Elsevier B.V. : Machine Learning based tool for CMS RPC currents quality monitoring

Shumka, E.; Hong, B.; Pugliese, G.; Gouzevitch, M.; Shopova, M.; Pedraza, I.; Nogima, H.; Petkov, P.; Ramos, D.; Asghar, I.; Choi, S.Y.; Aly, R.; Bagaturia, I.; Song, J.; Loddo, F.; Zhao, J.; Kim, T.J.; Santoro, A.; Ebraimi, M.; Abbrescia, M.; Eysermans, J.; Lee, K.S.; Assran, Y.; Lista, L.; Hoorani, H.; Vitulo, P.; Marujo, F.; Zaganidis, N.; Oh, H.Y.; Lomidze, I.; Filho, M. Barroso Ferreira; Tsamalaidze, Z.; Fienga, F.; Pavlov, B.; Piccolo, D.; Reyes, J.; Castilla-Valdez, H.; Petrov, A.; Elmetenawee, W.; Mota Amarilo, K.; Kou, H.; Barbosa, D.; Alves, G.A.; Goh, J.; Mirabito, L.; Aleksandrov, A.; Asilar, E.; Mohammadi Najafabadi, M.; Crotty, I.; Amoozegar, V.; Benussi, L.; Dimitrov, A.; Hadjiiska, R.; Qian, S.J.; Paesani, D.; Grenier, G.; Coelho, E.A.; De Souza, S. Fonseca; Fraga, J.; Thiel, M.; Florez, A.; Sanchez-Hernandez, A.; Ramirez-Garcia, M.; Tytgat, M.; Buontempo, S.; Riccardi, C.; Litov, L.; Samalan, A.; Ahmad, A.; Montagna, P.; Meola, S.; Mahmoud, M.A.; Muhammad, S.; Paolucci, P.; Rodozov, M.; Radi, A.; Estrada, C. Uribe; Margjeka, I.; Zareian, E.; Shah, M.A.; Leszki, S.; Mohammed, Y.; Cao, P.; Vazquez, E.; Boghrati, B.; Liu, Z.-A.; Braghieri, A.; Diao, W.; De Filippis, N.; Yu, I.; Fernandez, R.L.; Salvini, P.; Avila, C.; Shchablo, K.; Carnevali, F.; Soultanov, G.; Sawy, M. El; Choi, J.; De Jesus Damiao, D.; Hou, Q.; Iaselli, G.; Da Silva De Araujo, F. Torres; Cabrera, A.; Laktineh, I.; Bianco, S.; Da Costa, E.M.; Khan, W.A.; Iaydjiev, P.

doi:10.1016/j.nima.2023.168449

Article
Report number	arXiv:2302.02764
Title	Machine Learning based tool for CMS RPC currents quality monitoring
Author(s)	Shumka, E. (Sofiya U.) ; Samalan, A. (Gent U.) ; Tytgat, M. (Gent U.) ; Sawy, M. El (Brussels U.) ; Alves, G.A. (Rio de Janeiro, CBPF) ; Marujo, F. (Rio de Janeiro, CBPF) ; Coelho, E.A. (Rio de Janeiro, CBPF) ; Da Costa, E.M. (Rio de Janeiro State U.) ; Nogima, H. (Rio de Janeiro State U.) ; Santoro, A. (Rio de Janeiro State U.) ; De Souza, S. Fonseca (Rio de Janeiro State U.) ; De Jesus Damiao, D. (Rio de Janeiro State U.) ; Thiel, M. (Rio de Janeiro State U.) ; Mota Amarilo, K. (Rio de Janeiro State U.) ; Filho, M. Barroso Ferreira (Rio de Janeiro State U.) ; Aleksandrov, A. (Sofiya, Inst. Nucl. Res.) ; Hadjiiska, R. (Sofiya, Inst. Nucl. Res.) ; Iaydjiev, P. (Sofiya, Inst. Nucl. Res.) ; Rodozov, M. (Sofiya, Inst. Nucl. Res.) ; Shopova, M. (Sofiya, Inst. Nucl. Res.) ; Soultanov, G. (Sofiya, Inst. Nucl. Res.) ; Dimitrov, A. (Sofiya U.) ; Litov, L. (Sofiya U.) ; Pavlov, B. (Sofiya U.) ; Petkov, P. (Sofiya U.) ; Petrov, A. (Sofiya U.) ; Qian, S.J. (Peking U.) ; Kou, H. (Beijing, Inst. High Energy Phys. ; Beijing, GUCAS) ; Liu, Z.-A. (Beijing, Inst. High Energy Phys. ; Beijing, GUCAS) ; Zhao, J. (Beijing, Inst. High Energy Phys. ; Beijing, GUCAS) ; Song, J. (Beijing, Inst. High Energy Phys. ; Beijing, GUCAS) ; Hou, Q. (Beijing, Inst. High Energy Phys. ; Beijing, GUCAS) ; Diao, W. (Beijing, Inst. High Energy Phys. ; Beijing, GUCAS) ; Cao, P. (Beijing, Inst. High Energy Phys. ; Beijing, GUCAS) ; Avila, C. (Andes U., Bogota) ; Barbosa, D. (Andes U., Bogota) ; Cabrera, A. (Andes U., Bogota) ; Florez, A. (Andes U., Bogota) ; Fraga, J. (Andes U., Bogota) ; Reyes, J. (Andes U., Bogota) ; Assran, Y. (Egyptian Ctr. Theor. Phys., Cairo ; Suez Canal U.) ; Mahmoud, M.A. (Fayoum U.) ; Mohammed, Y. (Fayoum U.) ; Crotty, I. (Fayoum U.) ; Laktineh, I. (IP2I, Lyon) ; Grenier, G. (IP2I, Lyon) ; Gouzevitch, M. (IP2I, Lyon) ; Mirabito, L. (IP2I, Lyon) ; Shchablo, K. (IP2I, Lyon) ; Bagaturia, I. (GTU, Tbilisi) ; Lomidze, I. (GTU, Tbilisi) ; Tsamalaidze, Z. (GTU, Tbilisi) ; Amoozegar, V. (IPM, Tehran) ; Boghrati, B. (IPM, Tehran ; Damghan U.) ; Ebraimi, M. (IPM, Tehran) ; Mohammadi Najafabadi, M. (IPM, Tehran) ; Zareian, E. (IPM, Tehran) ; Abbrescia, M. (Bari U. ; INFN, Bari) ; Iaselli, G. (Bari U. ; INFN, Bari) ; Pugliese, G. (Bari U. ; INFN, Bari) ; Loddo, F. (Bari U. ; INFN, Bari) ; De Filippis, N. (Bari U. ; INFN, Bari) ; Aly, R. (Bari U. ; INFN, Bari) ; Ramos, D. (Bari U. ; INFN, Bari) ; Elmetenawee, W. (Bari U. ; INFN, Bari) ; Leszki, S. (Bari U. ; INFN, Bari) ; Margjeka, I. (Bari U. ; INFN, Bari) ; Paesani, D. (Bari U. ; INFN, Bari) ; Benussi, L. (Frascati) ; Bianco, S. (Frascati) ; Piccolo, D. (Frascati) ; Meola, S. (Frascati) ; Buontempo, S. (Guglielmo Marconi U. ; U. Rome 2, Tor Vergata (main) ; INFN, Naples) ; Carnevali, F. (Guglielmo Marconi U. ; U. Rome 2, Tor Vergata (main) ; INFN, Naples) ; Lista, L. (Guglielmo Marconi U. ; U. Rome 2, Tor Vergata (main) ; INFN, Naples) ; Paolucci, P. (Guglielmo Marconi U. ; U. Rome 2, Tor Vergata (main) ; INFN, Naples) ; Fienga, F. (Naples U.) ; Braghieri, A. (INFN, Pavia) ; Salvini, P. (INFN, Pavia) ; Montagna, P. (INFN, Pavia) ; Riccardi, C. (INFN, Pavia) ; Vitulo, P. (INFN, Pavia) ; Asilar, E. (Hanyang U.) ; Choi, J. (Hanyang U.) ; Kim, T.J. (Hanyang U.) ; Choi, S.Y. (Korea U.) ; Hong, B. (Korea U.) ; Lee, K.S. (Korea U.) ; Oh, H.Y. (Korea U.) ; Goh, J. (Kyung Hee U.) ; Yu, I. (Sungkyunkwan U.) ; Estrada, C. Uribe (Puebla U., Mexico) ; Pedraza, I. (Puebla U., Mexico) ; Castilla-Valdez, H. (CINVESTAV, IPN) ; Sanchez-Hernandez, A. (CINVESTAV, IPN) ; Fernandez, R.L. (CINVESTAV, IPN) ; Ramirez-Garcia, M. (Iberoamericana U.) ; Vazquez, E. (Iberoamericana U.) ; Shah, M.A. (Iberoamericana U.) ; Zaganidis, N. (Iberoamericana U.) ; Radi, A. (Sultan Qaboos U. ; Ain Shams U., Cairo) ; Hoorani, H. (NCP, Islamabad) ; Muhammad, S. (NCP, Islamabad) ; Ahmad, A. (NCP, Islamabad) ; Asghar, I. (NCP, Islamabad) ; Khan, W.A. (NCP, Islamabad) ; Eysermans, J. (MIT, Cambridge, CTP) ; Da Silva De Araujo, F. Torres (Aachen, Tech. Hochsch.)
Collaboration	CMS Muon Group
Publication	2023-06-15
Imprint	2023-02-06
Number of pages	6
In:	Nucl. Instrum. Methods Phys. Res., A 1054 (2023) 168449
In:	16th Workshop on Resistive Plate Chambers and Related Detectors (RPC 2022), CERN, Geneva, Switzerland, 26-30 Sep 2022, pp.168449
DOI	10.1016/j.nima.2023.168449 (publication)
Subject category	hep-ex ; Particle Physics - Experiment ; physics.ins-det ; Detectors and Experimental Techniques
Accelerator/Facility, Experiment	CERN LHC ; CMS
Abstract	The muon system of the CERN Compact Muon Solenoid (CMS) experiment includes more than a thousand Resistive Plate Chambers (RPC). They are gaseous detectors operated in the hostile environment of the CMS underground cavern on the Large Hadron Collider where pp luminosities of up to $2\times 10^{34}$$\text{cm}^{-2}\text{s}^{-1}$ are routinely achieved. The CMS RPC system performance is constantly monitored and the detector is regularly maintained to ensure stable operation. The main monitorable characteristics are dark current, efficiency for muon detection, noise rate etc. Herein we describe an automated tool for CMS RPC current monitoring which uses Machine Learning techniques. We further elaborate on the dedicated generalized linear model proposed already and add autoencoder models for self-consistent predictions as well as hybrid models to allow for RPC current predictions in a distant future.
Copyright/License	preprint: (License: CC BY 4.0) publication: © 2023-2024 The Author(s) (License: CC BY-NC 4.0)