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arxiv: 1012.5508 · v1 · pith:B3EHFDVMnew · submitted 2010-12-26 · ⚛️ physics.ins-det · hep-ex

A new approach in modeling the response of RPC detectors

L. Benussi (1) , S. Bianco (1) , S.Colafranceschi (1 , 2 , 3) , F.L. Fabbri (1) , M. Giardoni (1) , L. Passamonti (1)
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D. Piccolo (1) D. Pierluigi (1) A. Russo (1) G. Saviano (1 2) S. Buontempo (4) A. Cimmino (4 5) M. de Gruttola (4 F Fabozzi (4) A.O.M. Iorio (4 L. Lista (4) P. Paolucci (4) P. Baesso (6) G. Belli (6) D. Pagano (6) S.P. Ratti (6) A. Vicini (6) P. Vitulo (6) C. Viviani (6) A. Sharma (3) A. K. Bhattacharyya (3) ((1) INFN Laboratori Nazionali di Frascati Via E. Fermi Italy (2) Sapienza Universit`a degli Studi di Roma "La Sapienza" Piazzale A. Moro Roma Italy (3) CERN CH-1211 Gen\'eve 23 F-01631 Switzerland (4) INFN Sezione di Napoli Complesso Universitario di Monte Sant'Angelo (5) Universit`a di Napoli Federico II Complesso Universitario di Monte Sant'Angelo (6) INFN Sezione di Pavia Universit`degli studi di Pavia Via Bassi Italy)
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classification ⚛️ physics.ins-det hep-ex
keywords detectorsresponseapproachalgorithmartificialbeencommissioningconditions
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The response of RPC detectors is highly sensitive to environmental variables. A novel approach is presented to model the response of RPC detectors in a variety of experimental conditions. The algorithm, based on Artificial Neural Networks, has been developed and tested on the CMS RPC gas gain monitoring system during commissioning.

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