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Sanchis-Lozano, M. A., & Sarkisyan-Grinbaum, E. K. (2018). Searching for new physics with three-particle correlations in pp collisions at the LHC. Phys. Lett. B, 781, 505–509.
Abstract: New phenomena involving pseudorapidity and azimuthal correlations among final-state particles in pp collisions at the LHC can hint at the existence of hidden sectors beyond the Standard Model. In this paper we rely on a correlated-cluster picture of multiparticle production, which was shown to account for the ridge effect, to assess the effect of a hidden sector on three-particle correlations concluding that there is a potential signature of new physics that can be directly tested by experiments using well-known techniques.
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Alekhin, S. et al, & Hernandez, P. (2016). A facility to search for hidden particles at the CERN SPS: the SHiP physics case. Rep. Prog. Phys., 79(12), 124201–137pp.
Abstract: This paper describes the physics case for a new fixed target facility at CERN SPS. The SHiP (search for hidden particles) experiment is intended to hunt for new physics in the largely unexplored domain of very weakly interacting particles with masses below the Fermi scale, inaccessible to the LHC experiments, and to study tau neutrino physics. The same proton beam setup can be used later to look for decays of tau-leptons with lepton flavour number non-conservation, tau -> 3 μand to search for weakly-interacting sub-GeV dark matter candidates. We discuss the evidence for physics beyond the standard model and describe interactions between new particles and four different portals-scalars, vectors, fermions or axion-like particles. We discuss motivations for different models, manifesting themselves via these interactions, and how they can be probed with the SHiP experiment and present several case studies. The prospects to search for relatively light SUSY and composite particles at SHiP are also discussed. We demonstrate that the SHiP experiment has a unique potential to discover new physics and can directly probe a number of solutions of beyond the standard model puzzles, such as neutrino masses, baryon asymmetry of the Universe, dark matter, and inflation.
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Kasieczka, G. et al, & Sanz, V. (2021). The LHC Olympics 2020: a community challenge for anomaly detection in high energy physics. Rep. Prog. Phys., 84(12), 124201–64pp.
Abstract: A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.
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