Arguelles, C. A., Palomares-Ruiz, S., Schneider, A., Wille, L., & Yuan, T. L. (2018). Unified atmospheric neutrino passing fractions for large-scale neutrino telescopes. J. Cosmol. Astropart. Phys., 07(7), 047–41pp.
Abstract: The atmospheric neutrino passing fraction, or self-veto, is defined as the probability for an atmospheric neutrino not to be accompanied by a detectable muon from the same cosmic-ray air shower. Building upon previous work, we propose a redefinition of the passing fractions by unifying the treatment for muon and electron neutrinos. Several approximations have also been removed. This enables performing detailed estimations of the uncertainties in the passing fractions from several inputs: muon losses, cosmic-ray spectrum, hadronic-interaction models and atmosphere-density profiles. We also study the passing fractions under variations of the detector configuration: depth, surrounding medium and muon veto trigger probability. The calculation exhibits excellent agreement with passing fractions obtained from Monte Carlo simulations. Finally, we provide a general software framework to implement this veto technique for all large-scale neutrino observatories.
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Mangano, G., Miele, G., Pastor, S., Pisanti, O., & Sarikas, S. (2011). Constraining the cosmic radiation density due to lepton number with Big Bang Nucleosynthesis. J. Cosmol. Astropart. Phys., 03(3), 035–18pp.
Abstract: The cosmic energy density in the form of radiation before and during Big Bang Nucleosynthesis (BBN) is typically parameterized in terms of the effective number of neutrinos N-eff. This quantity, in case of no extra degrees of freedom, depends upon the chemical potential and the temperature characterizing the three active neutrino distributions, as well as by their possible non-thermal features. In the present analysis we determine the upper bounds that BBN places on N-eff from primordial neutrino-antineutrino asymmetries, with a careful treatment of the dynamics of neutrino oscillations. We consider quite a wide range for the total lepton number in the neutrino sector, eta(nu) = eta(nu e) + eta(nu mu) + eta(nu tau) and the initial electron neutrino asymmetry eta(in)(nu e), solving the corresponding kinetic equations which rule the dynamics of neutrino (antineutrino) distributions in phase space due to collisions, pair processes and flavor oscillations. New bounds on both the total lepton number in the neutrino sector and the nu(e)-(nu) over bar (e) asymmetry at the onset of BBN are obtained fully exploiting the time evolution of neutrino distributions, as well as the most recent determinations of primordial H-2/H density ratio and He-4 mass fraction. Note that taking the baryon fraction as measured by WMAP, the H-2/H abundance plays a relevant role in constraining the allowed regions in the eta(nu)-eta(in)(nu e) plane. These bounds fix the maximum contribution of neutrinos with primordial asymmetries to N-eff as a function of the mixing parameter theta(13), and point out the upper bound N-eff less than or similar to 3.4. Comparing these results with the forthcoming measurement of N-eff by the Planck satellite will likely provide insight on the nature of the radiation content of the universe.
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Caputo, A., Regis, M., & Taoso, M. (2020). Searching for sterile neutrino with X-ray intensity mapping. J. Cosmol. Astropart. Phys., 03(3), 001–21pp.
Abstract: The cosmological X-ray emission associated to the possible radiative decay of sterile neutrinos is composed by a collection of lines at different energies. For a given mass, each line corresponds to a given redshift. In this work, we cross correlate such line emission with catalogs of galaxies tracing the dark matter distribution at different redshifts. We derive observational prospects by correlating the X-ray sky that will be probed by the eROSITA and Athena missions with current and near future photometric and spectroscopic galaxy surveys. A relevant and unexplored fraction of the parameter space of sterile neutrinos can be probed by this technique.
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Di Valentino, E. et al, & Mena, O. (2021). Snowmass2021-Letter of interest cosmology intertwined II: The hubble constant tension. Astropart Phys., 131, 102605–8pp.
Abstract: The current cosmological probes have provided a fantastic confirmation of the standard A Cold Dark Matter cosmological model, which has been constrained with unprecedented accuracy. However, with the increase of the experimental sensitivity, a few statistically significant tensions between different independent cosmological datasets emerged. While these tensions can be in part the result of systematic errors, the persistence after several years of accurate analysis strongly hints at cracks in the standard cosmological scenario and the need for new physics. In this Letter of Interest we will focus on the 4.4 sigma – tension between the Planck estimate of the Hubble constant H-0 and the SH0ES collaboration measurements. After showing the H-0 evaluations made from different teams using different methods and geometric calibrations, we will list a few interesting models of new physics that could solve this tension and discuss how the next decade's experiments will be crucial.
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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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