Ana Bárbara Rodrigues Cavalcante

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SND@LHC - Scattering and Neutrino Detector at the LHC

Aurelio Bay, Alexey Boyarsky, Nikolaos Charitonidis, Serhii Cholak, Elena Graverini, Guido Haefeli, Sun Hee Kim, Andrea Montanari, Anton Petrov, Federico Leo Redi, Ana Bárbara Rodrigues Cavalcante, Olivier Schneider, Lesya Shchutska, Evgenii Shmanin, Jean-Loup Tastet, Carina Trippl, Ettore Zaffaroni

SND@LHC is a proposed, compact and stand-alone experiment to perform measurements with neutrinos produced at the LHC in an hitherto unexplored pseudo-rapidity region of

7.2 < \eta < 8.6

, complementary to all the other experiments at the LHC. The experiment is to be located 480 m downstream of IP1 in the unused TI18 tunnel. The first phase aims at operating the detector throughout LHC Run 3 to collect a total integrated luminosity of 150 fb

^{−1}

. Following the review of the Letter of Intent [1], submitted in August 2020, LHCC recommended the collaboration to proceed with the preparation of a Technical Proposal (TP), reported herein.

CERN2021

Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks

Aurelio Bay, Alexey Boyarsky, Nikolaos Charitonidis, Hans Dijkstra, Sebastian Gerlach, Alexandre Emmanuel Grandchamp, Elena Graverini, Guido Haefeli, Sun Hee Kim, Ekaterina Kuznetsova, Anton Petrov, Federico Leo Redi, Ana Bárbara Rodrigues Cavalcante, Oleg Ruchayskiy, Lesya Shchutska, Sergei Smirnov, Maria Elena Stramaglia, Jean-Loup Tastet

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 O(10(6)). 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.

IOP PUBLISHING LTD2019

Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks

Aurelio Bay, Alexey Boyarsky, Nikolaos Charitonidis, Hans Dijkstra, Sebastian Gerlach, Elena Graverini, Guido Haefeli, Sun Hee Kim, Ekaterina Kuznetsova, Anton Petrov, Federico Leo Redi, Ana Bárbara Rodrigues Cavalcante, Oleg Ruchayskiy, Lesya Shchutska, Sergei Smirnov, Maria Elena Stramaglia, Jean-Loup Tastet, Inar Timiryasov

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

\mathcal{O}(10^6)

. 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.

2019

Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks

/c

/c

\mathcal{O}(10^6)

2019

SND@LHC - Scattering and Neutrino Detector at the LHC

SND@LHC is a proposed, compact and stand-alone experiment to perform measurements with neutrinos produced at the LHC in an hitherto unexplored pseudo-rapidity region of

7.2 < \eta < 8.6

^{−1}

. Following the review of the Letter of Intent [1], submitted in August 2020, LHCC recommended the collaboration to proceed with the preparation of a Technical Proposal (TP), reported herein.

CERN2021