Lopez-Fogliani, D. E., Perez, A. D., & Ruiz de Austri, R. (2025). Insights into dark matter direct detection experiments: decision trees versus deep learning. J. Cosmol. Astropart. Phys., 01(1), 057–30pp.
Abstract: The detection of Dark Matter (DM) remains a significant challenge in particle physics. This study exploits advanced machine learning models to improve detection capabilities of liquid xenon time projection chamber experiments, utilizing state-of-the-art transformers alongside traditional methods like Multilayer Perceptrons and Convolutional Neural Networks. We evaluate various data representations and find that simplified feature representations, particularly corrected S1 and S2 signals as well as a few shape-related features including the time difference between signals, retain critical information for classification. Our results show that while transformers offer promising performance, simpler models like XGBoost can achieve comparable results with optimal data representations. We also derive exclusion limits in the cross-section versus DM mass parameter space, showing minimal differences between XGBoost and the best performing deep learning models. The comparative analysis of different machine learning approaches provides a valuable reference for future experiments by guiding the choice of models and data representations to maximize detection capabilities.
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ANTARES Collaboration(Albert, A. et al), Alves, S., Calvo, D., Carretero, V., Gozzini, R., Hernandez-Rey, J. J., et al. (2024). Results of the follow-up of ANTARES neutrino alerts. J. Cosmol. Astropart. Phys., 09(9), 042–33pp.
Abstract: High-energy neutrinos could be produced in the interaction of charged cosmic rays with matter or radiation surrounding astrophysical sources. To look for transient sources associated with neutrino emission, a follow-up program of neutrino alerts has been operating within the ANTARES collaboration since 2009. This program, named TAToO, has triggered robotic optical telescopes (MASTER, TAROT, ROTSE and the SVOM ground based telescopes) immediately after the detection of any relevant neutrino candidate and scheduled several observations in the weeks following the detection. A subset of ANTARES events with highest probabilities of being of cosmic origin has also been followed by the Swift and the INTEGRAL satellites, the Murchison Widefield Array radio telescope and the H.E.S.S. high-energy gamma-ray telescope. The results of twelve years of observations are reported. In September 2015, ANTARES issued a neutrino alert and during the follow-up, a potential transient counterpart was identified by Swift and MASTER. A multi-wavelength follow-up campaign has allowed to identify the nature of this source and has proven its fortuitous association with the neutrino. No other optical and X-ray counterpart has been significantly associated with an ANTARES candidate neutrino signal. Constraints on transient neutrino emission have been set. The return of experience is particularly important for the design of the alert system of KM3NeT, the next generation neutrino telescope in the Mediterranean Sea.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Bariego-Quintana, A., Calvo, D., Cecchini, V., Garcia Soto, A., et al. (2024). Search for neutrino emission from GRB 221009A using the KM3NeT ARCA and ORCA detectors. J. Cosmol. Astropart. Phys., 08(8), 006–16pp.
Abstract: Gamma-ray bursts are promising candidate sources of high-energy astrophysical neutrinos. The recent GRB 221009A event, identified as the brightest gamma-ray burst ever detected, provides a unique opportunity to investigate hadronic emissions involving neutrinos. The KM3NeT undersea neutrino detectors participated in the worldwide follow-up effort triggered by the event, searching for neutrino events. In this paper, we summarize subsequent searches, in a wide energy range from MeV up to a few PeVs. No neutrino events are found in any of the searches performed. Upper limits on the neutrino emission associated with GRB 221009A are computed.
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ANTARES Collaboration(Albert, A. et al), Alves, S., Calvo, D., Carretero, V., Gozzini, R., Hernandez-Rey, J. J., et al. (2024). Constraints on the energy spectrum of the diffuse cosmic neutrino flux from the ANTARES neutrino telescope. J. Cosmol. Astropart. Phys., 08(8), 038–27pp.
Abstract: High-significance evidences of the existence of a high-energy diffuse flux of cosmic neutrinos have emerged in the last decade from several observations by the IceCube Collaboration. The ANTARES neutrino telescope took data for 15 years in the Mediterranean Sea, from 2007 to 2022, and collected a high-purity all-flavour neutrino sample. The search for a diffuse cosmic neutrino signal using this dataset is presented in this article. This final analysis did not provide a statistically significant observation of the cosmic diffuse flux. However, this is converted into limits on the properties of the cosmic neutrino spectrum. In particular, given the sensitivity of the ANTARES neutrino telescope between 1 and 50TeV, constraints on single-power-law hypotheses are derived for the cosmic diffuse flux below 20TeV, especially for power-law fits of the IceCube data with spectral index softer than 2.8.
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Dimitriou, A., Figueroa, D. G., & Zaldivar, B. (2024). Fast likelihood-free reconstruction of gravitational wave backgrounds. J. Cosmol. Astropart. Phys., 09(9), 032–51pp.
Abstract: based) techniques for reconstructing the spectral shape of a gravitational wave background (GWB). We focus on the reconstruction of an arbitrarily shaped signal (approximated by a piecewise power-law in many frequency bins) by the LISA detector, but the method can be easily extended to either template-dependent signals, or to other detectors, as long as a characterisation of the instrumental noise is available. As proof of the technique, we quantify the ability of LISA to reconstruct signals of arbitrary spectral shape (blind reconstruction), considering a diversity of frequency profiles, and including astrophysical backgrounds in some cases. As a teaser of how the method can reconstruct signals characterised by a parameter-dependent template (template reconstruction), we present a dedicated study for power-law signals. While our technique has several advantages with respect to traditional MCMC methods, we validate it with the latter for concrete cases. This work opens the door for both fast and accurate Bayesian parameter estimation of GWBs, with essentially no computational overhead during the inference step. Our set of tools are integrated into the package GWBackFinder, which is publicly available in GitHub.
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