Denoising 3D Time Projection Chamber data using convolutional neural networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21670%2F25%3A00390190" target="_blank" >RIV/68407700:21670/25:00390190 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1088/1748-0221/20/05/C05014" target="_blank" >https://doi.org/10.1088/1748-0221/20/05/C05014</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1088/1748-0221/20/05/C05014" target="_blank" >10.1088/1748-0221/20/05/C05014</a>
Alternative languages
Result language
angličtina
Original language name
Denoising 3D Time Projection Chamber data using convolutional neural networks
Original language description
Spurious signals caused by microdischarges are a known effect inherent to all gaseous detectors. During the reconstruction in imaging and tracking detectors, such as time projection chambers, these signals are added to the actual track-generated signal as extra pixels or clusters, compromising the performance of the detector. The usual approach to remove these noise patterns is by hardware-dependent heuristics and conditions. In this work, we study the usage of denoising convolutional neural networks (NN) to clean the signals from a Time Projection Chamber (TPC) prototype. We show that this denoising provides also a tool for the selection and rejection of detector events that do not contain any track. The output provided by the neural network is compared with the results obtained using a conventional algorithm. The Physics of the events measured by the detector (such as the shape of the tracks) is used to assess and compare the quality of the two algorithms and how much they improve the existing data set.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10300 - Physical sciences
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Instrumentation
ISSN
1748-0221
e-ISSN
1748-0221
Volume of the periodical
20
Issue of the periodical within the volume
5
Country of publishing house
IT - ITALY
Number of pages
2
Pages from-to
1-2
UT code for WoS article
001490735100001
EID of the result in the Scopus database
2-s2.0-105005203949