429 citations · 3.3k across the 66 of their papers we have counts for
5 papers · 1 filter
Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge
Boris Panes, Christopher Eckner, Luc Hendriks +5
At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore…
Analyzing γ-rays of the Galactic Center with Deep Learning
Sascha Caron, Germán A. Gómez-Vargas, Luc Hendriks +1
We present a new method to interpret the -ray data of our inner Galaxy as measured by the Fermi Large Area Telescope (Fermi LAT). We train and test convolutional neural networks…
Bayesian analysis of cosmic-ray propagation: evidence against homogeneous diffusion
G. Jóhannesson, R. Ruiz de Austri, A. C. Vincent +8
We present the results of the most complete ever scan of the parameter space for cosmic ray (CR) injection and propagation. We perform a Bayesian search of the main GALPROP paramet…
Complementarity of Indirect and Accelerator Dark Matter Searches
G. Bertone, D. G. Cerdeno, M. Fornasa +3
Even if Supersymmetric particles are found at the Large Hadron Collider (LHC), it will be difficult to prove that they constitute the bulk of the Dark Matter (DM) in the Universe u…
Constraints on cosmic-ray propagation models from a global Bayesian analysis
R. Trotta, G. Johannesson, I. V. Moskalenko +3
Research in many areas of modern physics such as, e.g., indirect searches for dark matter and particle acceleration in SNR shocks, rely heavily on studies of cosmic rays (CRs) and…