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Bas i Beneito, A., Herrero-Garcia, J., & Vatsyayan, D. (2022). Multi-component dark sectors: symmetries, asymmetries and conversions. J. High Energy Phys., 10(10), 075–31pp.
Abstract: We study the relic abundance of several stable particles from a generic dark sector, including the possible presence of dark asymmetries. After discussing the different possibilities for stabilising multi-component dark matter, we analyse the final relic abundance of the symmetric and asymmetric dark matter components, paying special attention to the role of the unavoidable conversions between dark matter states. We find an exponential dependence of the asymmetries of the heavier components on annihilations and conversions. We conclude that having similar symmetric and asymmetric components is a natural outcome in many scenarios of multi-component dark matter. This has novel phenomenological implications, which we briefly discuss.
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Aparici, A., Herrero-Garcia, J., Rius, N., & Santamaria, A. (2012). On the nature of the fourth generation neutrino and its implications. J. High Energy Phys., 07(7), 030–31pp.
Abstract: We consider the neutrino sector of a Standard Model with four generations. While the three light neutrinos can obtain their masses from a variety of mechanisms with or without new neutral fermions, fourth-generation neutrinos need at least one new relatively light right-handed neutrino. If lepton number is not conserved this neutrino must have a Majorana mass term whose size depends on the underlying mechanism for lepton number violation. Majorana masses for the fourth-generation neutrinos induce relative large two-loop contributions to the light neutrino masses which could be even larger than the cosmological bounds. This sets strong limits on the mass parameters and mixings of the fourth-generation neutrinos.
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Aparici, A., Herrero-Garcia, J., Rius, N., & Santamaria, A. (2011). Neutrino masses from new generations. J. High Energy Phys., 07(7), 122.
Abstract: We reconsider the possibility that Majorana masses for the three known neutrinos are generated radiatively by the presence of a fourth generation and one right-handed neutrino with Yukawa couplings and a Majorana mass term. We find that the observed light neutrino mass hierarchy is not compatible with low energy universality bounds in this minimal scenario, but all present data can be accommodated with five generations and two right-handed neutrinos. Within this framework, we explore the parameter space regions which are currently allowed and could lead to observable effects in neutrinoless double beta decay, mu-e conversion in nuclei and μ-> e gamma experiments. We also discuss the detection prospects at LHC.
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Herrero-Garcia, J., Patrick, R., & Scaffidi, A. (2022). A semi-supervised approach to dark matter searches in direct detection data with machine learning. J. Cosmol. Astropart. Phys., 02, 039–19pp.
Abstract: The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general philosophy more concrete by applying modern machine learning techniques to dark matter direct detection. We do this by encoding and decoding the graphical representation of background events in the XENONnT experiment with a convolutional variational autoencoder. We describe a methodology that utilizes the `anomaly score' derived from the reconstruction loss of the convolutional variational autoencoder as well as a pre-trained standard convolutional neural network, in a semi-supervised fashion. Indeed, we observe that optimum results are obtained only when both unsupervised and supervised anomaly scores are considered together. A data set that has a higher proportion of anomaly score is deemed anomalous and deserves further investigation. Contrary to classical analyses, in principle all information about the events is used, preventing unnecessary information loss. Lastly, we demonstrate the reach of learning-focused anomaly detection in this context by comparing results with classical inference, observing that, if tuned properly, these techniques have the potential to outperform likelihood-based methods.
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