Machine learning: hit time finding with a neural network

Thalmeier, Richard; Yin, H.; Aihara, H.; Aziz, T.; Bacher, S.; Bahinipati, S.; Barberio, E.; Baroncelli, Ti.; Baroncelli, To.; Basith, A. K.; Batignani, Giovanni; Bauer, A.; Behera, P. K.; Bertacchi, V.; Bettarini, S.; Bhuyan, B.; Bilka, T.; Bosi, F.; Bosisio, L.; Bozek, A.; Buchsteiner, F.; Caria, G.; Casarosa, Giulia; Ceccanti, M.; Cervenkov, D.; Czank, T.; Dash, N.; De Nuccio, M.; Doležal, Z.; Forti, F.; Friedl, M.; Gobbo, B.; Grimaldo, J. A. M.; Hara, K.; Higuchi, T.; Irmler, C.; Ishikawa, A.; Jeon, H. B.; Joo, C.; Kaleta, M.; Kandra, Jakub; Kambara, N.; Kang, K. H.; Kodyš, P.; Kohriki, T.; Koike, S.; Komarov, I.; Kumar, M.; Kumar, R.; Kun, W.; Kvasnicka, P.; La Licata, C.; Lalwani, K.; Lanceri, L.; Lee, J. Y.; Lee, S. C.; Libby, J.; Lueck, T.; Mammini, P.; Martini, A.; Mayekar, S. N.; Mohanty, G. B.; Morii, T.; Nakamura, K. R.; Natkaniec, Z.; Onuki, Y.; Ostrowicz, W.; Paladino, A.; Paoloni, E.; Park, H.; Prasanth, K.; Profeti, A.; Rashevskaya, I.; Rao, K. K.; Rizzo, G.; Resmi, P. K.; Rozanska, M.; Sahoo, D.; Sasaki, J.; Sato, N.; Schultschik, S.; Schwanda, C.; Stypula, J.; Suzuki, J.; Tanaka, S.; Tanigawa, H.; Taylor, G. N.; Tsuboyama, T.; Urquijo, P.; Vitale, L.; Watanuki, S.; Watanabe, M.; Watson, I. J.; Webb, J.; Wiechczynski, J.; Williams, S.; Zani, Laura; Belle-II SVD Collaboration,

doi:10.22323/1.343.0065

Volume 343 - Topical Workshop on Electronics for Particle Physics (TWEPP2018) - Posters

Machine learning: hit time finding with a neural network

R. Thalmeier*, H. Yin, H. Aihara, T. Aziz, S. Bacher, S. Bahinipati, E. Barberio, T. Baroncelli, T. Baroncelli, A.K. Basith, G. Batignani, A. Bauer, P.K. Behera, V. Bertacchi, S. Bettarini, B. Bhuyan, T. Bilka, F. Bosi, L. Bosisio, A. Bozek, F. Buchsteiner, G. Caria, G. Casarosa, M. Ceccanti, D. Cervenkov, T. Czank, N. Dash, M. De Nuccio, Z. Doležal, F. Forti, M. Friedl, B. Gobbo, J.A.M. Grimaldo, K. Hara, T. Higuchi, C. Irmler, A. Ishikawa, H.B. Jeon, C. Joo, M. Kaleta, J. Kandra, N. Kambara, K.H. Kang, P. Kodyš, T. Kohriki, S. Koike, I. Komarov, M. Kumar, R. Kumar, W. Kun, P. Kvasnicka, C. La Licata, K. Lalwani, L. Lanceri, J.Y. Lee, S.C. Lee, J. Libby, T. Lueck, P. Mammini, A. Martini, S.N. Mayekar, G.B. Mohanty, T. Morii, K.R. Nakamura, Z. Natkaniec, Y. Onuki, W. Ostrowicz, A. Paladino, E. Paoloni, H. Park, K. Prasanth, A. Profeti, I. Rashevskaya, K.K. Rao, G. Rizzo, P.K. Resmi, M. Rozanska, D. Sahoo, J. Sasaki, N. Sato, S. Schultschik, C. Schwanda, J. Stypula, J. Suzuki, S. Tanaka, H. Tanigawa, G.N. Taylor, T. Tsuboyama, P. Urquijo, L. Vitale, S. Watanuki, M. Watanabe, I.J. Watson, J. Webb, J. Wiechczynski, S. Williams, L. Zani and Belle-II SVD Collaborationet al. (click to show)

Full text: pdf

Pre-published on: May 21, 2019

Published on: July 25, 2019

Abstract

At the High Energy Accelerator Research Organization (KEK) in Tsukuba, Japan, the double-sided silicon strip sub-detector of the Belle II experiment is read out by 1748 APV25 chips. FPGAs perform several calculations on the digitized signals. One of them will be "Hit Time Finding": the determination of the time and amplitude of the signal peaks of each event in real time using pre-programmed neural networks. This work analyses the possibility, precision and reliability of these calculations depending on various parameters.

DOI: https://doi.org/10.22323/1.343.0065

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