Abstract: We present the application of convolutional neural networks to a particular problem in gamma ray astronomy. Explicitly, we use this method to investigate the origin of an excess emission of GeV gamma rays in the direction of the Galactic Center, reported by several groups by analyzing Fermi-LAT data. Interpretations of this excess include gamma rays created by the annihilation of dark matter particles and gamma rays originating from a collection of unresolved point sources, such as millisecond pulsars. We train and test convolutional neural networks with simulated Fermi-LAT images based on point and diffuse emission models of the Galactic Center tuned to measured gamma ray data. Our new method allows precise measurements of the contribution and properties of an unresolved population of gamma ray point sources in the interstellar diffuse emission model. The current model predicts the fraction of unresolved point sources with an error of up to 10% and this is expected to decrease with future work.

Abstract: We study the impact of the cosmological parameters uncertainties on the measurements of primordial non-Gaussianity through the large-scale non-Gaussian halo bias effect. While this is not expected to be an issue for the standard Lambda CDM model, it may not be the case for more general models that modify the large-scale shape of the power spectrum. We consider the so-called local non-Gaussianity model, parametrized by the f(NL) non-Gaussianity parameter which is zero for a Gaussian case, and make forecasts on f(NL) from planned surveys, alone and combined with a Planck CMB prior. In particular, we consider EUCLID- and LSST-like surveys and forecast the correlations among f(NL) and the running of the spectral index alpha(s), the dark energy equation of state w, the effective sound speed of dark energy perturbations c(s)(2), the total mass of massive neutrinos M-nu = Sigma m(nu), and the number of extra relativistic degrees of freedom N-nu(rel). Neglecting CMB information on f(NL) and scales k > 0.03h/Mpc, we find that, if N-nu(rel) is assumed to be known, the uncertainty on cosmological parameters increases the error on f(NL) by 10 to 30% depending on the survey. Thus the f(NL) constraint is remarkable robust to cosmological model uncertainties. On the other hand, if N-nu(rel) is simultaneously constrained from the data, the f(NL) error increases by similar to 80%. Finally, future surveys which provide a large sample of galaxies or galaxy clusters over a volume comparable to the Hubble volume can measure primordial non-Gaussianity of the local form with a marginalized 1-sigma error of the order Delta f(NL) similar to 2 – 5, after combination with CMB priors for the remaining cosmological parameters. These results are competitive with CMB bispectrum constraints achievable with an ideal CMB experiment.

Abstract: The cosmological X-ray emission associated to the possible radiative decay of sterile neutrinos is composed by a collection of lines at different energies. For a given mass, each line corresponds to a given redshift. In this work, we cross correlate such line emission with catalogs of galaxies tracing the dark matter distribution at different redshifts. We derive observational prospects by correlating the X-ray sky that will be probed by the eROSITA and Athena missions with current and near future photometric and spectroscopic galaxy surveys. A relevant and unexplored fraction of the parameter space of sterile neutrinos can be probed by this technique.