Using deep neural networksto improve the precision of fast-sampled particle timing detectors

• Autorzy: Kocot Mateusz , Misan Krzysztof , Avati Valentina , Bossini Edoardo , Grzanka Leszek , Minafra Nicola

Identyfikatory

DOI

10.7494/csci.2024.25.1.5784

• Języki publikacji: EN

Abstrakty

EN

Measurements from particle timing detectors are often affected by the timewalk effect caused by statistical fluctuations in the charge deposited by passingparticles. The constant fraction discriminator (CFD) algorithm is frequentlyused to mitigate this effect both in test setups and in running experiments,such as the CMS-PPS system at the CERN’s LHC. The CFD is simple andeffective but does not leverage all voltage samples in a time series. Its performance could be enhanced with deep neural networks, which are commonlyused for time series analysis, including computing the particle arrival time. Weevaluated various neural network architectures using data acquired at the testbeam facility in the DESY-II synchrotron, where a precise MCP (MicroChan-nel Plate) detector was installed in addition to PPS diamond timing detectors.MCP measurements were used as a reference to train the networks and com-pare the results with the standard CFD method. Ultimately, we improved thetiming precision by 8% to 23%, depending on the detector’s readout channel.The best results were obtained using a UNet-based model, which outperformedclassical convolutional networks and the multilayer perceptron.

Słowa kluczowe

EN

deep neural network; timing detectors; iamond sensors; time series analysis; time walk correction; CERN; Precision Proton Spectrometer

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2024
• Tom: T. 25 (1)
• Strony: 43--61
• Opis fizyczny: Bibliogr. 28 poz., rys., tab., wykr.

Twórcy

autor

Kocot Mateusz

• AGH University of Krakow, Krakow, Poland

autor

Misan Krzysztof

• AGH University of Krakow, Krakow, Poland

autor

Avati Valentina

• AGH University of Krakow, Krakow, Poland

autor

Bossini Edoardo

• INFN Sezione di Pisa, Pisa, Italy

autor

Grzanka Leszek

• AGH University of Krakow, Krakow, Poland

autor

Minafra Nicola

• University of Kansas, Department of Physics and Astronomy, Lawrence, KS, United States

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