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Fileviez Perez, P., Murgui, C., & Plascencia, A. D. (2019). The QCD axion and unification. J. High Energy Phys., 11(11), 093–21pp.
Abstract: The QCD axion is one of the most appealing candidates for the dark matter in the Universe. In this article, we discuss the possibility to predict the axion mass in the context of a simple renormalizable grand unified theory where the Peccei-Quinn scale is determined by the unification scale. In this framework, the axion mass is predicted to be in the range ma, <^> (3-13) x 10-9 eV. We study the axion phenomenology and find that the ABRACADABRA and CASPEr-Electric experiments will be able to fully probe this mass window.
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Abdullahi, A. M. et al, & Lopez-Pavon, J. (2023). The present and future status of heavy neutral leptons. J. Phys. G, 50(2), 020501–100pp.
Abstract: The existence of nonzero neutrino masses points to the likely existence of multiple Standard Model neutral fermions. When such states are heavy enough that they cannot be produced in oscillations, they are referred to as heavy neutral leptons (HNLs). In this white paper, we discuss the present experimental status of HNLs including colliders, beta decay, accelerators, as well as astrophysical and cosmological impacts. We discuss the importance of continuing to search for HNLs, and its potential impact on our understanding of key fundamental questions, and additionally we outline the future prospects for next-generation future experiments or upcoming accelerator run scenarios.
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MoEDAL Collaboration(Acharya, B. et al), Bernabeu, J., Garcia, C., King, M., Mitsou, V. A., Vento, V., et al. (2014). The physics programme of the MoEDAL experiment at the LHC. Int. J. Mod. Phys. A, 29(23), 1430050–91pp.
Abstract: The MoEDAL experiment at Point 8 of the LHC ring is the seventh and newest LHC experiment. It is dedicated to the search for highly-ionizing particle avatars of physics beyond the Standard Model, extending significantly the discovery horizon of the LHC. A MoEDAL discovery would have revolutionary implications for our fundamental understanding of the Microcosm. MoEDAL is an unconventional and largely passive LHC detector comprised of the largest array of Nuclear Track Detector stacks ever deployed at an accelerator, surrounding the intersection region at Point 8 on the LHC ring. Another novel feature is the use of paramagnetic trapping volumes to capture both electrically and magnetically charged highly-ionizing particles predicted in new physics scenarios. It includes an array of TimePix pixel devices for monitoring highly-ionizing particle backgrounds. The main passive elements of the MoEDAL detector do not require a trigger system, electronic readout, or online computerized data acquisition. The aim of this paper is to give an overview of the MoEDAL physics reach, which is largely complementary to the programs of the large multipurpose LHC detectors ATLAS and CMS.
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Donini, A., Hernandez, P., Lopez-Pavon, J., Maltoni, M., & Schwetz, T. (2012). The minimal 3+2 neutrino model versus oscillation anomalies. J. High Energy Phys., 07(7), 161–20pp.
Abstract: We study the constraints imposed by neutrino oscillation experiments on the minimal extension of the Standard Model that can explain neutrino masses, which requires the addition of just two singlet Weyl fermions. The most general renormalizable couplings of this model imply generically four massive neutrino mass eigenstates while one remains massless: it is therefore a minimal 3+2 model. The possibility to account for the confirmed solar, atmospheric and long-baseline oscillations, together with the LSND/MiniBooNE and reactor anomalies is addressed. We find that the minimal model can fit oscillation data including the anomalies better than the standard 3 nu model and similarly to the 3 + 2 phenomenological models, even though the number of free parameters is much smaller than in the latter. Accounting for the anomalies in the minimal model favours a normal hierarchy of the light states and requires a large reactor angle, in agreement with recent measurements. Our analysis of the model employs a new parametrization of seesaw models that extends the Casas-Ibarra one to regimes where higher order corrections in the light-heavy mixings are significant.
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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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