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Blennow, M., Fernandez-Martinez, E., Hernandez-Garcia, J., Lopez-Pavon, J., Marcano, X., & Naredo-Tuero, D. (2023). Bounds on lepton non-unitarity and heavy neutrino mixing. J. High Energy Phys., 08(8), 030–41pp.
Abstract: We present an updated and improved global fit analysis of current flavour and electroweak precision observables to derive bounds on unitarity deviations of the leptonic mixing matrix and on the mixing of heavy neutrinos with the active flavours. This new analysis is motivated by new and updated experimental results on key observables such as V-ud, the invisible decay width of the Z boson and the W boson mass. It also improves upon previous studies by considering the full correlations among the different observables and explicitly calibrating the test statistic, which may present significant deviations from a & chi;(2) distribution. The results are provided for three different Type-I seesaw scenarios: the minimal scenario with only two additional right-handed neutrinos, the next to minimal one with three extra neutrinos, and the most general one with an arbitrary number of heavy neutrinos that we parametrise via a generic deviation from a unitary leptonic mixing matrix. Additionally, we also analyze the case of generic deviations from unitarity of the leptonic mixing matrix, not necessarily induced by the presence of additional neutrinos. This last case relaxes some correlations among the parameters and is able to provide a better fit to the data. Nevertheless, inducing only leptonic unitarity deviations avoiding both the correlations implied by the right-handed neutrino extension as well as more strongly constrained operators is challenging and would imply significantly more complex UV completions.
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Arganda, E., Marcano, X., Martin Lozano, V., Medina, A. D., Perez, A. D., Szewc, M., et al. (2022). A method for approximating optimal statistical significances with machine-learned likelihoods. Eur. Phys. J. C, 82(11), 993–14pp.
Abstract: Machine-learning techniques have become fundamental in high-energy physics and, for new physics searches, it is crucial to know their performance in terms of experimental sensitivity, understood as the statistical significance of the signal-plus-background hypothesis over the background-only one. We present here a simple method that combines the power of current machine-learning techniques to face high-dimensional data with the likelihood-based inference tests used in traditional analyses, which allows us to estimate the sensitivity for both discovery and exclusion limits through a single parameter of interest, the signal strength. Based on supervised learning techniques, it can perform well also with high-dimensional data, when traditional techniques cannot. We apply the method to a toy model first, so we can explore its potential, and then to a LHC study of new physics particles in dijet final states. Considering as the optimal statistical significance the one we would obtain if the true generative functions were known, we show that our method provides a better approximation than the usual naive counting experimental results.
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Abada, A., Escribano, P., Marcano, X., & Piazza, G. (2022). Collider searches for heavy neutral leptons: beyond simplified scenarios. Eur. Phys. J. C, 82(11), 1030–17pp.
Abstract: With very few exceptions, the large amount of available experimental bounds on heavy neutral leptons – HNL – have been derived relying on the assumption of the existence of a single (usually Majorana) sterile fermion state that mixes with only one lepton flavour. However, most of the extensions of the Standard Model involving sterile fermions predict the existence of several HNLs, with complex mixing patterns to all flavours. Consequently, most of the experimental bounds for HNLs need to be recast before being applied to a generic scenario. In this work, we focus on LHC searches of heavy neutral leptons and discuss how to reinterpret the available bounds when it comes to consider mixings to all active flavours, not only in the case with a single HNL, but also in the case when more heavy neutral leptons are involved. In the latter case, we also consider the possibility of interference effects and show how the bounds on the parameter space should be recast.
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