Related papers: Extracting the gamma-ray source-count distribution…
The gamma-ray sky >100 MeV is dominated by the diffuse emissions from interactions of cosmic rays with the interstellar gas and radiation fields of the Milky Way. Observations of these diffuse emissions provide a tool to study cosmic-ray…
We present a catalog of gamma-ray sources at energies above 10 GeV based on data from the Large Area Telescope (LAT) accumulated during the first three years of the Fermi Gamma-ray Space Telescope mission. The first Fermi-LAT catalog of…
In the latest data release from the Fermi $\gamma$-ray Space Telescope (the 4th Fermi LAT 14 yr Catalog, or 4FGL), more than 50% of the Galactic sources are yet to be identified. We observed 13 unidentified Fermi LAT sources with the…
The Fermi-LAT unassociated sources represent some of the most enigmatic gamma-ray sources in the sky. Observations with the Swift-XRT and -UVOT telescopes have identified hundreds of likely X-ray and UV/optical counterparts in the…
Machine learning algorithms have been used to determine probabilistic classifications of unassociated sources. Often classification into two large classes, such as Galactic and extra-galactic, is considered. However, there are many more…
Nearly 1/3 of the sources listed in the Third Fermi Large Area Telescope (LAT) catalog (3FGL) remain unassociated. It is possible that predicted and even unanticipated gamma-ray source classes are present in these data waiting to be…
A deep neural network (DNN) has been developed to generate the distributions of nuclear charge density, utilizing the training data from the relativistic density functional theory and incorporating available experimental charge radii of…
While supernova remnants (SNRs) are widely thought to be powerful accelerators, evidence comes largely from a small number of well-studied cases. Here we systematically determine the gamma-ray emission from all known Galactic SNRs,…
We demonstrate the potential of Deep Learning methods for measurements of cosmological parameters from density fields, focusing on the extraction of non-Gaussian information. We consider weak lensing mass maps as our dataset. We aim for our…
The two leading hypotheses for the Galactic Center Excess (GCE) in the $\textit{Fermi}$ data are an unresolved population of faint millisecond pulsars (MSPs) and dark-matter (DM) annihilation. The dichotomy between these explanations is…
We have analyzed the GeV gamma-ray emission in the region of the supernova remnant (SNR) Kes 78 using $\sim$16.7 years of Fermi-LAT observations and found that the catalog sources 4FGL J1852.4+0037e and 4FGL J1851.8$-$0007c are better…
We present an incremental version (4FGL-DR4, for Data Release 4) of the fourth Fermi-LAT catalog containing 7194 gamma-ray sources. Based on the first 14 years of science data in the energy range from 50 MeV to 1 TeV, it uses the same…
Cosmic rays of energies up to a few PeV are believed to be of galactic origin, yet individual sources have still not been firmly identified. Due to inelastic collisions with the interstellar gas, cosmic-ray nuclei produce a diffuse flux of…
Mapping data from and/or onto a known family of distributions has become an important topic in machine learning and data analysis. Deep generative models (e.g., generative adversarial networks ) have been used effectively to match known and…
Previous analyses of point sources in the gamma-ray range were done either below 30 MeV or above 100 MeV. Below 30 MeV, the imaging Compton telescope (COMPTEL) onboard NASA's Compton Gamma-Ray Observatory detected 26 steady sources in the…
With a decade of gamma-ray data from the Fermi-LAT telescope, we can now hope to answer how well we know the local Universe at gamma-ray frequencies. On the other hand, with gamma-ray data alone it is not possible to directly access the…
In this work, starting from 21 months of data from the Fermi-Large Area Telescope, we derive maps of the residual isotropic gamma-ray emission, a relevant fraction of which is expected to be contributed by the extragalactic diffuse…
In recent years, sub-grid models for turbulent mixing have been developed by data-driven methods for large eddy simulation (LES). Super-resolution is a data-driven deconvolution technique in which deep convolutional neural networks are…
Gamma-ray emission provides constraints on the non-thermal radiation processes at play in astrophysical particle accelerators. This allows both the nature of accelerated particles and the maximum energy that they can reach to be determined.…
The Fermi-LAT collaboration has studied the gamma-ray emission from a stacked population of dwarf spheroidal galaxies and used this information to set constraints on the dark matter annihilation cross section. Interestingly, their analysis…