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Author Herrero-Garcia, J.; Patrick, R.; Scaffidi, A. url  doi
openurl 
  Title A semi-supervised approach to dark matter searches in direct detection data with machine learning Type Journal Article
  Year 2022 Publication Journal of Cosmology and Astroparticle Physics Abbreviated Journal J. Cosmol. Astropart. Phys.  
  Volume 02 Issue Pages 039 - 19pp  
  Keywords  
  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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  Notes Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5495  
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Author Herrero-Garcia, J.; Landini, G.; Vatsyayan, D. url  doi
openurl 
  Title Asymmetries in extended dark sectors: a cogenesis scenario Type Journal Article
  Year 2023 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 05 Issue 5 Pages 049 - 41pp  
  Keywords Models for Dark Matter; Particle Nature of Dark Matter  
  Abstract The observed dark matter relic abundance may be explained by different mechanisms, such as thermal freeze-out/freeze-in, with one or more symmetric/asymmetric components. In this work we investigate the role played by asymmetries in determining the yield and nature of dark matter in non-minimal scenarios with more than one dark matter particle. In particular, we show that the energy density of a particle may come from an asymmetry, even if the particle is asymptotically symmetric by nature. To illustrate the different effects of asymmetries, we adopt a model with two dark matter components. We embed it in a multi-component cogenesis scenario that is also able to reproduce neutrino masses and the baryon asymmetry. In some cases, the model predicts an interesting monochromatic neutrino line that may be searched for at neutrino telescopes.  
  Address [Herrero-Garcia, Juan] Univ Valencia, Dept Fis Teor, C Catedrat Jose Beltran 2, E-46980 Paterna, Spain, Email: juan.herrero@ific.uv.es;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue (up) Edition  
  ISSN 1029-8479 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000988319500002 Approved no  
  Is ISI yes International Collaboration no  
  Call Number IFIC @ pastor @ Serial 5550  
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