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| 4. |
- Aad, G., et al.
(författare)
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- 2010
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swepub:Mat__t
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| 5. |
- Aad, G., et al.
(författare)
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- 2010
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swepub:Mat__t
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| 6. |
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| 7. |
- Armesto, N., et al.
(författare)
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Heavy-ion collisions at the LHC-Last call for predictions
- 2008
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Ingår i: Journal of Physics G. - : IOP Publishing. - 0954-3899 .- 1361-6471. ; 35:5, s. 054001-
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Forskningsöversikt (refereegranskat)abstract
- This writeup is a compilation of the predictions for the forthcoming Heavy Ion Program at the Large Hadron Collider, as presented at the CERN Theory Institute 'Heavy Ion Collisions at the LHC - Last Call for Predictions', held from 14th May to 10th June 2007.
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| 8. |
- Ahdida, C., et al.
(författare)
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Fast simulation of muons produced at the SHiP experiment using Generative Adversarial Networks
- 2019
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Ingår i: Journal of Instrumentation. - : IOP PUBLISHING LTD. - 1748-0221 .- 1748-0221. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 9. |
- Ahdida, C., et al.
(författare)
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Sensitivity of the SHiP experiment to dark photons decaying to a pair of charged particles
- 2021
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Ingår i: European Physical Journal C. - : Springer Nature. - 1434-6044 .- 1434-6052. ; 81:5
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Tidskriftsartikel (refereegranskat)abstract
- Dark photons are hypothetical massive vector particles that could mix with ordinary photons. The simplest theoretical model is fully characterised by only two parameters: the mass of the dark photon m(gamma)D and its mixing parameter with the photon, epsilon. The sensitivity of the SHiP detector is reviewed for dark photons in the mass range between 0.002 and 10 GeV. Different productionmechanisms are simulated, with the dark photons decaying to pairs of visible fermions, including both leptons and quarks. Exclusion contours are presented and compared with those of past experiments. The SHiP detector is expected to have a unique sensitivity for m. D ranging between 0.8 and 3.3(-0.5)(+0.2) GeV, and epsilon(2) ranging between 10(-11) and 10(-17).
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| 10. |
- Ahdida, C., et al.
(författare)
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Sensitivity of the SHiP experiment to Heavy Neutral Leptons
- 2019
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Ingår i: Journal of High Energy Physics (JHEP). - 1126-6708 .- 1029-8479. ; :4
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Tidskriftsartikel (refereegranskat)abstract
- Heavy Neutral Leptons (HNLs) are hypothetical particles predicted by many extensions of the Standard Model. These particles can, among other things, explain the origin of neutrino masses, generate the observed matter-antimatter asymmetry in the Universe and provide a dark matter candidate. The SHiP experiment will be able to search for HNLs produced in decays of heavy mesons and travelling distances ranging between O(50 m) and tens of kilometers before decaying. We present the sensitivity of the SHiP experiment to a number of HNL's benchmark models and provide a way to calculate the SHiP's sensitivity to HNLs for arbitrary patterns of flavour mixings. The corresponding tools and data files are also made publicly available.
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