Abstract: We investigate the possibility that right-handed (RH) sneutrinos and gravitinos can coexist and explain the dark matter (DM) problem. We compare extensions of the minimal supersymmetric standard model (MSSM) and the next-to-MSSM (NMSSM) adding RH neutrinos superfields, with special emphasis on the latter. If the gravitino is the lightest supersymmetric particle (LSP) and the RH sneutrino the next-to-LSP (NLSP), the heavier particle decays to the former plus left-handed (LH) neutrinos through the mixing between the scalar partners of the LH and RH neutrinos. However, the interaction is suppressed by the Planck mass, and if the LH-RH sneutrino mixing parameter is small, << O(10-2), a long-lived RH sneutrino NLSP is possible even surpassing the age of the Universe. As a byproduct, the NLSP to LSP decay produces monochromatic neutrinos in the ballpark of current and planned neutrino telescopes like Super-Kamiokande, IceCube and Antares that we use to set constraints and show prospects of detection. In the NMSSM+RHN, assuming a gluino mass parameter M3 = 3 TeV we found the following lower limits for the gravitino mass m3/2 >= 1-600 GeV and the reheating temperature TR >= 105-3 x 107 GeV, for m nu similar to R similar to 10-800 GeV. If we take M3 = 10 TeV, then the limits on TR are relaxed by one order of magnitude.

Abstract: Dark-matter particles that annihilate or decay can undergo complex sequences of processes, including strong and electromagnetic radiation, hadronisation, and hadron de-cays, before particles that are stable on astrophysical time scales are produced. Antiprotons produced in this way may leave footprints in experiments such as AMS-02. Several groups have reported an excess of events in the antiproton flux in the rigidity range of 10-20 GV. However, the theoretical modeling of baryon production is not straightforward and relies in part on phenomenological models in Monte Carlo event generators. In this work, we assess the impact of QCD uncertainties on the spectra of antiprotons from dark-matter annihila-tion. As a proof-of-principle, we show that for a two-parameter model that depends only on the thermally-averaged annihilation cross section ((o -v)) and the dark-matter mass (Mx), QCD uncertainties can affect the best-fit mass by up to ti 14% (with large uncertainties for large DM masses), depending on the choice of Mx and the annihilation channel (bb over bar or W+W-), and (o -v) by up to ti 10%. For comparison, changes to the underlying diffusion parameters are found to be within 1%-5%, and the results are also quite resilient to the choice of cosmic-ray propagation model. These findings indicate that QCD uncertainties need to be included in future DM analyses. To facilitate full-fledged analyses, we provide the spectra in tabulated form including QCD uncertainties and code snippets to perform mass interpolations and quick DM fits. The code can be found in this GitHub [1] repository.

Abstract: Sterile neutrinos with mass in the eV-scale and large mixings of order theta(0) similar or equal to 0.1 could explain some anomalies found in short-baseline neutrino oscillation data. Here, we revisit a neutrino portal scenario in which eV-scale sterile neutrinos have self-interactions via a new gauge vector boson phi. Their production in the early Universe via mixing with active neutrinos can be suppressed by the induced effective potential in the sterile sector. We study how different cosmological observations can constrain this model, in terms of the mass of the new gauge boson, M-phi, and its coupling to sterile neutrinos, g(s). Then, we explore how to probe part of the allowed parameter space of this particular model with future observations of the diffuse supernova neutrino background by the Hyper-Kamiokande and DUNE detectors. For M-phi similar to 5 – 10 keV and g(s) similar to 10-(4) – 10(-2), as allowed by cosmological constraints, we find that interactions of diffuse supernova neutrinos with relic sterile neutrinos on their way to the Earth would result in significant dips in the neutrino spectrum which would produce unique features in the event spectra observed in these detectors.

Abstract: We consider the possibility that the Higgs can be produced in dark matter annihilations, appearing as a line in the spectrum of gamma rays at an energy determined by the masses of the WIMP and the Higgs itself. We argue that this phenomenon occurs generally in models in which the the dark sector has large couplings to the most massive states of the SM and provide a simple example inspired by the Randall-Sundrum vision of dark matter, whose 4d dual corresponds to electroweak symmetry-breaking by strong dynamics which respect global symmetries that guarantee a stable WIMP. The dark matter is a Dirac fermion that couples to a Z' acting as a portal to the Standard Model through its strong coupling to top quarks. Annihilation into light standard model degrees of freedom is suppressed and generates a feeble continuum spectrum of gamma rays. Loops of top quarks mediate annihilation into gamma Z, gamma h, and gamma Z', providing a forest of lines in the spectrum. Such models can be probed by the Fermi/GLAST satellite and ground-based Air Cherenkov telescopes.

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.