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May 8 – 12, 2023
Norfolk Waterside Marriott
US/Eastern timezone

A Kinematic Kalman Filter Track Reconstruction Algorithm for the Mu2e Experiment

May 9, 2023, 2:00 PM
15m
Hampton Roads Ballroom VIII (Norfolk Waterside Marriott)

Hampton Roads Ballroom VIII

Norfolk Waterside Marriott

235 East Main Street Norfolk, VA 23510
Oral Track 6 - Physics Analysis Tools Track 6 - Physics Analysis Tools

Speaker

Brown, David (LBL)

Description

The primary physics goal of the Mu2e experiment requires reconstructing an isolated 105 MeV electron with better than 500 KeV/c momentum resolution. Mu2e uses a low-mass straw tube tracker, and a CsI crystal calorimeter, to reconstruct tracks.
In this paper, we present the design and performance of a track reconstruction algorithm optimized for Mu2e’s unusual requirements. The algorithm is based on the KinKal kinematic Kalman filter track fit package. KinKal supports multiple track parameterizations, including one optimized for looping tracks, such as Mu2e signal tracks, and others optimized for straight or slightly-curved tracks, such as the high-momentum (P>1 GeV/c) cosmic ray muons used to calibrate and align the Mu2e detectors. All KinKal track parameterizations include the track origin time, to correctly model correlations arising from measurements that couple time and space, such as the straw drift time or the calorimeter cluster time. KinKal employs magnetic field inhomogeneity and material effect correction algorithms with 10-4 fractional precision. The Mu2e fit uses Artificial Neural Net functions to discriminate background hits from signal hits, and to resolve the straw tube hit left-right ambiguity, while iterating the extended Kalman filter. The efficiency, accuracy, and precision of the Mu2e track reconstruction, as tested on detailed simulations of Mu2e data, will be presented.

Consider for long presentation No

Primary author

Co-author

Bonventre, Richard (Lawrence Berkeley National Lab)

Presentation materials

Peer reviewing

Paper