TY - JOUR
T1 - Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks
AU - COMPASS Collaboration
AU - Ahdida, C.
AU - Albanese, R. Marshall
AU - Alexandrov, A.
AU - Anokhina, A.
AU - Aoki, S.
AU - Arduini, G.
AU - Atkin, E.
AU - Azorskiy, N.
AU - Back, J. J.
AU - Bagulya, A.
AU - Santos, F. Baaltasar Dos
AU - Baranov, A.
AU - Bardou, F.
AU - Barker, G. J.
AU - Battistin, M.
AU - Bauche, J.
AU - Bay, A.
AU - Bayliss, V.
AU - Bencivenni, G.
AU - Berdnikov, A. Y.
AU - Berdnikov, Y. A.
AU - Berezkina, I.
AU - Bertani, M.
AU - Betancourt, C.
AU - Bezshyiko, I.
AU - Bezshyyko, O.
AU - Bick, D.
AU - Bieschke, S.
AU - Blanco, A.
AU - Boehm, J.
AU - Bogomilov, M.
AU - Bondarenko, K.
AU - Bonivento, W. M.
AU - Borburgh, J.
AU - Boyarsky, A.
AU - Brenner, R.
AU - Breton, D.
AU - Brundler, R.
AU - Bruschi, M.
AU - Büscher, V.
AU - Buonaura, A.
AU - Buontempo, S.
AU - Cadeddu, S.
AU - Calcaterra, A.
AU - Calviani, M.
AU - Campanelli, M.
AU - Chumakov, A.
AU - Kim, V.
AU - Lyubovitskij, V.
AU - Petrov, A.
N1 - Funding Information:
The SHiP Collaboration wishes to thank the Castaldo company (Naples, Italy) for their contribution to the development studies of the decay vessel. The support from the National Research Foundation of Korea with grant numbers of 2018R1A2B2007757, 2018R1D1A3B07050649, 2018R1D1A1B07050701, 2017R1D1A1B03036042, 2017R1A6A3A01075752, 2016R1A2B4012302, and 2016R1A6A3A11930680 is acknowledged.
Funding Information:
The support from the FCT — Fundação para a Ciência e a Tecnologia of Portugal with grant number CERN/FIS-PAR/0030/2017 is acknowledged. The support from the Russian Foundation for Basic Research (RFBR), grant 17-02-00607, the support from the TAEK of Turkey, and the
Funding Information:
support from the U.K. Science and Technology Facilities Council (STFC), grant ST/P006779/1 are acknowledged.
PY - 2019/11/27
Y1 - 2019/11/27
N2 - This paper presents a fast approach to simulating muons produced in interactions of the SPS proton beams with the target of the SHiP experiment. The SHiP experiment will be able to search for new long-lived particles produced in a 400 GeV/c SPS proton beam dump and which travel distances between fifty metres and tens of kilometers. The SHiP detector needs to operate under ultra-low background conditions and requires large simulated samples of muon induced background processes. Through the use of Generative Adversarial Networks it is possible to emulate the simulation of the interaction of 400 GeV/c proton beams with the SHiP target, an otherwise computationally intensive process. For the simulation requirements of the SHiP experiment, generative networks are capable of approximating the full simulation of the dense fixed target, offering a speed increase by a factor of (106). To evaluate the performance of such an approach, comparisons of the distributions of reconstructed muon momenta in SHiP's spectrometer between samples using the full simulation and samples produced through generative models are presented. The methods discussed in this paper can be generalised and applied to modelling any non-discrete multi-dimensional distribution.
AB - This paper presents a fast approach to simulating muons produced in interactions of the SPS proton beams with the target of the SHiP experiment. The SHiP experiment will be able to search for new long-lived particles produced in a 400 GeV/c SPS proton beam dump and which travel distances between fifty metres and tens of kilometers. The SHiP detector needs to operate under ultra-low background conditions and requires large simulated samples of muon induced background processes. Through the use of Generative Adversarial Networks it is possible to emulate the simulation of the interaction of 400 GeV/c proton beams with the SHiP target, an otherwise computationally intensive process. For the simulation requirements of the SHiP experiment, generative networks are capable of approximating the full simulation of the dense fixed target, offering a speed increase by a factor of (106). To evaluate the performance of such an approach, comparisons of the distributions of reconstructed muon momenta in SHiP's spectrometer between samples using the full simulation and samples produced through generative models are presented. The methods discussed in this paper can be generalised and applied to modelling any non-discrete multi-dimensional distribution.
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U2 - 10.1088/1748-0221/14/11/P11028
DO - 10.1088/1748-0221/14/11/P11028
M3 - Article
AN - SCOPUS:85076006499
VL - 14
JO - Journal of Instrumentation
JF - Journal of Instrumentation
SN - 1748-0221
IS - 11
M1 - P11028
ER -