Abstract: A search for astrophysical pointlike neutrino sources using the data collected by the ANTARES detector between 2007 January 29 and 2017 December 31 is presented. A likelihood method is used to assess the significance of an excess of muon neutrinos inducing track-like events in correlation with the location of a list of possible sources. Different sets of objects are tested in the analysis: (a) a subsample of the Fermi 3LAC catalog of blazars, (b) a jet-obscured population of active galactic nuclei, (c) a sample of hard X-ray selected radio galaxies, (d) a star-forming galaxy catalog, and (e) a public sample of 56 very-high-energy track events from the IceCube experiment. None of the tested sources shows a significant association with the sample of neutrinos detected by ANTARES. The smallest p-value is obtained for the catalog of radio galaxies with an equal-weights hypothesis, with a pre-trial p-value equivalent to a 2.8 sigma excess, which is equivalent to 1.6 sigma post-trial. In addition, the results of a dedicated analysis for the blazar MG3 J225517+2409 are also reported: this source is found to be the most significant within the Fermi 3LAC sample, with five ANTARES events located less than one degree from the source. This blazar showed evidence of flaring activity in Fermi data, in spacetime coincidence with a high-energy track detected by IceCube. An a posteriori significance of 2.6 sigma for the combination of ANTARES and IceCube data is reported.

Abstract: The High Altitude Water Cherenkov (HAWC) observatory and the High Energy Stereoscopic System (H.E.S.S.) are two leading instruments in the ground-based very-high-energy gamma-ray domain. HAWC employs the water Cherenkov detection (WCD) technique, while H.E.S.S. is an array of Imaging Atmospheric Cherenkov Telescopes (IACTs). The two facilities therefore differ in multiple aspects, including their observation strategy, the size of their field of view, and their angular resolution, leading to different analysis approaches. Until now, it has been unclear if the results of observations by both types of instruments are consistent: several of the recently discovered HAWC sources have been followed up by IACTs, resulting in a confirmed detection only in a minority of cases. With this paper, we go further and try to resolve the tensions between previous results by performing a new analysis of the H.E.S.S. Galactic plane survey data, applying an analysis technique comparable between H.E.S.S. and HAWC. Events above 1 TeV are selected for both data sets, the point-spread function of H.E.S.S. is broadened to approach that of HAWC, and a similar background estimation method is used. This is the first detailed comparison of the Galactic plane observed by both instruments. H.E.S.S. can confirm the gamma-ray emission of four HAWC sources among seven previously undetected by IACTs, while the three others have measured fluxes below the sensitivity of the H.E.S.S. data set. Remaining differences in the overall gamma-ray flux can be explained by the systematic uncertainties. Therefore, we confirm a consistent view of the gamma-ray sky between WCD and IACT techniques.

Abstract: On 2019 October 1, the IceCube Collaboration detected a muon track neutrino with a high probability of being of astrophysical origin, IC191001A. After a few hours, the tidal disruption event (TDE) AT2019dsg, observed by the Zwicky Transient Facility (ZTF), was indicated as the most likely counterpart of the IceCube track. More recently, the follow-up campaign of the IceCube alerts by ZTF suggested a second TDE, AT2019fdr, as a promising counterpart of another IceCube muon track candidate, IC200530A, detected on 2020 May 30. Here, these intriguing associations are followed-up by searching for neutrinos in the ANTARES detector from the directions of AT2019dsg and AT2019fdr using a time-integrated approach. As no significant evidence for space clustering is found in the ANTARES data, upper limits on the one-flavor neutrino flux and fluence are set.

Abstract: The High Altitude Water Cherenkov (HAWC) Gamma-Ray Observatory surveys the very high-energy sky in the 300 GeV to >100 TeV energy range. HAWC has detected two blazars above 11 sigma, Markarian 421 (Mrk 421) and Markarian 501 (Mrk 501). The observations are comprised of data taken in the period between 2015 June and 2018 July, resulting in similar to 1038 days of exposure. In this work, we report the time-averaged spectral analyses for both sources, above 0.5 TeV. Taking into account the flux attenuation due to the extragalactic background light, the intrinsic spectrum of Mrk 421 is described by a power law with an exponential energy cutoff with index alpha = 2.26 +/- (0.12)(stat)((+0.17)(-0.2))(sys) and energy cutoff E-c = 5.1 +/- (1.6)(stat)((+1.4)(-2.5))(sys) TeV, while the intrinsic spectrum of Mrk 501 is better described by a simple power law with index alpha = 2.61 +/- (0.11)(stat)((+)(0.01)(-0.07))(sys). The maximum energies at which the Mrk 421 and Mrk 501 signals are detected are 9 and 12 TeV, respectively. This makes these some of the highest energy detections to date for spectra averaged over years-long timescales. Since the observation of gamma radiation from blazars provides information about the physical processes that take place in their relativistic jets, it is important to study the broadband spectral energy distributions (SEDs) of these objects. For this purpose, contemporaneous data in the gamma-ray band to the X-ray range, and literature data in the radio to UV range, were used to build time-averaged SEDs that were modeled within a synchrotron-self Compton leptonic scenario.

Abstract: Understanding the halo-galaxy connection is fundamental in order to improve our knowledge on the nature and properties of dark matter. In this work, we build a model that infers the mass of a halo given the positions, velocities, stellar masses, and radii of the galaxies it hosts. In order to capture information from correlations among galaxy properties and their phase space, we use Graph Neural Networks (GNNs), which are designed to work with irregular and sparse data. We train our models on galaxies from more than 2000 state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations project. Our model, which accounts for cosmological and astrophysical uncertainties, is able to constrain the masses of the halos with a similar to 0.2 dex accuracy. Furthermore, a GNN trained on a suite of simulations is able to preserve part of its accuracy when tested on simulations run with a different code that utilizes a distinct subgrid physics model, showing the robustness of our method. The PyTorch Geometric implementation of the GNN is publicly available on GitHub (https://github.com/PabloVD/HaloGraphNet).