard In use
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Sim/Recon toolkitSim/Recon toolkit
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Sources: Incident FluxSources: Incident Flux
• Available types:– Primary and secondary GCR– Albedo gammas– Point & diffuse sources
• Distributions of energy spectra • Various angles distribution
– Zenith, spacecraft galactic or celestial coords
• Keep track of time– Orbit, rates, deadtime– Transients
• Sources:– Gamma or particles beam– Power law, point sources– Egret Sources(3rd catalogue)– Transient sources: GRB
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Geometry RepositoryGeometry Repository
• A complex instrument: GLAST geometry is formed by more than 40000 different kind of volumes. – A typical problem in HEP
experiments (and GLAST is not so big)
• The geometry database in GLAST is in XML, a quite common choice (LHCb, Atlas and more) today
• detModel is a set of C++ classes to parse and represent in memory such XML description
• Used by various clients (reconstruction algorithms, MonteCarlo simulation, graphics etc. etc)
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The MC SimulationThe MC Simulation
• G4 as proposed MC• Learning G4 and development of GammaRayTel• Geometry repository• Gaudi integration
– Managing the event loop– Source generation– Hit generation by G4– Digitization – Reconstruction
• G4 adopted as official MC• Continuing validation activity• MC data production phase
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GLAST G4 physicsGLAST G4 physics
W
Si
white: incoming photon
green: W boundaries
Orange: Si boundaries
blue boxes: CsI segments
black: electrons and positons
red: light repsonse
Tracker
Calorimeter
• Photon processes: – Photoelectric– Compton Scattering – Pair Production
• Charged particles processes – Ionisation
• Landau and Bethe Bloch • Range, Straggling,
Stopping Power – Multiple Scattering
• Angular distribution, Energy Dependence
– Bremsstrahlung • Cross Section, Angular
and Energy Distribution – Delta Ray production
• Energy distribution, Multiplicity
– Positron Annihilation – EM shower development
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The whole event, with photonsThe whole event, with photons
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Event ReconstructionEvent Reconstruction
• Sequence of operations, each implemented by one or more Algorithms, using TDS for communication
1. DIGITIZATION– MC energy deposition -> Digital signal
2. RECONSTRUCTION– Preliminary CAL to find seed for tracker– Tracker recon: pattern recognition and fitting to
find tracks and then photons in the tracker (uses Kalman filter)
– Full CAL recon: finds clusters to estimate energies and directions
• Must deal with significant energy leakage since only 8.5 X0 thick
– ACD recon: associate tracks with hit tiles to allow rejection of events in which a tile fired in the vicinity of a track extrapolation
– Background rejection: consistency of patterns:• Hits in tracker• Shower in CAL: alignment with track,
consistency with EM shower
An easy rejection
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Digitization AlgorithmsDigitization Algorithms
• Digitization Algorithms
– Geant4 tracks particles through the LAT and records interactions in “active” volumes
• McIntegratingHits in the Calorimeter crystals• McPositionHits in the tracker silicon layers and the ACD tiles
– Digitization algorithms then convert this MC information to simulate the electronics output (ACD,TKR,CAL)
Geant4 treats the entire silicon plane as a unit. Energy is deposited with “landau” fluctuations. Using this information, the digitization algorithm determines which strips are hit.
• TKR Digitization Tools:– Two Digitization tools exist:
• In the Simple Digitization tool energy deposited in the silicon is divided according to the path length (no fluctuations).
– Time-over-threshold is linear in (deposited energy - threshold)
• The Full Digitization is a complete electronics simulation which accounts for fluctuations in deposited energy as the particle traverses the silicon, etc.
– More detail – 2-3 times slower execution speed
• Merging two tools recently finished:– Common tools available for both (Bad strips, failed layers, noisy strip generation, etc. )– Select one tool or the other at program start-up (Easy comparison of the two – cross
check results)
• CAL Digitization:– Takes into account light propagation to the two ends of a crystal segment
• Add noise to “unhit” crystals; save those above threshold• Convert to ADC units and pick the appropriate readout range for hits above
threshold• ACD Digitization
– McPositionHit is input– ACD digitization:
• Energy deposited converted to PMT output (with corrections)• Tile “hit” if above threshold
• DC1: One day of simulated data (diffuse background + stationary sources + GRBs)
• “End-to-end” testing of analysis software. • Familiarize team with data content, formats, tools and realistic
details of analysis issues (both instrumental and astrophysical).• If needed, develop additional methods for analyzing LAT data,
encouraging alternatives that fit within the existing framework.• Provide feedback to the SAS group on what works and what is
missing from the data formats and tools.• Uncover systematic effects in reconstruction and analysis.
Support readiness by launch time to do all first-year science.
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High-Level AnalysisHigh-Level Analysis
Gamma rays in 1-day scanning observation (~150k >30 MeV), color coded by energy
Hundreds of sources even in this short time: What are their fluxes? Which are flaring?
Bright diffuse emission of the Milky Way + Galactic and extragalactic point source populations
Annual rate (all energies) ~108 gamma rays/year
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Main Science ToolsMain Science Tools
Package Description
Likelihood Workhorse model fitting for detection & characterization of cosmic gamma-ray sources
Level 1 database access Extracts desired event data
Exposure calculation Uses IRFs, pointing, livetime etc. for deriving calibrated source fluxes
Source identification Identifies gamma-ray sources with cataloged counterparts at other wavelengths
GRB analysis Temporal and spectral analyses of burst profiles
Pulsar analysis Phase folding & period searching of gamma-ray pulsars and candidates
Observation simulator High level simulation of observations of the gamma-ray sky with the LAT
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GRB050718 !GRB050718 !
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ConclusionsConclusions
• The simulation chain starts from astrophysical sources and produces “Level 1” data.
• MonteCarlo simulation:– Geant4 adopted as GLAST MC simulator– Independent packages interacting with MC simulations
• Starting phase of massive MC data production– Reconstruction strategies evaluation and refinement– Evaluation of the “Instrument Response Function” (Aeff, PSF, ∆E)
• Development of the analysis software– Data Challenge 1 completed – First test of scientific tools– Preparing DC2 (1 month of sim data) and DC3 (one year).