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Atlas

Implementation of an Object OrientedTrack Reconstruction Model

into Multiple LHC Experiments

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Atlas Outline• Overview of LHC, CMS and Atlas• Review of the OO track reconstruction model

• Implementation of the OO model into CMS ORCA (Object-oriented Reconstruction for CMS Analysis)

• Implementation of the OO model into Atlas LVL-2 trigger reference SW and performance

• Experience and lessons learned

• Summary and prospects

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Atlas L H C

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Atlas CMS and ATLAS

CMS

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Atlas Trackers of CMS and Atlas

CMS

ATLAS

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Atlas OO Tracker Model (I)• Brief history -- Initial analysis and design by Irwin GAINES and Sijin QIAN (3/1995) -- Started C++ coding based on a Fortran Kalman filter tracking package (9/95) -- The model re-design by using STL (2/1996) -- Accomplished the tracking finding and fitting (autumn 1996) -- Ported to Windows NT (the beginning of 1997)

** a contribution published in proceedings of CHEP’97, Berlin, Germany (4/1997)

-- A partial re-design to form an abstract Track_builder class (summer 1997) -- Tested in Atlas environment (end of 1997) and started LVL-2 implem. (9/98) ** a presentation by Irwin at CHEP’98, Chicago, U.S.A. (9/1998)

-- Produced the pure C++ version (3/1999) ** a presentation by Sijin at AIHENP’99, Crete, Greece (4/1999)

-- Released to Atlas LVL-2 reference SW (5/1999) and Ctrig (8/1999) -- Preliminarily integrated into ORCA (8-9/1999)

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Atlas OO Tracker Model (II)• Main ingredients of the OO model:

– Problem statement ==> class diagram

– Function statement ==> object diagrams and message trace diagrams

• Main features of the model:– Use well known HEP concepts for classes

– Extensive use of Standard Template Library (STL), in both model design and C++ coding

– Initially successful re-use of FORTRAN legacy code (for Kalman filtering method) in the member functions of various classes; later converted them to C++ in a straightforward manner; now pure C++

– Flexible enough to be re-used in multiple HEP experiments (only implementation of layer class is different)

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Atlas

The latest

version of

class diagram

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Atlas Object DiagramsFirst scenario Second scenario

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Atlas CMS Implementation• Uses first scenario (internal hit triplets as seeds)

• Conceptual structure of “mytest.cpp” in the ORCA example directory– RecHit objects (in ORCA) are converted to “hit” object of the OO

model.

– Layer objects of OO model are instantiated with hard-wired code at this stage, can be done from ORCA tracker geometry in future.

– All classes in the OO KF tracking model are brought in straightforwardly without any major change.

• Examples of reconstructed tracks from the output log file

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Atlas

Conceptual

structure of

“mytest.cxx”

in ORCA

example

directory

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Atlas

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Atlas

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Atlas A Reconstructed Event

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Atlas Atlas Implementation (I)• LVL-2 trigger requirement (O(10ms) time slot)

==> execution time is a factor of concern.– use 2nd scenario (outside seeds)– do reconstruction in Region of Interest (RoI) instead of in full - range

• Frameworks– LVL-2 Reference Software system (OO designed, input ASCII data)– Ctrig (input from ASCII files, produce ntuples, etc.)

• Seed modes: (1) TRT guided (inward pattern recognition) (2) pixel guided (outward pattern recognition)

• Tracking corrections: (1) Multiple scattering (yes); (2) Energy loss (yes for electrons); (3) Non-uniform B field (in near

future).

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Atlas Energy Loss Correction (1/Pt) distribution (1/GeV)

1 GeV 5 GeV 20 GeVelectrons electrons electrons

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Atlas Atlas Implementation (II)• Performance:

– Execution speed (on 300 MHz Pentium II, under Linux) TRT seeded

Pixel seeded

Single (no pile-up) <1.3> ms/event -- B-physics (at low luminosity) <725> ms/event <320> ms/event

(<262> seeds) (<122> seeds)

– Memory usage is in O(10 MB), depends on data volume– Efficiencies (single track events, B-physics events)– Resolutions (momentum, impact parameter, etc.) – B-physics study in the channel B --> – Many more results are at http://www-wisconsin.cern.ch/~sijinat/lvl2/res.html

http://www-wisconsin.cern.ch/~atsaul/results/sctkalman/

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Atlas Efficiencies for and e muons electrons

–

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Atlas Efficiencies for B-physics (1) vs. Pt for e from B0 --> J/ vs.

–

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Atlas Efficiencies for B-physics (2) vs. Pt for e from B0 --> vs.

–

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Atlas Resolutions Pt 20 GeV (tops: barrel; bottoms: endcap) D0

–

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Atlas B-physics mass reconstruction

Reconstruction of

B --> mass hypothesis

in ATLAS Level-2

trigger using the

Kalman filtering method

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Atlas Lessons Learned• C++’s new features (for previous Fortran

programmers) now can be handled by some powerful debugging tools, e.g.

– “INSURE++” to detect the memory leaks– “DDD” graphic debugger to detect the pointer bugs

• Integration of an OO model into a general OO environment of whole experiment needs a stable framework with a stable interface. As soon as all functionality of I/O objects needed by the model are available, the integration is straightforward.

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Atlas Conclusions

• OO makes it easier to do cooperative development among widely separated collaborators (promotes truly modular designs)

• OO makes re-use easier: the implementation of this OO model into two LHC experiments demonstrates:

-- the implementation structure is very similar for different experiments-- the experience in code development can be shared

among different experiments immediately

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Atlas Summary and Prospects

• We are moving towards a realistic OO track reconstruction model for HEP experiments– the memory usage of this OO model is moderate– the track finding efficiency is satisfactory– the execution speed is approaching the LVL-2 trigger

requirement

• It can be used in different experiments with only minor modifications

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Atlas Ongoing and Future Work• CMS:

-- Investigate more efficient I/O functions-- Use finalized CMS detector and track classes-- Overhaul the package with CMS coding rules

• Atlas: -- Implement the non-uniform B-field correction-- Optimize the performance by investigating

new seeding methods and by exploring new reconstruction strategies