KIP KIP TRACKING IN MAGNETIC FIELD TRACKING IN MAGNETIC FIELD BASED ON THE BASED ON THE CELLULAR AUTOMATON METHOD CELLULAR AUTOMATON METHOD Ivan Kisel KIP, Uni-Heidelberg Collaboration Meeting of the CBM Experiment at the Future Accelerator Facility in Darmstadt July 7 - 8, 2003
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KIP TRACKING IN MAGNETIC FIELD BASED ON THE CELLULAR AUTOMATON METHOD TRACKING IN MAGNETIC FIELD BASED ON THE CELLULAR AUTOMATON METHOD Ivan Kisel KIP,
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KIPKIP
TRACKING IN MAGNETIC FIELDTRACKING IN MAGNETIC FIELDBASED ON THEBASED ON THECELLULAR AUTOMATON METHODCELLULAR AUTOMATON METHOD
Ivan KiselKIP, Uni-Heidelberg
Collaboration Meeting of theCBM Experiment at the Future Accelerator Facility in DarmstadtJuly 7 - 8, 2003
July 7-8, 2003 Ivan Kisel - Tracking in Magnetic Field based on the Cellular Automaton Method 2
KIPKIP
Straight line Parabola
SIMULATED DATA:YZ (non-bending) / XZ (bending)
SIMULATED DATA:YZ (non-bending) / XZ (bending)
TRACK MODEL:
July 7-8, 2003 Ivan Kisel - Tracking in Magnetic Field based on the Cellular Automaton Method 3
KIPKIP
MC Truth -> YES
PERFORMANCE•Evaluation of efficiencies•Evaluation of resolutions•Histogramming•Timing•Statistics•Event display
MC Truth -> NO
RECONSTRUCTION•Fetch ROOT MC data•Copy to local arrays and sort•Create segments•Link segments•Create track candidates•Select tracks
RECONSTRUCTION PROGRAMRECONSTRUCTION PROGRAM
Main ProgramMain Program
Event LoopEvent Loop
Reconstruction PartReconstruction Part
Performance PartPerformance Part
July 7-8, 2003 Ivan Kisel - Tracking in Magnetic Field based on the Cellular Automaton Method 4
Being essentially local and parallel cellular automata avoid exhaustive combinatorial searches, even when implemented on conventional computers. . Since cellular automata operate with highly structured information (for instance sets of track segments connecting space points), the amount of data to be processed in the course of the track search is significantly reduced. . Further reduction of information to be processed is achieved by smart definition of the segment neighborhood. Usually cellular automata employ a very simple track model which leads to utmost computational simplicity and a fast algorithm. .
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Define : •CELLS CELLS
•NEIGHBORS NEIGHBORS •RULES RULES
•EVOLUTIONEVOLUTION
Define : •CELLS CELLS
•NEIGHBORS NEIGHBORS •RULES RULES
•EVOLUTIONEVOLUTION
Create segments
Collect tracks
July 7-8, 2003 Ivan Kisel - Tracking in Magnetic Field based on the Cellular Automaton Method 5
KIPKIPTRACK CATEGORIESTRACK CATEGORIES
RECONSTRUCTED TRACK ?RECONSTRUCTED TRACK ?
ALL MC TRACKSALL MC TRACKS
RECONSTRUCTABLE TRACKS
Number of hits >= 3
REFERENCE TRACKS
Momentum > 1 GeV
70%
100%
% OF CORRECT HITS FITTING ACCURACY
% OF CORRECT HITS FITTING ACCURACY
noise
July 7-8, 2003 Ivan Kisel - Tracking in Magnetic Field based on the Cellular Automaton Method 6
July 7-8, 2003 Ivan Kisel - Tracking in Magnetic Field based on the Cellular Automaton Method 12
KIPKIP
• Track search with digitized detector• Track fit including multiple scattering• FPGA adapted algorithm• Development of a trigger architecture• Build a trigger prototype
• Track search with digitized detector• Track fit including multiple scattering• FPGA adapted algorithm• Development of a trigger architecture• Build a trigger prototype