|
|
Caron, S., Eckner, C., Hendriks, L., Johannesson, G., Ruiz de Austri, R., & Zaharijas, G. (2023). Mind the gap: the discrepancy between simulation and reality drives interpretations of the Galactic Center Excess. J. Cosmol. Astropart. Phys., 06(6), 013–56pp.
Abstract: The Galactic Center Excess (GCE) in GeV gamma rays has been debated for over a decade, with the possibility that it might be due to dark matter annihilation or undetected point sources such as millisecond pulsars (MSPs). This study investigates how the gamma-ray emission model (-yEM) used in Galactic center analyses affects the interpretation of the GCE's nature. To address this issue, we construct an ultra-fast and powerful inference pipeline based on convolutional Deep Ensemble Networks. We explore the two main competing hypotheses for the GCE using a set of-yEMs with increasing parametric freedom. We calculate the fractional contribution (fsrc) of a dim population of MSPs to the total luminosity of the GCE and analyze its dependence on the complexity of the ryEM. For the simplest ryEM, we obtain fsrc = 0.10 f 0.07, while the most complex model yields fsrc = 0.79 f 0.24. In conclusion, we find that the statement about the nature of the GCE (dark matter or not) strongly depends on the assumed ryEM. The quoted results for fsrc do not account for the additional uncertainty arising from the fact that the observed gamma-ray sky is out-of-distribution concerning the investigated ryEM iterations. We quantify the reality gap between our ryEMs using deep-learning-based One-Class Deep Support Vector Data Description networks, revealing that all employed ryEMs have gaps to reality. Our study casts doubt on the validity of previous conclusions regarding the GCE and dark matter, and underscores the urgent need to account for the reality gap and consider previously overlooked “out of domain” uncertainties in future interpretations.
|
|
|
|
Amerio, A., Cuoco, A., & Fornengo, N. (2023). Extracting the gamma-ray source-count distribution below the Fermi-LAT detection limit with deep learning. J. Cosmol. Astropart. Phys., 09(9), 029–39pp.
Abstract: We reconstruct the extra-galactic gamma-ray source-count distribution, or dN/dS, of resolved and unresolved sources by adopting machine learning techniques. Specifically, we train a convolutional neural network on synthetic 2-dimensional sky-maps, which are built by varying parameters of underlying source-counts models and incorporate the FermiLAT instrumental response functions. The trained neural network is then applied to the Fermi-LAT data, from which we estimate the source count distribution down to flux levels a factor of 50 below the Fermi-LAT threshold. We perform our analysis using 14 years of data collected in the (1, 10) GeV energy range. The results we obtain show a source count distribution which, in the resolved regime, is in excellent agreement with the one derived from cataloged sources, and then extends as dN/dS " S-2 in the unresolved regime, down to fluxes of 5 center dot 10-12 cm-2 s-1. The neural network architecture and the devised methodology have the flexibility to enable future analyses to study the energy dependence of the source-count distribution.
|
|
|
|
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.
|
|
|
|
De La Torre Luque, P., Gaggero, D., Grasso, D., & Marinelli, A. (2022). Prospects for detection of a galactic diffuse neutrino flux. Front. Astron. Space Sci., 9, 1041838–9pp.
Abstract: A Galactic cosmic-ray transport model featuring non-homogeneous transport has been developed over the latest years. This setup is aimed at reproducing gamma-ray observations in different regions of the Galaxy (with particular focus on the progressive hardening of the hadronic spectrum in the inner Galaxy) and was shown to be compatible with the very-high-energy gamma-ray diffuse emission recently detected up to PeV energies. In this work, we extend the results previously presented to test the reliability of that model throughout the whole sky. To this aim, we compare our predictions with detailed longitude and latitude profiles of the diffuse gamma-ray emission measured by Fermi-LAT for different energies and compute the expected Galactic nu diffuse emission, comparing it with current limits from the ANTARES collaboration. We emphasize that the possible detection of a Galactic nu component will allow us to break the degeneracy between our model and other scenarios featuring prominent contributions from unresolved sources and TeV halos.
|
|
|
|
ANTARES and IceCube Collaborations(Albert, A. et al), Barrios-Marti, J., Coleiro, A., Colomer, M., Hernandez-Rey, J. J., Illuminati, G., et al. (2018). Joint Constraints on Galactic Diffuse Neutrino Emission from the ANTARES and IceCube Neutrino Telescopes. Astrophys. J. Lett., 868(2), L20–7pp.
Abstract: The existence of diffuse Galactic neutrino production is expected from cosmic-ray interactions with Galactic gas and radiation fields. Thus, neutrinos are a unique messenger offering the opportunity to test the products of Galactic cosmic-ray interactions up to energies of hundreds of TeV. Here we present a search for this production using ten years of Astronomy with a Neutrino Telescope and Abyss environmental RESearch (ANTARES) track and shower data, as well as seven years of IceCube track data. The data are combined into a joint likelihood test for neutrino emission according to the KRA(gamma) model assuming a 5 PeV per nucleon Galactic cosmic-ray cutoff. No significant excess is found. As a consequence, the limits presented in this Letter start constraining the model parameter space for Galactic cosmic-ray production and transport.
|
|
