Abstract: Context. 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 challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.

Abstract: Electrically charged particles can be created by the decay of strong enough electric fields, a phenomenon known as the Schwinger mechanism(1). By electromagnetic duality, a sufficiently strong magnetic field would similarly produce magnetic monopoles, if they exist(2). Magnetic monopoles are hypothetical fundamental particles that are predicted by several theories beyond the standard model(3-7) but have never been experimentally detected. Searching for the existence of magnetic monopoles via the Schwinger mechanism has not yet been attempted, but it is advantageous, owing to the possibility of calculating its rate through semi-classical techniques without perturbation theory, as well as that the production of the magnetic monopoles should be enhanced by their finite size(8,9) and strong coupling to photons(2,10). Here we present a search for magnetic monopole production by the Schwinger mechanism in Pb-Pb heavy ion collisions at the Large Hadron Collider, producing the strongest known magnetic fields in the current Universe(11). It was conducted by the MoEDAL experiment, whose trapping detectors were exposed to 0.235 per nanobarn, or approximately 1.8 x 10(9), of Pb-Pb collisions with 5.02-teraelectronvolt center-of-mass energy per collision in November 2018. A superconducting quantum interference device (SQUID) magnetometer scanned the trapping detectors of MoEDAL for the presence of magnetic charge, which would induce a persistent current in the SQUID. Magnetic monopoles with integer Dirac charges of 1, 2 and 3 and masses up to 75 gigaelectronvolts per speed of light squared were excluded by the analysis at the 95% confidence level. This provides a lower mass limit for finite-size magnetic monopoles from a collider search and greatly extends previous mass bounds.

Abstract: When a heavy atomic nucleus splits (fission), the resulting fragments are observed to emerge spinning(1); this phenomenon has been a mystery in nuclear physics for over 40 years(2,3). The internal generation of typically six or seven units of angular momentum in each fragment is particularly puzzling for systems that start with zero, or almost zero, spin. There are currently no experimental observations that enable decisive discrimination between the many competing theories for the mechanism that generates the angular momentum(4-12). Nevertheless, the consensus is that excitation of collective vibrational modes generates the intrinsic spin before the nucleus splits (pre-scission). Here we show that there is no significant correlation between the spins of the fragment partners, which leads us to conclude that angular momentum in fission is actually generated after the nucleus splits (post-scission). We present comprehensive data showing that the average spin is strongly mass-dependent, varying in saw-tooth distributions. We observe no notable dependence of fragment spin on the mass or charge of the partner nucleus, confirming the uncorrelated post-scission nature of the spin mechanism. To explain these observations, we propose that the collective motion of nucleons in the ruptured neck of the fissioning system generates two independent torques, analogous to the snapping of an elastic band. A parameterization based on occupation of angular momentum states according to statistical theory describes the full range of experimental data well. This insight into the role of spin in nuclear fission is not only important for the fundamental understanding and theoretical description of fission, but also has consequences for the gamma-ray heating problem in nuclear reactors(13,14), for the study of the structure of neutron-rich isotopes(15,16), and for the synthesis and stability of super-heavy elements(17,18). gamma-ray spectroscopy experiments on the origin of spin in the products of nuclear fission of spin-zero nuclei suggest that the fission fragments acquire their spin after scission, rather than before.