Bulletin of the American Physical Society
5th Joint Meeting of the APS Division of Nuclear Physics and the Physical Society of Japan
Volume 63, Number 12
Tuesday–Saturday, October 23–27, 2018; Waikoloa, Hawaii
Session DH: Mini-Symposium: Active Target Techniques for Studies with Exotic Beams
9:00 AM–12:00 PM,
Thursday, October 25, 2018
Hilton
Room: Kona 2/3
Chair: Andrew Rogers, University of Massachusetts, Lowell
Abstract ID: BAPS.2018.HAW.DH.9
Abstract: DH.00009 : Machine Learning Methods for Track Classification in the AT-TPC
11:15 AM–11:30 AM
Presenter:
Michelle Perry Kuchera
(Davidson College)
Authors:
Michelle Perry Kuchera
(Davidson College)
Jack Z Taylor
(Davidson College)
Raghu Ramanujan
(Davidson College)
Daniel Bazin
(Michigan State University)
Joshua W Bradt
(Michigan State University)
Track classification methods were evaluated for reaction products in the Active-Target Time Projection Chamber (AT-TPC) at the National Superconducting Cyclotron Laboratory (NSCL). Single-class, binary, and multi-class event classification methods were benchmarked on data produced by the $^{46}$Ar(p,p) experiment which ran at the NSCL in September of 2015. The experiment ran with a 1.68 T magnetic field parallel to the beam axis, producing spiral tracks. Results from logistic regression, feed-forward neural networks, convolutional neural networks, and support vector machines will be presented. We will compare classification of experimental data with simulated training data versus experimental training data. Recommendations for choosing appropriate event classification methods in future AT-TPC experiments will be made.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.HAW.DH.9
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