Track Finding for the PANDA Detector Based on Hough Transformations
The PANDA experiment at FAIR (Facility for Antiproton and Ion Research) in Darmstadt is currently under construction. In order to reduce the amount of data collected during operation, it is essential to find as many true tracks as possible and to be able to distinguish them from false tracks. Part o...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2021-01-01
|
Series: | EPJ Web of Conferences |
Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_04002.pdf |
id |
doaj-f595e5f32b5b4075956232a781ccd84c |
---|---|
record_format |
Article |
spelling |
doaj-f595e5f32b5b4075956232a781ccd84c2021-08-26T09:27:32ZengEDP SciencesEPJ Web of Conferences2100-014X2021-01-012510400210.1051/epjconf/202125104002epjconf_chep2021_04002Track Finding for the PANDA Detector Based on Hough TransformationsAlicke Anna0Stockmanns Tobias1Ritman JamesForschungszentrum Jülich, Institut für KernphysikForschungszentrum Jülich, Institut für KernphysikThe PANDA experiment at FAIR (Facility for Antiproton and Ion Research) in Darmstadt is currently under construction. In order to reduce the amount of data collected during operation, it is essential to find as many true tracks as possible and to be able to distinguish them from false tracks. Part of the preparation for the experiment is the development of a fast online track finder. This work presents an online track finding algorithm based on Hough transformations, which is comparable in quality and performance to the currently best offline track finder in PANDA. In contrast to most track finders the algorithm can handle the challenge of extended hits delivered by PANDA’s central Straw Tube Tracker and thus benefit from its precise spatial resolution. Furthermore, optimization methods are presented that improved the ghost ratio as well as the speed of the algorithm by 70 %. Due to further development potential in terms of track finding for secondary particles and speed optimization on GPUs, this algorithm promises to exceed the quality and speed of other track finders developed for PANDA.https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_04002.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alicke Anna Stockmanns Tobias Ritman James |
spellingShingle |
Alicke Anna Stockmanns Tobias Ritman James Track Finding for the PANDA Detector Based on Hough Transformations EPJ Web of Conferences |
author_facet |
Alicke Anna Stockmanns Tobias Ritman James |
author_sort |
Alicke Anna |
title |
Track Finding for the PANDA Detector Based on Hough Transformations |
title_short |
Track Finding for the PANDA Detector Based on Hough Transformations |
title_full |
Track Finding for the PANDA Detector Based on Hough Transformations |
title_fullStr |
Track Finding for the PANDA Detector Based on Hough Transformations |
title_full_unstemmed |
Track Finding for the PANDA Detector Based on Hough Transformations |
title_sort |
track finding for the panda detector based on hough transformations |
publisher |
EDP Sciences |
series |
EPJ Web of Conferences |
issn |
2100-014X |
publishDate |
2021-01-01 |
description |
The PANDA experiment at FAIR (Facility for Antiproton and Ion Research) in Darmstadt is currently under construction. In order to reduce the amount of data collected during operation, it is essential to find as many true tracks as possible and to be able to distinguish them from false tracks. Part of the preparation for the experiment is the development of a fast online track finder. This work presents an online track finding algorithm based on Hough transformations, which is comparable in quality and performance to the currently best offline track finder in PANDA. In contrast to most track finders the algorithm can handle the challenge of extended hits delivered by PANDA’s central Straw Tube Tracker and thus benefit from its precise spatial resolution. Furthermore, optimization methods are presented that improved the ghost ratio as well as the speed of the algorithm by 70 %. Due to further development potential in terms of track finding for secondary particles and speed optimization on GPUs, this algorithm promises to exceed the quality and speed of other track finders developed for PANDA. |
url |
https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_04002.pdf |
work_keys_str_mv |
AT alickeanna trackfindingforthepandadetectorbasedonhoughtransformations AT stockmannstobias trackfindingforthepandadetectorbasedonhoughtransformations AT ritmanjames trackfindingforthepandadetectorbasedonhoughtransformations |
_version_ |
1721195838049353728 |