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Amerio, A., Calore, F., Serpico, P. D., & Zaldivar, B. (2024). Deepening gamma-ray point-source catalogues with sub-threshold information. J. Cosmol. Astropart. Phys., 03(3), 055–18pp.
Abstract: We propose a novel statistical method to extend Fermi-LAT catalogues of highlatitude -y-ray sources below their nominal threshold. To do so, we rely on the determination of the differential source -count distribution of sub -threshold sources which only provides the statistical flux distribution of faint sources. By simulating ensembles of synthetic skies, we assess quantitatively the likelihood for pixels in the sky with relatively low -test statistics to be due to sources, therefore complementing the source -count distribution with spatial information. Besides being useful to orient efforts towards multi -messenger and multi -wavelength identification of new -y-ray sources, we expect the results to be especially advantageous for statistical applications such as cross -correlation analyses.
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Balaudo, A., Calore, F., De Romeri, V., & Donato, F. (2024). NAJADS: a self-contained framework for the direct determination of astrophysical J-factors. J. Cosmol. Astropart. Phys., 02(2), 001–33pp.
Abstract: Cosmological simulations play a pivotal role in understanding the properties of the dark matter (DM) distribution in both galactic and galaxy -cluster environments. The characterization of DM structures is crucial for informing indirect DM searches, aiming at the detection of the annihilation (or decay) products of DM particles. A fundamental quantity in these analyses is the astrophysical J -factor. In the DM phenomenology community, J -factors are typically computed through the semi -analytical modelling of the DM mass distribution, which is affected by large uncertainties. With the scope of addressing and possibly reducing these uncertainties, we present NAJADS, a self-contained framework to derive the DM J -factor directly from the raw simulations data. We show how this framework can be used to compute all -sky maps of the J -factor, automatically accounting for the complex 3D structure of the simulated halos and for the boosting of the signal due to the density fluctuations along the line of sight. After validating our code, we present a proof -of -concept application of NAJADS to a realistic halo from the IllustrisTNG suite, and exploit it to make a thorough comparison between our numerical approach and traditional semi -analytical methods. JCAP02(2024)001
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Bertone, G., Calore, F., Caron, S., Ruiz de Austri, R., Kim, J. S., Trotta, R., et al. (2016). Global analysis of the pMSSM in light of the Fermi GeV excess: prospects for the LHC Run-II and astroparticle experiments. J. Cosmol. Astropart. Phys., 04(4), 037–20pp.
Abstract: We present a new global fit of the 19-dimensional phenomenological Minimal Supersymmetric Standard Model (pMSSM-19) that complies with all the latest experimental results from dark matter indirect, direct and accelerator dark matter searches. We show that the model provides a satisfactory explanation of the excess of gamma rays from the Galactic centre observed by the Fermi Large Area Telescope, assuming that it is produced by the annihilation of neutralinos in the Milky Way halo. We identify two regions that pass all the constraints: the first corresponds to neutralinos with a mass similar to 80 – 100 GeV annihilating into WW with a branching ratio of 95%; the second to heavier neutralinos, with mass similar to 180 – 200 GeV annihilating into (l) over barl with a branching ratio of 87%. We show that neutralinos compatible with the Galactic centre GeV excess will soon be within the reach of LHC run-II – notably through searches for charginos and neutralinos, squarks and light smuons – and of Xenon1T, thanks to its unprecedented sensitivity to spin-dependent cross-section off neutrons.
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Calore, F., De Romeri, V., & Donato, F. (2012). Conservative upper limits on WIMP annihilation cross section from Fermi-LAT gamma rays. Phys. Rev. D, 85(2), 023004–9pp.
Abstract: The spectrum of an isotropic extragalactic gamma-ray background (EGB) has been measured by the Fermi-LAT telescope at high latitudes. Two new models for the EGB are derived from the subtraction of unresolved point sources and extragalactic diffuse processes, which could explain from 30% to 70% of the Fermi-LAT EGB. Within the hypothesis that the two residual EGBs are entirely due to the annihilation of dark matter (DM) particles in the Galactic halo, we obtain stringent upper limits on their annihilation cross section. Severe bounds on a possible Sommerfeld enhancement of the annihilation cross section are set as well. Finally, we consider models for DM annihilation depending on the inverse of the velocity and associate the EGBs to photons arising from the annihilation of DM in primordial halos. Given our choices for the EGB and the minimal DM modeling, the derived upper bounds are claimed to be conservative.
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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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