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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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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.
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Amoroso, S., Caron, S., Jueid, A., Ruiz de Austri, R., & Skands, P. (2019). Estimating QCD uncertainties in Monte Carlo event generators for gamma-ray dark matter searches. J. Cosmol. Astropart. Phys., 05(5), 007–44pp.
Abstract: Motivated by the recent galactic center gamma-ray excess identified in the Fermi-LAT data, we perform a detailed study of QCD fragmentation uncertainties in the modeling of the energy spectra of gamma-rays from Dark-Matter (DM) annihilation. When Dark-Matter particles annihilate to coloured final states, either directly or via decays such as W(*) -> qq-', photons are produced from a complex sequence of shower, hadronisation and hadron decays. In phenomenological studies their energy spectra are typically computed using Monte Carlo event generators. These results have however intrinsic uncertainties due to the specific model used and the choice of model parameters, which are difficult to asses and which are typically neglected. We derive a new set of hadronisation parameters (tunes) for the PYTHIA 8.2 Monte Carlo generator from a fit to LEP and SLD data at the Z peak. For the first time we also derive a conservative set of uncertainties on the shower and hadronisation model parameters. Their impact on the gamma-ray energy spectra is evaluated and discussed for a range of DM masses and annihilation channels. The spectra and their uncertainties are also provided in tabulated form for future use. The fragmentation-parameter uncertainties may be useful for collider studies as well.
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Ancilotto, F., Barranco, M., Navarro, J., & Pi, M. (2011). Cavitation of electron bubbles in liquid parahydrogen. Mol. Phys., 109(23-24), 2757–2762.
Abstract: Within a finite-temperature density functional approach, we have investigated the structure of electron bubbles in liquid parahydrogen below the saturated vapour pressure, determining the critical pressure at which electron bubbles explode as a function of temperature. The electron-parahydrogen interaction has been modelled by a Hartree-type local potential fitted to the experimental value of the conduction band-edge for a delocalized electron in pH(2). We have found that the pressure for bubble explosion is, in absolute value, about a factor of two smaller than that of the homogeneous cavitation pressure in the liquid. Comparison with the results obtained within the capillary model shows the limitations of this approximation, especially as temperature increases.
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Ancilotto, F., Barranco, M., Navarro, J., & Pi, M. (2016). A Density Functional Approach to Para-hydrogen at Zero Temperature. J. Low Temp. Phys., 185(1-2), 26–38.
Abstract: We have developed a density functional (DF) built so as to reproduce either the metastable liquid or the solid equation of state of bulk para-hydrogen, as derived from quantum Monte Carlo zero temperature calculations. As an application, we have used it to study the structure and energetics of small para-hydrogen clusters made of up to molecules. We compare our results for liquid clusters with diffusion Monte Carlo (DMC) calculations and find a fair agreement between them. In particular, the transition found within DMC between hollow-core structures for small N values and center-filled structures at higher N values is reproduced. The present DF approach yields results for (pH) clusters indicating that for small N values a liquid-like character of the clusters prevails, while solid-like clusters are instead energetically favored for .
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