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de Salas, P. F., Gariazzo, S., Lesgourgues, J., & Pastor, S. (2017). Calculation of the local density of relic neutrinos. J. Cosmol. Astropart. Phys., 09(9), 034–24pp.
Abstract: Nonzero neutrino masses are required by the existence of flavour oscillations, with values of the order of at least 50 meV. We consider the gravitational clustering of relic neutrinos within the Milky Way, and used the N – one-body simulation technique to compute their density enhancement factor in the neighbourhood of the Earth with respect to the average cosmic density. Compared to previous similar studies, we pushed the simulation down to smaller neutrino masses, and included an improved treatment of the baryonic and dark matter distributions in the Milky Way. Our results are important for future experiments aiming at detecting the cosmic neutrino background, such as the Princeton Tritium Observatory for Light, Early-universe, Massive-neutrino Yield (PTOLEMY) proposal. We calculate the impact of neutrino clustering in the Milky Way on the expected event rate for a PTOLEMY-like experiment. We find that the effect of clustering remains negligible for the minimal normal hierarchy scenario, while it enhances the event rate by 10 to 20% (resp. a factor 1.7 to 2.5) for the minimal inverted hierarchy scenario (resp. a degenerate scenario with 150 meV masses). Finally we compute the impact on the event rate of a possible fourth sterile neutrino with a mass of 1.3 eV.
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De Romeri, V., Martinez-Mirave, P., & Tortola, M. (2021). Signatures of primordial black hole dark matter at DUNE and THEIA. J. Cosmol. Astropart. Phys., 10(10), 051–21pp.
Abstract: Primordial black holes (PBHs) are a potential dark matter candidate whose masses can span over many orders of magnitude. If they have masses in the 10(15)-10(17) g range, they can emit sizeable fluxes of MeV neutrinos through evaporation via Hawking radiation. We explore the possibility of detecting light (non-)rotating PBHs with future neutrino experiments. We focus on two next generation facilities: the Deep Underground Neutrino Experiment (DUNE) and THEIA. We simulate the expected event spectra at both experiments assuming different PBH mass distributions and spins, and we extract the expected 95% C.L. sensitivities to these scenarios. Our analysis shows that future neutrino experiments like DUNE and THEIA will be able to set competitive constraints on PBH dark matter, thus providing complementary probes in a part of the PBH parameter space currently constrained mainly by photon data.
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De Romeri, V., Majumdar, A., Papoulias, D. K., & Srivastava, R. (2024). XENONnT and LUX-ZEPLIN constraints on DSNB-boosted dark matter. J. Cosmol. Astropart. Phys., 03(3), 028–34pp.
Abstract: We consider a scenario in which dark matter particles are accelerated to semirelativistic velocities through their scattering with the Diffuse Supernova Neutrino Background. Such a subdominant, but more energetic dark matter component can be then detected via its scattering on the electrons and nucleons inside direct detection experiments. This opens up the possibility to probe the sub -GeV mass range, a region of parameter space that is usually not accessible at such facilities. We analyze current data from the XENONnT and LUX-ZEPLIN experiments and we obtain novel constraints on the scattering cross sections of sub -GeV boosted dark matter with both nucleons and electrons. We also highlight the importance of carefully taking into account Earth's attenuation effects as well as the finite nuclear size into the analysis. By comparing our results to other existing constraints, we show that these effects lead to improved and more robust constraints.
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de Putter, R., Wagner, C., Mena, O., Verde, L., & Percival, W. J. (2012). Thinking outside the box: effects of modes larger than the survey on matter power spectrum covariance. J. Cosmol. Astropart. Phys., 04(4), 019–31pp.
Abstract: Accurate power spectrum (or correlation function) covariance matrices are a crucial requirement for cosmological parameter estimation from large scale structure surveys. In order to minimize reliance on computationally expensive mock catalogs, it is important to have a solid analytic understanding of the different components that make up a covariance matrix. Considering the matter power spectrum covariance matrix, it has recently been found that there is a potentially dominant effect on mildly non-linear scales due to power in modes of size equal to and larger than the survey volume. This beat coupling effect has been derived analytically in perturbation theory and while it has been tested with simulations, some questions remain unanswered. Moreover, there is an additional effect of these large modes, which has so far not been included in analytic studies, namely the effect on the estimated average density which enters the power spectrum estimate. In this article, we work out analytic, perturbation theory based expressions including both the beat coupling and this local average effect and we show that while, when isolated, beat coupling indeed causes large excess covariance in agreement with the literature, in a realistic scenario this is compensated almost entirely by the local average effect, leaving only similar to 10% of the excess. We test our analytic expressions by comparison to a suite of large N-body simulations, using both full simulation boxes and subboxes thereof to study cases without beat coupling, with beat coupling and with both beat coupling and the local average effect. For the variances, we find excellent agreement with the analytic expressions for k < 0.2 hMpc(-1) at z = 0.5, while the correlation coefficients agree to beyond k = 0.4 hMpc(-1). As expected, the range of agreement increases towards higher redshift and decreases slightly towards z = 0. We finish by including the large-mode effects in a full covariance matrix description for arbitrary survey geometry and confirming its validity using simulations. This may be useful as a stepping stone towards building an actual galaxy (or other tracer's) power spectrum covariance matrix.
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de los Rios, M., Petac, M., Zaldivar, B., Bonaventura, N. R., Calore, F., & Iocco, F. (2023). Determining the dark matter distribution in simulated galaxies with deep learning. Mon. Not. Roy. Astron. Soc., 525(4), 6015–6035.
Abstract: We present a novel method of inferring the dark matter (DM) content and spatial distribution within galaxies, using convolutional neural networks (CNNs) trained within state-of-the-art hydrodynamical simulations (Illustris-TNG100). Within the controlled environment of the simulation, the framework we have developed is capable of inferring the DM mass distribution within galaxies of mass similar to 10(11)-10(13)M(circle dot) from the gravitationally baryon-dominated internal regions to the DM-rich, baryon-depleted outskirts of the galaxies, with a mean absolute error always below approximate to 0.25 when using photometrical and spectroscopic information. With respect to traditional methods, the one presented here also possesses the advantages of not relying on a pre-assigned shape for the DM distribution, to be applicable to galaxies not necessarily in isolation, and to perform very well even in the absence of spectroscopic observations.
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