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@article{Ahdida:2019:11/P11028,
author = {Ahdida, C and Albanese, R and Alexandrov, A and Anokhina, A and Aoki, S and Arduini, G and Atkin, E and Azorskiy, N and Back, JJ and Bagulya, A and Dos, Santos FB and Baranov, A and Bardou, F and Barker, GJ and Battistin, M and Bauche, J and Bay, A and Bayliss, V and Bencivenni, G and Berdnikov, AY and Berdnikov, YA and Berezkina, I and Bertani, M and Betancourt, C and Bezshyiko, I and Bezshyyko, O and Bick, D and Bieschke, S and Blanco, A and Boehm, J and Bogomilov, M and Bondarenko, K and Bonivento, WM and Borburgh, J and Boyarsky, A and Brenner, R and Breton, D and Brundler, R and Bruschi, M and Bscher, V and Buonaura, A and Buontempo, S and Cadeddu, S and Calcaterra, A and Calviani, M and Campanelli, M and Casolino, M and Charitonidis, N and Chau, P and Chauveau, J and Chepurnov, A and Chernyavskiy, M and Choi, K-Y and Chumakov, A and Ciambrone, P and Congedo, L and Cornelis, K and Cristinziani, M and Crupano, A and Dallavalle, GM and Datwyler, A and D'Ambrosio, N and D'Appollonio,},
doi = {11/P11028},
journal = {Journal of Instrumentation},
pages = {1--19},
title = {Fast simulation of muons produced at the SHiP experiment using generative adversarial networks},
url = {http://dx.doi.org/10.1088/1748-0221/14/11/P11028},
volume = {14},
year = {2019}
}

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TY  - JOUR
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 Script O(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.
AU  - Ahdida,C
AU  - Albanese,R
AU  - Alexandrov,A
AU  - Anokhina,A
AU  - Aoki,S
AU  - Arduini,G
AU  - Atkin,E
AU  - Azorskiy,N
AU  - Back,JJ
AU  - Bagulya,A
AU  - Dos,Santos FB
AU  - Baranov,A
AU  - Bardou,F
AU  - Barker,GJ
AU  - Battistin,M
AU  - Bauche,J
AU  - Bay,A
AU  - Bayliss,V
AU  - Bencivenni,G
AU  - Berdnikov,AY
AU  - Berdnikov,YA
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,WM
AU  - Borburgh,J
AU  - Boyarsky,A
AU  - Brenner,R
AU  - Breton,D
AU  - Brundler,R
AU  - Bruschi,M
AU  - Bscher,V
AU  - Buonaura,A
AU  - Buontempo,S
AU  - Cadeddu,S
AU  - Calcaterra,A
AU  - Calviani,M
AU  - Campanelli,M
AU  - Casolino,M
AU  - Charitonidis,N
AU  - Chau,P
AU  - Chauveau,J
AU  - Chepurnov,A
AU  - Chernyavskiy,M
AU  - Choi,K-Y
AU  - Chumakov,A
AU  - Ciambrone,P
AU  - Congedo,L
AU  - Cornelis,K
AU  - Cristinziani,M
AU  - Crupano,A
AU  - Dallavalle,GM
AU  - Datwyler,A
AU  - D'Ambrosio,N
AU  - D'Appollonio,G
AU  - De,Carvalho Saraiva J
AU  - De,Lellis G
AU  - de,Magistris M
AU  - De,Roeck A
AU  - De,Serio M
AU  - De,Simone D
AU  - Dedenko,L
AU  - Dergachev,P
AU  - Di,Crescenzo A
AU  - Di,Marco N
AU  - Dib,C
AU  - Dijkstra,H
AU  - Dipinto,P
AU  - Dmitrenko,V
AU  - Dmitrievskiy,S
AU  - Dougherty,LA
AU  - Dolmatov,A
AU  - Domenici,D
AU  - Donskov,S
AU  - Drohan,V
AU  - Dubreuil,A
AU  - Ehlert,M
AU  - Enik,T
AU  - Etenko,A
AU  - Fabbri,F
AU  - Fabbri,L
AU  - Fabich,A
AU  - Fedin,O
AU  - Fedotovs,F
AU  - Felici,G
AU  - Ferro-Luzzi,M
AU  - Filippov,K
AU  - Fini,RA
AU  - Fonte,P
AU  - Franco,C
AU  - Fraser,M
AU  - Fresa,R
AU  - Froeschl,R
AU  - Fukuda,T
AU  - Galati,G
AU  - Gall,J
AU  - Gatignon,L
AU  - Gavrilov,G
AU  - Gentile,V
AU  - Gerlach,S
AU  - Goddard,B
AU  - Golinka-Bezshyyko,L
AU  - Golovatiuk,A
AU  - Golubkov,D
AU  - Golutvin,A
AU  - Gorbounov,P
AU  - Gorbunov,D
AU  - Gorbunov,S
AU  - Gorkavenko,V
AU  - Gornushkin,Y
AU  - Gorshenkov,M
AU  - Grachev,V
AU  - Grandchamp,AL
AU  - Granich,G
AU  - Graverini,E
AU  - Grenard,J-L
AU  - Grenier,D
AU  - Grichine,V
AU  - Gruzinskii,N
AU  - Guler,AM
AU  - Guz,Y
AU  - Haefeli,GJ
AU  - Hagner,C
AU  - Hakobyan,H
AU  - Harris,IW
AU  - van,Herwijnen E
AU  - Hessler,C
AU  - Hollnagel,A
AU  - Hosseini,B
AU  - Hushchyn,M
AU  - Iaselli,G
AU  - Iuliano,A
AU  - Ivantchenko,V
AU  - Jacobsson,R
AU  - Jokovic,D
AU  - Jonker,M
AU  - Kadenko,I
AU  - Kain,V
AU  - Kaiser,B
AU  - Kamiscioglu,C
AU  - Kershaw,K
AU  - Khabibullin,M
AU  - Khalikov,E
AU  - Khaustov,G
AU  - Khoriauli,G
AU  - Khotyantsev,A
AU  - Kim,SH
AU  - Kim,YG
AU  - Kim,V
AU  - Kitagawa,N
AU  - Ko,J-W
AU  - Kodama,K
AU  - Kolesnikov,A
AU  - Kolev,D
AU  - Kolosov,V
AU  - Komatsu,M
AU  - Kondrateva,N
AU  - Kono,A
AU  - Konovalova,N
AU  - Kormannshaus,S
AU  - Korol
DO  - 11/P11028
EP  - 19
PY  - 2019///
SN  - 1748-0221
SP  - 1
TI  - Fast simulation of muons produced at the SHiP experiment using generative adversarial networks
T2  - Journal of Instrumentation
UR  - http://dx.doi.org/10.1088/1748-0221/14/11/P11028
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000507589800028&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://iopscience.iop.org/article/10.1088/1748-0221/14/11/P11028
UR  - http://hdl.handle.net/10044/1/79880
VL  - 14
ER  -

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