Science Analysis Software DC-2 Kickoff Workshop March 1-3, 2005 Tracy Usher 1/25 Data Challenge II Kickoff Workshop Simulation and Reconstruction Overview

Science Analysis Software DC-2 Kickoff Workshop March 1-3, 2005

Tracy Usher 1/25

Data Challenge IIData Challenge IIKickoff WorkshopKickoff Workshop

Simulation and Reconstruction

Overview

Tracy Usher

(representing a lot of people – mis-statements are mine, credit is all theirs…)


Tracy Usher 2/25

Goals of this TalkGoals of this Talk

• Overview of Simulation/Reconstruction: – Introduce the simulation and reconstruction to those unfamiliar

with it

• Highlight changes/improvements since DC-1– Attempting to focus on those simulation and reconstruction

features which are new for DC-2 • Though most recent changes are foremost in memory…

• Provide background for next talk:– Hopefully, this serves as a useful introduction to Bill Atwood’s

talk which will describe the performance of the reconstruction, again highlighting what is new from DC-1


Tracy Usher 3/25

OutlineOutline

• Framework– Gaudi environment

• Simulation– Overview of the flow of

simulation

– A look at the LAT Geometry as used in simulation and reconstruction

– Simulating events with Geant4

– Digitization

• Reconstruction– Overview and flow of the

reconstruction

– Calorimeter Reconstruction• Clustering/Moments Analysis• Energy correction methods• MIP Finder

– Tracker Reconstruction• The basic steps

– ACD Recon

– “Analysis” and Output


Tracy Usher 4/25

Sim/Recon Framework: GaudiSim/Recon Framework: Gaudi

• Gaudi– An experiment independent framework providing the necessary interfaces and

services for HEP event data processing applications– Used by several LHC experiments

• Sim/Recon interacts with Gaudi through:– Gaudi Algorithms

• Algorithms define the reconstruction tasks and control the sequence in which they are performed

– Gaudi Services• Provide “global” information across events (e.g. geometry)

– Gaudi Tools• Implementation of specific reconstruction tasks• Interact with Algorithms through abstract interfaces to allow interchangeability

– Gaudi Transient Data Store (TDS)• Globally accessible repository containing the results of each reconstruction

task• Provides communication between the stages of reconstruction

• Gaudi allows us to configure event processing “on the fly” – Job Options files define event processing and Input/Output for a given job


Tracy Usher 5/25

Simulation OverviewSimulation Overview

• Goal of simulation is to produce “raw data”, representing the response of the LAT to a given event, which can be fed to the reconstruction

• Logically breaks into four steps:– Event generation – “source particle”

– Simulation of LAT response to the generated event

– Digitization: the conversion of simulated LAT response to “raw data”

– Simulation of Trigger


Tracy Usher 6/25

Flow of SimulationFlow of SimulationGaudi Algorithm Sructure for DC-2Gaudi Algorithm Sructure for DC-2

New Event

EventGenerator(FluxAlg)

(PointingAlg)

Event Simulation(G4Generator)

Output Datato TDS

(or PDS)

LAT Geometry(G4GeometrySv

c)(also accessed by

the reconstruction)

Sources, Orbit Orientation, Etc.

(Many improvements and additions from DC1 - See Toby’s

Talk later)

Digitization(ACDDigiAlg)(CalDigiAlg)(TkrDigiAlg)

Trigger / Filter(TriggerAlg)

(OnboardFilter)

Geant4Event/Detector

Simulation

Convert simulated detector response

to “raw data”(calibration effects

enter here)

Output of digis given to Trigger

and Onboard FilterEvents MUST pass

Trigger in order to get reconstructed

Onboard Filter results recorded, events not

rejected


Tracy Usher 7/25

LAT GeometryLAT GeometrySimulation and ReconstructionSimulation and Reconstruction


Tracy Usher 8/25



Tracy Usher 9/25


• Main Point:– Most detailed LAT geometry to date including all features which

would significantly impact DC-2 results• From active devices • To surrounding support structures• Including electronics, wrapping, …• etc.

• Large number of updates to geometry since DC-1– Primarily CAL and ACD– For complete list see the xmlGeoDbs change log at:

http://www-glast.stanford.edu/cgi-bin/viewcvs/xmlGeoDbs/ChangeLog?rev=1.413&view=markup

• Still working on improvements for DC-3:– e.g. Curved ACD tiles

• One other important point:– The reconstruction, through the propagator, uses the same

geometry as the simulation


Tracy Usher 10/25

Overview of Geant4 SimulationOverview of Geant4 Simulation

• Geant4 determines the evolution of the event

– G4 given “source” which is propagated through the LAT

– G4 output to TDS:• McParticles – particles produced during

trackinig• McPositionHits – positions and energy

deposited in Silicon and ACD• McIntegratingHits – energy deposited in

“sub-cubes” of CsI crystals

• Passed on to Digitization stage

• For DC-2 we are using G4 v6.2.2– “Vanilla” G4 for everything…– However, we continue to experience

“problems” with the multiple scattering• Native G4 v6.2.2 Multiple Scattering

“too small” • Continue to use formalism circa G4 v3

– Have recently upgraded to G4 v7 where this problem is claimed to be fixed (finally)…

Incident Gamma

Conversion Point

Incident Gamma

Conversion Point

Propagation of primarye+ and e- through LAT

McPositionHits in Active Silicon

of Tracker

Incident Gamma

Conversion Point

Propagation of primarye+ and e- through LAT

McPositionHits in Active Silicon

of Tracker

Production and Trackingof Secondaries

McIntegratngHitsproduced in the

Calorimeter Crystals


Tracy Usher 11/25

DigitizationDigitization

• Digitization: Convert Monte Carlo information to detector response– Simulates the response of the detector to the simulated event

• TKR– Input: McPositionHits – position/energy in active silicon– Output: hit strips and ToT (Time over Threshold)– New for DC-2:

• Implementation of “bad” (hot/dead) strips• Implementation of cable controller buffer limit

– Truncation of data in “big” events (64 strips/plane end, 128 strips/cable)• Improved ToT response

• CAL– Input: McIntegratingHits – Energy deposited in cubes subdividing the Calorimeter

crystals– Output: ADC counts for both diodes at both ends– New for DC-2 (but mostly in well over 1 year ago, past time horizon…):

• New code throughout– Improved/updated xTal response– Calibrations (DC-2 uses “ideal” though)

• ACD– Input: McPositionHits – position/energy in ACD Tiles/ribbons– Output: PMT ADC counts per end

• Many updates / improvements from DC-1


Tracy Usher 12/25

Reconstruction OverviewReconstruction Overview

• Goal of the reconstruction:– Determine the incident gamma direction and energy– Provide tools for suppressing background

• Follow a two pass approach for Cal and Tracker– Best energy from Calorimeter needs tracking information– Best tracks from Tracker needs best energy reconstruction– Solve by breaking into two passes

• Background suppression– ACD Recon– MIP Finder

• Analysis step at end of reconstruction– Create output ntuple for detailed performance studies– Event Classification– Create FT1 output for analysis

• NOTE:– Will not discuss Calibrations

• Critical piece of “real” reconstruction• But (mostly) not using calibrations for DC2


Tracy Usher 13/25

Flow of ReconstructionFlow of ReconstructionGaudi Algorithm Sructure: Envisioned for DC-2Gaudi Algorithm Sructure: Envisioned for DC-2

“Raw data” from

TDS

CalReconPass I

TkrReconPass I

CalReconPass II

TkrReconPass II

AcdReconEvent

“Analysis”

Root tree/ntupleoutput to PDS

CalXtalRecAlg

CalClusterAlg

CalMipFinderAlg

CalEventEnergyAlg(parametric only)

TkrClusterAlg

TkrFilterAlg(inactive for DC2)

TkrFindAlg

TkrTrackFitAlg

TkrVertexAlg

CalEventEnergyAlg

TkrTrackFitAlg

TkrVertexAlg

AcdReconAlg

meritAlg(output ntuple)

Key

Existing Algorithms

New Algorithms

Not “Recon”

ClassifyAlg(Classification

Analysis)

FT1Alg(FT1 tuple)


Tracy Usher 14/25

Calorimeter ReconCalorimeter Recon

• CalRecon extensively restructured for DC-2 – Break into logical pieces– Follow TkrRecon organization paradigm

• Consists of a number of tasks handled by Gaudi Algorithms:– CalXtalRecAlg (Recon First Pass Only)

• Takes in raw data (CalDigis – diode readouts) and produces calibrated output data (CalXtalRecData – energy, position) for input to rest of CalRecon.

– CalClusterAlg (Recon First Pass Only)

• Associates CalXtalRecData objects into a “Cal Cluster”• Performs a “Moments Analysis” to determine principal axis,

etc.– CalMipFinderAlg (Recon First Pass Only)

• Search for MIP signature(s) in CalXtalRecData– CalEventEnergyAlg (Recon First and Second Pass)

• Run various energy correction algorithms


Tracy Usher 15/25

Calorimeter ReconCalorimeter ReconClustering and Moments AnalysisClustering and Moments Analysis

CalXtalRecAlg:• Convert diode ADC counts to energy, position in crystals: - Select range/diode - Pedestal subtraction - Correct for Light attenuation - etc.• Use “ideal” response – no calibrations• Much work here – all “new” code from DC-1 (but nearly 2 years ago now!)

1 GeV Gamma

Energy Flow

Monte Carlo Version of event

“McIntegratingHits”

“McPositionHits”

1 GeV Gamma

Energy Flow

CalXtalRecAlg Version of event

“McPositionHits”

“hit” crystals

1 GeV Gamma

Energy Flow

CalXtalRecAlg Version of event

“hit” crystals

Red Box size proportionalto total energy deposited, longitudinal position fromreadout asymmetry at eachend of crystal

1 GeV Gamma

Energy Flow

CalClusterAlg Version of event

Energy centroid foreach layer

Cluster Centroidfrom

Moments Analysis

Cluster Axisfrom

Moments Analysis

CalClusterAlg:•Associate hit crystals to form a single cluster •Determine cluster centroid and axis via a Moments Analysis• Provide “raw” calorimeter energy - simple sum of crystal energies• New “code” from DC-1• New “TDS” output from DC-1• Much work here as well


Tracy Usher 16/25

Calorimeter ReconstructionCalorimeter ReconstructionEnergy Correction AlgorithmsEnergy Correction Algorithms

• The Problem:– Large phase space of Glast

• Energy range from 20 MeV to 300 GeV

• Large FoV: ~2.5 str

– Tracker above

• Up to 1.5 radiation lengths BEFORE the Cal

– Gaps between towers

• Crystals ~187 mm, gaps ~35 mm

– Cal is “only” 8.6 radiation lengths deep

– etc.

• Corrections:– Energy Deposit in the Calorimeter

• e.g. Wallet Card Shower Profile correction– a and b are parameters

» b scales the radiation length» a sets the location of the energy centroid t

– Detector / Geometry (see next slide)

• Huge Amount of Effort in this area– Cannot do justice to this work in these few slides…

)(

1

0 a

ebtbE

dt

dE bta

b

at


Tracy Usher 17/25

2 GeV PhotonCal E = 950 MeV

Conversion

Bottom of Cal

Calorimeter ReconstructionCalorimeter ReconstructionEnergy Correction AlgorithmsEnergy Correction Algorithms

• Correct for:– Leakage out the back

• Cal is 8.6 rl deep




2 GeV photonCal E = 980 GeV

conversion

Bottom of Cal


Conversion

Gap between towers




– Edge of Calorimeter


Edge of Cal

100 MeV PhotonCal E = 60 MeV

Conversion

Positron stopsin Tracker

Electron rangesin Calorimeter




– Edge of Calorimeter

– Loss in the Tracker


Tracy Usher 18/25

Calorimeter ReconstructionCalorimeter ReconstructionEnergy Correction Algorithms - continuedEnergy Correction Algorithms - continued

• Maximum Likelihood Estimator – Replaces the previous (DC-1) Last Layer Leakage method with Maximum

Likelihood estimator – In addition, method extended to the low energy range to correct energy

taking into account energy lost in tracker• Extends method to provide correction in range from 50 MeV to 300 GeV

– Also, angular acceptance extended from around 30o to 50o

– See Pol D’Avezac’s note: http://polywww.in2p3.fr/glast/CalLikelihood.pdf

• Full Profile Shower Fit– Extension of previous 1D method (not used in DC-1) to a full 3D shower

profile fit– Finds energy correction for events above ~1 GeV – Angular acceptance extended to 90o – See Philippe Bruel’s note: http://polywww.in2p3.fr/~bruel/CalFullProfile.ps

• Parametric Method– Parameterized shower profile model – Provides corrected energy in range 20 MeV to 300 GeV and over the full

field of view– See Bill Atwood’s talk: http://www-glast.slac.stanford.edu/software/AnaGroup/Atwood-EnergyRecon-2May2005.ppt

• The following talk will compare these methods


Tracy Usher 19/25

Calorimeter ReconCalorimeter ReconMIP FinderMIP Finder

• The MIP finder analyzes the calorimeter data looking for a Minimum Ionizing Particle signature

– Goal is to eliminate a large source of charged particle backgrounds which enter from the sides and bottom of the Calorimeter

• The Method in two bullets or less:– Select CalXtalRecData objects in Calorimeter

• Take those crystals with energy deposits consistent with a MIP energy deposit• Look for a straight line trajectory through these crystals• Does Full fit of MIP track – returns a number of powerful background rejection variables

– Can then reject as background those events with clear MIP tracks

• Completely new for DC-2

See: http://www-glast.slac.stanford.edu/software/AnaGroup/Piron_ana2005-08-08.pdf


Tracy Usher 20/25

• Current Status:– Blue Lines - Protons– Red Lines - Gammas– Selection Cuts:

• Bottom right shows efficiency to identify MIPs (or misidentify Gammas)

(Plots from Sylvain Guiriec)

Calorimeter ReconCalorimeter ReconMIP FinderMIP Finder

http://www-glast.slac.stanford.edu/software/DataChallenges/DC2/MarchWorkshop/Presentations/Ana05-08-29-1.ppt

Pre-cuts :

TkrNumTracks > 0&& CalCsIRLn > 4&& CalEnergyRaw > 5&& CalTotalCorr < 3.5&& CalDeadTotRat < 0.15&& CalGapFraction < 0.30&& CalTransRms < 60&& CalLRmsAsym > 0

Cuts :

CalMipErm / CalMipArcLen < 1&& CalMipChi2 < 30&& CalMipEcor between 8 and 25 MeV&& CalMipEcorRms < 5&& dirErr < 0.7


Tracy Usher 21/25

1 GeV Gamma

Conversion point

e+ and e- trajectories

1 GeV Gamma

Conversion point

Pattern Track trajectories

1 GeV Gamma

Conversion point

Fit TrackTrajectories

1 GeV Gamma

Conversion point

Vector resultingfrom vertexing offit track pair for

this event

1 GeV Gamma

Conversion point

Vector resultingfrom vertexing offit track pair for

this event

The Illustrated Tracker ReconstructionThe Illustrated Tracker Reconstruction

Tkr Clustering:Associate adjacent hit strips to form strip clusters (corrected for hot and dead strips)

Pattern Recognition:Associate strips to form candidate tracks (Combinatoric pattern recognition using Kalman Filter to accept/reject candidate hits)

Track Fit:Take candidate tracks and track energy estimate and fit using a Kalman Filter

Vertexing:Combine fit tracks to form common vertex point- If one track, vertex is head of track- If two tracks don’t “combine” well, keep as separate vertices


Tracy Usher 22/25

Tracker ReconstructionTracker Reconstruction

• What is new for DC-2? – Pretty much everything…

• Algorithm Structure remains same– Two pass reconstruction format same as for DC-1

• But… Underlying code extensively reworked– Combo Pat Rec

• Combinatoric loops restructed and optimized to improve performance

• Uses same KF as track fit for hit selection

• Much improved performance

– Track Fit

• New Kalman Filter

• Track fit parameters (energy loss, particle type, etc.) controlled from Job Options file

– Vertexing

• New scheme for deciding whether to pair tracks or not

• Completely new TDS structure


Tracy Usher 23/25

ACD ReconstructionACD Reconstruction

“Active Distance”

outside tile boundary

no tile hit

inside tile

boundary

[cm]

1 GeV Muon

Reconstructed Track

Struck ACD TileProjection of Track back to

nearest ACD Tile

•ACD: Primary Background Suppression Tool

•Project Track to plane of struck tile

•Calculate distance to nearest edge 3D calculation if outside tile 2D calculation if inside tile

•Sign Positive if track projection inside the tile Negative if track projection outside the tile

•Reject if inside the tile

For complete details see Eric Charle’s IA Workshop talk on Monday February 27


Tracy Usher 24/25

Post Reconstruction ProcessingPost Reconstruction ProcessingThe Final StepsThe Final Steps

• meritAlg– Controls the creation of the merit output ntuple

• Used, for example, in various event classification analyses

• ClassifyAlg– Runs the classification analysis:

• Energy Selection• PSF Tail suppression• Background Rejection

– For DC-2 this is the Insightful Miner Analysis provided by Bill Atwood (see next talk)

• Future versions will allow alternate analyses as well (e.g. Toby Burnett’s Random Forests analysis)

• FT1Alg– Produce the Fits Level 1 output

• Will be discussed in more detail later


Tracy Usher 25/25

Main Points for DC-2Main Points for DC-2

• Very Detailed LAT Geometry– Really getting to the very fine details at this point

• Most of what is missing is already in the pipeline for DC-3

• Very Detailed Geant4 simulation– Based on G4 v6.2.2

• Multi-pass Reconstruction Algorithms– New algorithms to improve energy resolution and background

suppression– Many improvements to existing algorithms– Resulting in improved energy and psf resolution and background

rejection

• Enhanced post reconstruction processing– Perform Event Classification as part of reconstruction


Tracy Usher 26/25

SummarySummary

• Since DC-1 TkrRecon, CalRecon and AcdRecon have undergone extensive restructuring with many improvements…– Substantial updates to existing code

– Major overhaul of the algorithm output

– Implementation of many new tools along full reconstruction chain

• Resulting in major improvements– Background rejection

– PSF Tail suppression

– Energy Resolution

– Reconstruction efficiency

– Event classification

• See next talk for the results!

Documents

Science Analysis Software DC-2 Kickoff Workshop March 1-3, 2005 Tracy Usher 1/25 Data Challenge II Kickoff Workshop Simulation and Reconstruction Overview