Eric Charles

ACD Software review

Phase IWalkthrough of major ACD software

compontents

Jan. 24 2008

Outline

OverviewTasks of ACD softwareCode organization

Calibrations Data structures and storage [in CalibData, CalibSvc]Access to calibrations [AcdCalibSvc and AcdSimCalibSvc]Acd calibration definitions and functions [AcdUtil/AcdCalib*]

Storing digi data [Event/AcdDigi]Signal simulation [AcdDigiAlg]Reconstruction [AcdRecon]

Applying calibrations [AcdPha2MipTool]Track based recon [AcdPocaTool, AcdTkrIntersectTool]

Storing recon data: [Event/AcdRecon]Extracting stuff for merit files [AcdValsTool]Generating Calibrations: [calibGenACD]

Tasks of ACD software

Handle calibrationsAccess calibrations in Gaudi (CalibData/Acd, CalibSvc)Generate calibrations (calibGenACD)

Store dataTDS (Event/Digi/AcdDigi, Event/Recon/AcdRecon)ROOT (digiRootData/AcdDigi, reconRootData/AcdRecon)

Simulating detector responseMaking digis in Monte Carlo events (AcdDigi)

Reconstruct eventsGeometrical calculations (AcdRecon)

Filling Merit ntupleExtracting data from TDS (AnalysisNtuple/AcdValsTool)

Various Pieces of ACD software

Event/ACDreconRootData/Acd*

digiRootData/Acd*

CalibData/Acd

AcdUtil/AcdGeomMap

AcdUtil/AcdCalibFuncs AcdRecon/AcdReconFuncs

AcdRecon/AcdReconStruct

AcdReconAlgAcdDigiAlgcalibGenACD/apps

AcdPha2MipTool

AcdPocaTool

AcdTkrIntersectionTool

RootConvert

AcdDigiUtil

Tools and LibrariesPublic Data

Algs & Apps

Internal Data

AcdValsTool

MeritTuple

ACD calibrations

Seven types of calibrationsPedestalsGains (a.k.a. MIP peaks)High range PHA -> MIPCoherent readout noise effect on pedestalVeto ThresholdCNO ThresholdRange crossover

All calibration are very similarA few numbers for each PMTRecycle as much technology as possible

Not used in reconstruction, MC only

CalibData/Acd

All calibrations are PMT basedA few floats and a status flag

CalibData::AcdCalibDescription captures this Gives names to each of the floats in order

E.g. “mean”, “width”, or “veto”, “width”

CalibData::AcdCalibObj stores calib constantsJust stored as a vector

Need AcdCalibDescription to give names to each slot

Sub-class of AcdCalibObj for each calibration typeJust there to provide fast access functions

getMean() { return operator[](0); }getWidth() { return operator[](1); }

More on CalibData and CalibSvc

CalibData/AcdCalibBase does all the workJust a map to associate calibrations with pmt IDsStores data as vectors of <AcdCalibObj*>

Template CalibData/AcdCalib<CalibObjType>This is just there for type safetyForces use to get the right type of calibration

Reuse same trick in CalibSvcBase class XmlAcdBaseCnv reads all the xml expect for the actual calibration constants

All the channel ID and headersTemplate XmlAcdCnv<T> read the calibration constants

Uses AcdCalibDescription to know what attributes to expect

AcdCalibSvc and AcdSimCalibSvc

AcdUtil provides two services to get calibrationsBoth are used in MC jobs, allows user different calibrations to generate and simulate

AcdCalibSvc (for reconstruction)Pedestals, Gains, High Range, CoherentNoise

AcdSimCalibSvc (for simulation)Also Veto & CNO thresholds, Range crossover

Reuse same trick with templatesBase class AcdCalibMgr talks to the CalibDataSvc

Handles all the caching and validity checkingTemplate AcdCalibMgrTmpl<T> provides the type safety

One AcdCalibMgrTmpl<T> per calibration type

Using the Acd*CalibSvc

Several Job options, somewhat confusingDefaultFlavor [“ideal”]

Used for all calibrations unless overriddenFlavorXXX [“”]

Null string means use default, otherwise override

“ideal” doesn’t access DB, just uses pre-defined values

AcdDigi

AcdId m_id;const char* m_tileName;int m_tileNumber;VolumeIdentifier m_volId;double m_energy;unsigned short m_pha[2];bool m_veto[2];bool m_low[2];bool m_high[2];Range m_range[2];ParityError m_error[4];

High range is set by board, not by PMT

This is the MC energy

4 versions of same information

AcdDigi merges data from both PMTs attachedto a single tile or ribbon

By design, data content is superset of data coming offdetector

AcdDigiAlg overviewTask: to simulate Acd electronics responseInput: energy deposited in element from GEANT

Event::McPositionHitColOutput: full AcdDigi collection

Pulse height, Veto, CNO, zero suppression discriminators

Ancillary inputs:From xml file

Conversion from MeV -> p.e. Conversion from p.e. -> mips Zero suppression threshold (in PHA -> converted to mips)Edge effects

From Calibrations DBPedestal (in PHA) MIP peak (in PHA above Pedestal) Range crossover value (in PHA ->converted to mips)Veto threshold (in PHA->converted to mips)CNO threshold (in PHA->converted to mips)High Range gain and saturationCoherent noise effect ( in PHA )

AcdDigiAlg Algorithm

p.e. nominal

Readout range

HIGH range PHA

Event::AcdDigi

Event::McPositionHit (Energy in MeV)

p.e. observed

Signal in MIP

Conversion to p.e.

Poisson Stats & dynode chain

Conversion to MIPs

Range Calibration

High Range CalibrationLOW range PHAPedestals

Gains (aka MIPs)

VETO CNO

Veto Calibration

CNO Calibration

Accept Map BitZero Sup.

AcdReconAlg overviewTask: to do all ACD reconstrucitonInput: Tracks and AcdDigis

Event::TrkTrackColEvent::AcdDigiCol

Output: full AcdRecon dataEvent::AcdHitCol -> calibrated signalsEvent::AcdTkrHitPocaCol -> track/hit associationsEvent::AcdTkrGapPocaCol -> track/gap associationsEvent::AcdTrkIntersectionCol -> track extrapolations to GEANT modelEvent::AcdTkrPointCol -> track extrapolations to ACD volume

Ancillary inputs:From job options

Cuts on signal sizeFrom xmlGeoDbs

ACD detector geometry From Calibrations DB

Pedestal (in PHA) MIP peak (in PHA above Pedestal) High Range gain and saturationCoherent Noise effect (in PHA)

AcdReconAlg algorithmEvent::AcdDigiCol

AcdRecon::TrackData

AcdRecon::PocaDataMap

Event::AcdRecon::m_active*

vector<Event::AcdTkrIntersection*>

vector<Event::AcdHit*>

vector<Event::AcdTkrGapPoca*>set<Event::AcdTkrHitPoca*>

Event::TkrTrackCol

AcdRecon::ExitData

AcdRecon::PocaDataMap

AcdPha2MipTool

Extract params

Find lat exit pointCalculate all POCAs

Propagate track

Apply calibrations

AcdPocaToolLatch best act_distFilter POCAs

AcdTrkIntersectionTool

Find doca w.r.t GapsProject errorsIntersect w/ GEANT model

AcdRecon code elements

AcdRecon/AcdReconStructAll the internal data structures

AcdRecon/AcdReconFuncsA bunch of functions to do geometrical calculations

AcdRecon/AcdPha2MipToolTo convert AcdDigi to AcdHit using calibrations

AcdRecon/AcdPocaToolTo do POCA calculations

AcdRecon/AcdTrkIntersectToolTo use G4Propagator to extend tracks, calculate error matrices

Calibrated ACD Hits

Just want to keep track of the pulses in terms of MIPs,

rather than ADC countsEvent::AcdHit {

AcdId m_tileId; // which tile was hit

ushort m_pha[2]; // Digi level data for both PMT ushort m_flags[2] // Veto, Accept bits, error flags for both PMT float m_mips[2]; // calibrated values for both PMT}

ACD hit flags

These flags are defined so far:PMT_ACCEPT // pmt is above zero suppression threshold PMT_VETO // pmt fired veto discriminatorPMT_CNO // pmt fired CNO discriminatorPMT_RANGE // pmt was read out in high rangePMT_ODD_PARITY_ERROR // pmt has parity errorPMT_HEADER_PARITY_ERROR // parity error in headerPMT_DEAD // pmt was dead or masked off PMT_HOT // pmt was hot

Maybe others such as:PMT_IN_ROI // pmt was used in making an ROI coincidence

Some of these require non-acd dataPMT_DEAD, PMT_HOT could require offline tables

Leave it for now

Associations Between Tracks and ACD hits

We want to keep track of which track come close to which hit ACD elementFor each track with an arbitrary distance of a hit ACD element we can store

Event::AcdTkrHitPoca { AcdId m_tileId; // which tile was hit int m_trkId; // which track did the hitting Event::AcdTkrLocalCoords { float m_local[XY]; // Position where track crossed element plane float m_local[XY]Cov; // Covariance on that positions float m_pathLength; // path length in sensor float m_cosTheta; // Angle of track w.r.t. element plane int m_region; // which part of element } Event::AcdPocaData { double m_arcLength; // distance from POCA to tile plane

float m_doca, m_docaErr; // the active distance and the error on it Point m_poca; // 3D global postion of POCA Vector m_pocaVector; // Vector from POCA to element edge }}

Track Extrapolation to ACD

Top View

m_arcLengthToISect;

m_position;

Last Hit in Tracker

y

x

m_localX;m_localY;

m_localXXCov;m_localXYCov;m_lcoalYYCov;

m_pathLengthInTile;

Associations Between Tracks and ACD hits

m_arcLengthToISect;m_position;m_params;

Last Hit in Tracker

m_doca

Much more to AcdRecon

How to handle gapsStored in AcdTkrGapPocaCalculated in AcdTkrIntersectToolWhat about screw holes?

Track Error projection?How to handle bent tiles

Ambiguity about active distance around bent part

Plane v. 3D POCA calculationsCurrently meaning changes inside tile v. outside tileUsing track error projections might get rid of this

Details about using G4PropagatorSort PocaData objects by path lengthNeed to seed it, how good is energy estimate?

AcdValsTool

This Tool is simple, just extracts stuff from AcdRecon

Loop over AcdTkrHitPoca objects and extract:Largest active distance for all tracks and tilesLargest active distance for all tiles and best trackEnergies deposited in said tiles

Loop over AcdTkrGapPoca objects and extract:Smallest DOCA to gap for all ribbons and tracksSmallest DOCA to gap for all ribbons and best track

Variety of other quantitiesSummary statistics

Numbers of hit tiles, ribbonsTotal energy deposited

Generating calibrations w/ calibGenACD

Framework to make calibrationsAll calibrations are PMT based

Share lots of tools. Basically fill histograms for each PMT then fit them all at the event of the event loop

For each calibrations type, may want try a couple different fitting methodsStore all calibrations in xml files

Standalone apps to run calibrations.calibGenACD/apps

runPedestal.exerunMuonCalib_Svac.exerunVetoCalib.exerunCnoCalib.exerunRangeFit.exerunCoherentNoise.exe

Status, to do:

Code is fairly well developedStill not totally stableNeed better testing proceduresNeed performance benchmarks

Some obvious points of workCode cleanup, adhering to GLAST conventionsTrack error projectionImplementing CNO calibration generation

More subtle issuesMoving to more global use of ACD in merit tuple

Considering both signal size and active distance when deciding to which track / tile pair to storeCatching tracking errors

ACD hit patterns that implyMore studies of how to handle backsplash