HAWC Collaboration(Albert, A. et al), & Salesa Greus, F. (2020). 3HWC: The Third HAWC Catalog of Very-high-energy Gamma-Ray Sources. Astrophys. J., 905(1), 76–14pp.
Abstract: We present a new catalog of TeV gamma-ray sources using 1523 days of data from the High-Altitude Water Cherenkov (HAWC) Observatory. The catalog represents the most sensitive survey of the northern gamma-ray sky at energies above several TeV, with three times the exposure compared to the previous HAWC catalog, 2HWC. We report 65 sources detected at >= 5 sigma significance, along with the positions and spectral fits for each source. The catalog contains eight sources that have no counterpart in the 2HWC catalog, but are within 1 degrees of previously detected TeV emitters, and 20 sources that are more than 1 degrees away from any previously detected TeV source. Of these 20 new sources, 14 have a potential counterpart in the fourth Fermi Large Area Telescope catalog of gamma-ray sources. We also explore potential associations of 3HWC sources with pulsars in the Australia Telescope National Facility (ATNF) pulsar catalog and supernova remnants in the Galactic supernova remnant catalog.
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HAWC Collaboration(Albert, A. et al), & Salesa Greus, F. (2021). A Survey of Active Galaxies at TeV Photon Energies with the HAWC Gamma-Ray Observatory. Astrophys. J., 907(2), 67–18pp.
Abstract: The High Altitude Water Cherenkov (HAWC) Gamma-Ray Observatory continuously detects TeV photons and particles within its large field of view, accumulating every day a deeper exposure of two-thirds of the sky. We analyzed 1523 days of HAWC live data acquired over four and a half years, in a follow-up analysis of 138 nearby (z < 0.3) active galactic nuclei from the Third Catalog of Hard Fermi-LAT sources culminating within 40 degrees of the zenith at Sierra Negra, the HAWC site. This search for persistent TeV emission used a maximum-likelihood analysis assuming intrinsic power-law spectra attenuated by pair production of gamma-ray photons with the extragalactic background light. HAWC clearly detects persistent emission from Mkn 421 and Mkn 501, the two brightest blazars in the TeV sky, at 65 sigma and 17 sigma level, respectively. Marginal evidence, just above the 3 sigma level, was found for three other known very high-energy emitters: the radio galaxy M87 and the BL Lac objects VER J0521+211 and 1ES 1215+303, the latter two at z similar to 0.1. We find a 4.2 sigma evidence for collective emission from the set of 30 previously reported very high-energy sources, with Mkn 421 and Mkn 501 excluded. Upper limits are presented for the sample under the power-law assumption and in the predefined (0.5-2.0), (2.0-8.0), and (8.0-32.0) TeV energy intervals.
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ANTARES Collaboration(Adrian-Martinez, S. et al), Barrios-Marti, J., Hernandez-Rey, J. J., Sanchez-Losa, A., Tönnis, C., Zornoza, J. D., et al. (2016). The first combined search for neutrino point-sources in the Southern Hemisphere with the ANTARES and IceCube neutrino telescopes. Astrophys. J., 823(1), 65–12pp.
Abstract: We present the results of searches for point-like sources of neutrinos based on the first combined analysis of data from both the ANTARES and IceCube neutrino telescopes. The combination of both detectors, which differ in size and location, forms a window in the southern sky where the sensitivity to point sources improves by up to a factor of 2 compared with individual analyses. Using data recorded by ANTARES from 2007 to 2012, and by IceCube from 2008 to 2011, we search for sources of neutrino emission both across the southern sky and from a preselected list of candidate objects. No significant excess over background has been found in these searches, and flux upper limits for the candidate sources are presented for E-2.5 and E-2 power-law spectra with different energy cut-offs.
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AMON Team, H. A. W. C. and I. C. C.(A. S., H.A. et al), & Salesa Greus, F. (2021). Multimessenger Gamma-Ray and Neutrino Coincidence Alerts Using HAWC and IceCube Subthreshold Data. Astrophys. J., 906(1), 63–10pp.
Abstract: The High Altitude Water Cerenkov (HAWC) and IceCube observatories, through the Astrophysical Multimessenger Observatory Network (AMON) framework, have developed a multimessenger joint search for extragalactic astrophysical sources. This analysis looks for sources that emit both cosmic neutrinos and gamma rays that are produced in photohadronic or hadronic interactions. The AMON system is running continuously, receiving subthreshold data (i.e., data that are not suited on their own to do astrophysical searches) from HAWC and IceCube, and combining them in real time. Here we present the analysis algorithm, as well as results from archival data collected between 2015 June and 2018 August, with a total live time of 3.0 yr. During this period we found two coincident events that have a false-alarm rate (FAR) of <1 coincidence yr(-1), consistent with the background expectations. The real-time implementation of the analysis in the AMON system began on 2019 November 20 and issues alerts to the community through the Gamma-ray Coordinates Network with an FAR threshold of <4 coincidences yr(-1).
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Villaescusa-Navarro, F. et al, & Villanueva-Domingo, P. (2022). The CAMELS Multifield Data Set: Learning the Universe's Fundamental Parameters with Artificial Intelligence. Astrophys. J. Suppl. Ser., 259(2), 61–14pp.
Abstract: We present the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) Multifield Data set (CMD), a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and stars from more than 2000 distinct simulated universes at several cosmic times. The 2D maps and 3D grids represent cosmic regions that span similar to 100 million light-years and have been generated from thousands of state-of-the-art hydrodynamic and gravity-only N-body simulations from the CAMELS project. Designed to train machine-learning models, CMD is the largest data set of its kind containing more than 70 TB of data. In this paper we describe CMD in detail and outline a few of its applications. We focus our attention on one such task, parameter inference, formulating the problems we face as a challenge to the community. We release all data and provide further technical details at https://camels-multifield-dataset.readthedocs.io.
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