Tracker SoftwareMECO/Mu2e Experience

Yury KolomenskyUC Berkeley/LBNL

January 24, 2008

01/24/2009 YGK, Tracker Software

History• Mu2e: benefit from years of detailed studies for

MECO Also inherited the code base, which I will briefly

review here Present effort: new, unified simulation/reconstruction

platform, modern software tools and algorithms Rob Kutschke et al Based on (lighter) CMS Framework Would make it easier to adapt new pattern recognition,

track fitting algorithms, use existing HEP code base

01/24/2009 YGK, Tracker Software

MECO Software Overview• Two simulations packages, based on Geant3 and Geant4

GMC (G3): most developed, used by Mu2e Detailed geometry, field maps Beamline simulations, signal and backgrounds Tightly integrated pattern recognition/tracking for L-tracker

Standalone G3 for T-tracker simulations Step-wise approach: simulate signals and backgrounds, read into

separate (C++-based) reco code Rudimentary G4/C++

Some work by Vladimir Tumakov on porting MECO geometry Some work at Irvine (Paul Huwe) on porting L-tracker PatRec to C+

+

• No hardware response (hit digitization, efficiency) Resolution smearing

01/24/2009 YGK, Tracker Software

Longitudinal TrackerGeometry: Octagon with Eight Vanes

Straws: 2.9 m length 5mm diameter, 25 mm thickness – 2800 total

Three layers per plane, outer two resistive, inner conductingPads: 30 cm 5mm wide cathode strips affixed to outer straws

18500 total pads

Position Resolution: 0.2 mm (r,f) 1.5 mm (z)

Readout Channels: 20k each of ADC & TDC

Main advantage: pattern recognition, intrinsic momentum resolution (180o spectrometer)

01/24/2009 YGK, Tracker Software

Transverse TrackerGeometry: 18 Modules of three planes each, 30° rotation between

successive planes

Straws: 70 – 130 cm length 5mm diameter, 15 or 25 mm thickness

12960 total straws

One layer per plane

All straws conducting

Position Resolution: 0.2 mm (x,y)

Main advantage: mechanical

Biggest issue: pattern recognition

01/24/2009 YGK, Tracker Software

Tracker Simulations

• Simulations, reproduced by Mu2e Detailed geometries, including straw walls, wires, gas

manifolds Noise hits, at nominal and double rate, including highly-

ionizing protons Energy loss and straggling in the stopping target L-tracker: Gaussian resolution model and average hit

efficiency, “salt and pepper” backgrounds superimposed T-tracker: more sophisticated PatRec, including L-R

ambiguities

• What wasn’t specifically done Hit digitization Limited scope: upshifting DIO electrons due to PatRec errors

01/24/2009 YGK, Tracker Software

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L-Tracker Reconstruction

• Helical pattern recognition based on space-points

• Likelihood-based fitter

• Reasonably robust against background hits

• Intrinsic momentum resolution ~180 keV

• Efficiency ~19%

QuickTime™ and aTIFF (Uncompressed) decompressor

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T-Tracker: Deterministic Annealing Filter

• Left and Right points are projected on straw center layer using fitted helix• Calculate point prob Gauss(Xi,

Mean, Vn)• Kalman filter runs on all layers taking weighted mean according to point prob • If combined hit prob < Threshold hit is rejected• Combinatorial Collapse Filter (CCF) treats Left-Right problem keeping a set of best choices• CPU-intensive

01/24/2009 YGK, Tracker Software

T-Tracker Resolution

• Nominal background and 25 µm

• Delta-ray and straw inefficiency

• Average straw rate 550 kHz

• Kalman filter reconstruction

• Intrinsic Resolution

= 190 keV

• Average efficiency ~19%

Prec-Pgen

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Mu2e Software

• Goal: integrated simulation/reconstruction framework using modern tools and practices Ongoing work by CD @ FNAL (R.Kutschke et al.) “CMS-lite” implementation Provide overall distribution/build/runtime

infrastructure Geometry, constants management “Grid-enabled” to facilitate parallel farm processing Options for “one-shot” sim/reco process, or step-wise

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Infrastructure Deliverables1) Framework proper

2) Services

3) Configuration

4) Geometry shell

5) Simulation shell

6) IO system

7) Initial documentation

8) Conditions

9) Full featured build and release mgt

10)Grid features

11) Full documentation

Rob Kutschke

~ Immediate future

Later

01/24/2009 YGK, Tracker Software

Opportunities for Collaboration

• Common infrastructure, tools ? Take advantage of FNAL CPU farm Facilitate comparisons between options

• Cooperation on algorithms and simulations Backgrounds Pattern recognition/fitting

Even if the details of geometry are different, concepts are the same