standalone fles package for event reconstruction and selection in cbm dpg -2012 mainz, 21 march 2012...

Standalone FLES Package for Event Reconstruction and Selection in CBM

DPG -2012Mainz, 21 March 2012

I. Kisel1,2, I. Kulakov1, M. Zyzak1

(for the CBM Collaboration)

1. Johann Wolfgang Goethe-Universität Frankfurt am Main2. GSI Helmholtzzentrum für Schwerionenforschung GmbH

21.03.21.03.20122012 Igor Kulakov,Igor Kulakov, Mainz, DPG-2012Mainz, DPG-2012 22/13/13

OutlineOutline

Motivation

Block diagram of the First Level Event Selection (FLES) package

Reconstruction stages:

Track reconstruction

Track fit

Particle reconstruction

Summary and plans


Tracking Challenge in CBMTracking Challenge in CBM

Simulation ReconstructionSimulation Reconstruction

Intel CPU 8 cores

CBM FLES will be based on full event reconstruction andhas to be sophisticated, fast and efficient.

• 1000 charged particles/collision• Double-sided strip detectors (85% fake space

points)• Non-homogeneous magnetic field• 107 AuAu collisions/sec• Track reconstruction in STS/MVD and

displaced vertex search are required in the first level trigger


Standalone FLES PackageStandalone FLES Package

Standalone package for FLES has been developed.

Efficient Optimized (time) SIMD-ized Parallelized

CA Track Finder

KF Track Fitter

KFParticle

Selection

Quality Check

FLESFLES

HitsGeometry Info

ROOT

Efficiencies

ASCII Files

Histograms

MC


Cellular Automaton Based Track FinderCellular Automaton Based Track Finder Track finding: Which hits in detector belong to the same track? – Cellular Automaton (CA)

Cellular Automaton:• local w.r.t. data• intrinsically parallel• extremely simple• very fast

Perfect for many-core CPU/GPU !

Cellular Automaton:• local w.r.t. data• intrinsically parallel• extremely simple• very fast

Perfect for many-core CPU/GPU !

0. Hits (CBM)

1000 Hits

4. Tracks (CBM)

1000 Tracks

Cellular Automaton:1.Build short track segments.2.Connect according to the track

model, estimate a possible position on a track.

3.Tree structures appear, collect segments into track candidates.

4.Select the best track candidates.

0. Hits

1. Segments

2 3 42. Counters

3. Track Candidates

4. Tracks

1

CA illustration: Application to straight tracks reconstruction


CA Track Reconstruction QualityCA Track Reconstruction Quality

Efficiency and ratios, %

Fast Prim Set 97.7

All Set 88.9

Clone 0.1

Ghost 0.3

Reco Tracks/ev 121

Time/ev, ms 8.2

Reconstructable track:≥ 4 consecutive MC points

All set: p ≥ 0.1 GeV/c

Fast set: p ≥ 1 GeV/cGhost: purity <

70%

CA Track Finder shows 98% efficiency for signal tracks

AuAu 25 AGeV mbias; 8 STS, 0o & 8o strips; 1000 UrQMD events; Intel [email protected] GHz


Kalman Filter Based Track FitKalman Filter Based Track FitTrack fit: Optimal estimation of the track parameters according to hits – Kalman Filter (KF)

Detector layersHits

(r, C)

r – Track parameters C – Precision

Initializing

Prediction

Correction

Precision

11

22

33

r = { x, y, tx, ty, q/p }

Position, direction and momentum

State vector

Kalman Filter: 1. Start with an arbitrary initialization.2. Add one hit after another. 3. Improve the state vector. 4. Get the optimal parameters after the last hit.

KF as a recursive least squares method

KF Block-diagram 11

22 33


pulls

resi

duals

Track Fit QualityTrack Fit Quality

Time: ~0.3 ms/eventAuAu 25 AGeV mbias; 8 STS, 0o & 8o strips; 1000 UrQMD events; Intel [email protected] GHz

residuals pulls

x, μm y, μm tx, 10-3 ty, 10-3 p, % x y tx ty q/p

9.7 92 0.48 0.77 1.07 0.7 0.7 1.1 1.1 1.3

Track fit quality is high. Momentum resolution is 1%.


KFParticle for Particle ReconstructionKFParticle for Particle Reconstruction

Concept:•

Mother and daughter particles

have same state vector and

are treated in the same way

•

Geometry independent

•

Kalman filter based

r = { x, y, z, px, py, pz,

E }

Position, momentum and energy

Particle state vector

Functionality of the package:

•Construction of the particles from tracks or another particles

•Decay chains reconstruction

•Transport of the particles (on the distance, to a point, to another particle, to vertex)

•Simple access to the particle parameters and their errors

•Calculation of the distance to point, vertex or another particle

•Calculation of the deviation from point, vertex or another particle


Particle Reconstruction StrategyParticle Reconstruction Strategy

χ2fit – χ2 given by a track fit

χ2prim – χ2 distance to a primary vertex

(PV)χ2

geo – χ2 given by a particle fitχ2

topo – χ2 of a particle fitted to PV

Tracksχ2

fit criterion

Secondary tracks

χ2prim criterion

Selected K0s and Λ Store

Selected tracks

χ2geo

criterion

check mass

Secondary Λ Primary Λ

χ2topo, zvertex criteria

Selected Λ

Primary tracks

K0s and Λ candidates

Σ*+ and Σ*- candidates

Selected Σ*+ and Σ*-

χ2geo , χ2

topo , zvertex criteria

Store

Ξ- and Ω- candidates

Selected Ξ- and Ω-

χ2geo

criterionStore


Particle Reconstruction QualityParticle Reconstruction Quality

Time: ~4 ms/event

AuAu 25 AGeV mbias; 8 STS, 0o & 8o strips; 1000 UrQMD events; Intel [email protected] GHz

Particle reconstruction algorithm has been tested with K0s and Λ

Eff = 11.3 %S/B = 1.15

Eff = 9.2 %S/B = 2.14

K0s Λ


Scalability on Many-core SystemScalability on Many-core System

Given n threads each filled with 1000 events, run them on specific n logical cores, 1 thread per 1 core.

The FLES package shows strong scalability on many-core systems.


Summary & PlansSummary & Plans

The first version of the standalone FLES package has been

developed and tested Signal tracks reconstruction efficiency is 98% Tracks momentum resolution is 1%

K0s and Λ reconstruction efficiencies are 11% and 9% with

signal to background ratios 1.2 and 2.1 Linear scalability on many-core systems Throughput of 1700 minimum bias events per second on 80-

core system

Plans: Further optimization with respect to time Full event topology reconstruction

standalone fles package for event reconstruction and selection in cbm dpg -2012 mainz, 21 march 2012...

Documents

track parameters

track finder track finding

track fit2prim

track model

track candidates4

track fittrack fit

short track segments

best track candidates