n.omodei glast lat full simulation 1 glast lat siena2004 conference may 23 – 26, 2004 glast lat...

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



OutlineOutline

• Description of the mission and instrument• Scientific goals• Software infrastructure• MonteCarlo simulations:GEANT4• Digitization and Reconstruction•High level data analysis: DC 1•Conclusions



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

Launch: February 2007 Florida

Orbit: 550 km, 28.5o inclination

Lifetime: 5 years (minimum)



Map the High-Energy Universe

GLAST ScienceGLAST Science0.01 GeV 0.1 GeV 1 GeV 10 GeV 100 GeV 1 TeV0.01 GeV 0.1 GeV 1 GeV 10 GeV 100 GeV 1 TeV

• 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



-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



GLAST Large Area Telescope (LAT)GLAST Large Area Telescope (LAT)

e+ e–

Si Tracker Towerpitch = 228 µm5.52 104 channels12 layers 3% X0

+ 4 layers 18% X0

+ 2 layers

Grid (& Thermal Radiators)

3000 kg, 650 W (allocation)

1.8 m 1.8 m 1.0 m

20 MeV – 300 GeV

CsI CalorimeterHodoscopic array8.4 X0 8 x 12 bars

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



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)



Simulation InfrastructureSimulation Infrastructure

SourceFluxes

Geometry

ParticleTransport

“Raw”Data

Recon

BackgroundRejection

-Particle ID

SourceFluxes

Geometry

ParticleTransport

“Raw”Data

Recon

BackgroundRejection

-Particle ID

Real Data

3 GeV

Level 1



Sim/Recon ToolkitSim/Recon Toolkit

Package Description Provider Status

ACD, CAL, TKR Recon

Data reconstruction

LAT 90% done

In use

ACD, CAL, TKR Sim

Instrument sim LAT 95% done

In use

GEANT4 Particle transport sim

G4 worldwide collaboration

In use

xml Parameters World standard In use

Root C++ object I/O HEP standard In use

Gaudi Code skeleton CERN standard In use

doxygen Code doc tool HEP standard In use

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



Sim/Recon toolkitSim/Recon toolkit



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



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)



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



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



The whole event, with photonsThe whole event, with photons



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



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.

particle

digis Mc Hit

cluster



Simulation / DigitizationSimulation / Digitization

• 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

– AcdDigi is output



TkrClusterAlgTkrDigiCol

TkrClusterCol

TkrFindAlg

TkrTrackFitAlg

TkrVertexAlg

PatternRecognition:•TkrComboPatRec

Kalman Filter:•KalFitTrack

TkrPatCandCol

Track Propagator:•G4Propagator

Vertexing:TkrComboVtxRecon

TkrTrackCol

TkrVertexCol

Clustering:•TkrMakeClusters

TkrReconAlg

Tracker ReconstructionTracker Reconstruction

TkrFailureModeSvcTkrBadStripsSvc TkrAlignmentSvc



Reconstructed tracks Reconstructed tracks



Calorimeter ReconstructionCalorimeter Reconstruction• Basic Reconstruction Goals:

– Reconstruct the energy of the incident gamma ray

– Reconstruct its direction– Reconstruct its position within

the calorimeter• Step 1:Convert ADC scale to

Energy measured at each crystal• Step 2: For Each Layer:Sum the

individual crystal energies• Step 3: Energy Reconstruction

Algorithms (energy leaks): – Shower profile fitting– Shower profile model– Last layer correlation method

• Step 4: Estimation of the incident position and direction

– Uses a two-dimensional energy-weighted centroid position in each layer



Calorimeter ReconstructionCalorimeter Reconstruction

20 GeV incident positrons

Raw

Profile fitting

Correlation method

4 - 7% E/E

Resolution vs. Energy and incident angle



Recon – The ResultRecon – The Result



GLAST Instrument Response FunctionsGLAST Instrument Response Functions



The Data Challenges The Data Challenges

• 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.



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



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



GRB050718 !GRB050718 !



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).

• Mission to be launched in 2007!

n.omodei glast lat full simulation 1 glast lat siena2004 conference may 23 – 26, 2004 glast lat...

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