Tracker Software MECO/Mu2e Experience Yury Kolomensky UC Berkeley/LBNL January 24, 2008

01/24/2009YGK, 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

01/24/2009YGK, 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

01/24/2009YGK, Tracker Software Longitudinal Tracker Geometry: Octagon with Eight Vanes Straws:2.9 m length  5mm diameter, 25 mm thickness – 2800 total Three layers per plane, outer two resistive, inner conducting Pads:30 cm  5mm wide cathode strips affixed to outer straws 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 (180 o spectrometer)

01/24/2009YGK, Tracker Software Transverse Tracker Geometry: 18 Modules of three planes each, 30° rotation between successive planes Straws: 70 – 130 cm length  5mm diameter, 15 or 25 mm thickness total straws One layer per plane All straws conducting Position Resolution: 0.2 mm (x,y) Main advantage: mechanical Biggest issue: pattern recognition

01/24/2009YGK, 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

01/24/2009YGK, Tracker Software 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%

01/24/2009YGK, Tracker Software 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

01/24/2009YGK, 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% P rec -P gen

01/24/2009YGK, Tracker Software Mu2e Software Goal: integrated simulation/reconstruction framework using modern tools and practices  Ongoing work by 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

01/24/2009YGK, Tracker Software Infrastructure Deliverables 1)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

01/24/2009YGK, 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