de Salas, P. F., & Pastor, S. (2016). Relic neutrino decoupling with flavour oscillations revisited. J. Cosmol. Astropart. Phys., 07(7), 051–18pp.
Abstract: We study the decoupling process of neutrinos in the early universe in the presence of three-flavour oscillations. The evolution of the neutrino spectra is found by solving the corresponding momentum-dependent kinetic equations for the neutrino density matrix, including for the first time the proper collision integrals for both diagonal and off-diagonal elements. This improved calculation modifies the evolution of the off-diagonal elements of the neutrino density matrix and changes the deviation from equilibrium of the frozen neutrino spectra. However, it does not vary the contribution of neutrinos to the cosmological energy density in the form of radiation, usually expressed in terms of the effective number of neutrinos, N-eff. We find a value of N-eff = 3.045, in agreement with previous theoretical calculations and consistent with the latest analysis of Planck data. This result does not depend on the ordering of neutrino masses. We also consider the effect of non-standard neutrino-electron interactions (NSI), predicted in many theoretical models where neutrinos acquire mass. For two sets of NSI parameters allowed by present data, we find that Neff can be reduced down to 3.040 or enhanced up to 3.059.
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Aristizabal Sierra, D., Tortola, M., Valle, J. W. F., & Vicente, A. (2014). Leptogenesis with a dynamical seesaw scale. J. Cosmol. Astropart. Phys., 07(7), 052–20pp.
Abstract: In the simplest type-I seesaw leptogenesis scenario right-handed neutrino annihilation processes are absent. However, in the presence of new interactions these processes are possible and can affect the resulting B – L asymmetry in an important way. A prominent example is provided by models with spontaneous lepton number violation, where the existence of new dynamical degrees of freedom can play a crucial role. In this context, we provide a model-independent discussion of the effects of right-handed neutrino annihilations. We show that in the weak washout regime, as long as the scattering processes remain slow compared with the Hubble expansion rate throughout the relevant temperature range, the efficiency can be largely enhanced, reaching in some cases maximal values. Moreover, the B – L asymmetry yield turns out to be independent upon initial conditions, in contrast to the “standard” case. On the other hand, when the annihilation processes are fast, the right-handed neutrino distribution tends to a thermal one down to low temperatures, implying a drastic suppression of the efficiency which in some cases can render the B – L generation mechanism inoperative.
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ANTARES Collaboration(Adrian-Martinez, S. et al), Bigongiari, C., Dornic, D., Emanuele, U., Gomez-Gonzalez, J. P., Hernandez-Rey, J. J., et al. (2012). Search for Cosmic Neutrino Point Sources with Four Years of Data from the Antares Telescope. Astrophys. J., 760(1), 53–10pp.
Abstract: In this paper, a time-integrated search for point sources of cosmic neutrinos is presented using the data collected from 2007 to 2010 by the ANTARES neutrino telescope. No statistically significant signal has been found and upper limits on the neutrino flux have been obtained. Assuming an E-nu(-2). spectrum, these flux limits are at 1-10x10(-8) GeV cm(-2) s(-1) for declinations ranging from -90 degrees to 40 degrees. Limits for specific models of RX J1713.7-3946 and Vela X, which include information on the source morphology and spectrum, are also given.
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Lineros, R. A., & Pereira dos Santos, F. A. (2014). Inert scalar dark matter in an extra dimension inspired model. J. Cosmol. Astropart. Phys., 10(10), 059–17pp.
Abstract: In this paper we analyze a dark matter model inspired by theories with extra dimensions. The dark matter candidate corresponds to the first Kaluza-Klein mode of an real scalar added to the Standard Model. The tower of new particles enriches the calculation of the relic abundance. For large mass splitting, the model converges to the predictions of the inert singlet dark matter model. For nearly degenerate mass spectrum, coannihilations increase the cross-sections used for direct and indirect dark matter searches. Moreover, the Kaluza-Klein zero mode can mix with the SM higgs and further constraints can be applied.
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Panes, B., Eckner, C., Hendriks, L., Caron, S., Dijkstra, K., Johannesson, G., et al. (2021). Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge. Astron. Astrophys., 656, A62–18pp.
Abstract: Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.
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