Previous detections of individual astrophysical sources of neutrinos are limited to the Sun and the supernova 1987A, whereas the origins of the diffuse flux of high-energy cosmic neutrinos remain unidentified. On 22 September 2017, we detected a high-energy neutrino, IceCube-170922A, with an energy of ~290 tera-electron volts. Its arrival direction was consistent with the location of a known γ-ray blazar, TXS 0506+056, observed to be in a flaring state. An extensive multiwavelength campaign followed, ranging from radio frequencies to γ-rays. These observations characterize the variability and energetics of the blazar and include the detection of TXS 0506+056 in very-high-energy γ-rays. This observation of a neutrino in spatial coincidence with a γ-ray-emitting blazar during an active phase suggests that blazars may be a source of high-energy neutrinos.

A deep survey of the Large Magellanic Cloud at ∼ 0.1−100 TeV photon energies with the Cherenkov Telescope Array is planned. We assess the detection prospects based on a model for the emission of the galaxy, comprising the four known TeV emitters, mock populations of sources, and interstellar emission on galactic scales. We also assess the detectability of 30 Doradus and SN 1987A, and the constraints that can be derived on the nature of dark matter. The survey will allow for fine spectral studies of N 157B, N 132D, LMC P3, and 30 Doradus C, and half a dozen other sources should be revealed, mainly pulsar-powered objects. The remnant from SN 1987A could be detected if it produces cosmic-ray nuclei with a flat power-law spectrum at high energies, or with a steeper index 2.3 − 2.4 pending a flux increase by a factor > 3 − 4 over ∼ 2015 − 2035. Large-scale interstellar emission remains mostly out of reach of the survey if its > 10 GeV spectrum has a soft photon index ∼ 2.7, but degree-scale 0.1 − 10 TeV pion-decay emission could be detected if the cosmic-ray spectrum hardens above >100 GeV. The 30 Doradus star-forming region is detectable if acceleration efficiency is on the order of 1 − 10% of the mechanical luminosity and diffusion is suppressed by two orders of magnitude within < 100 pc. Finally, the survey could probe the canonical velocity-averaged cross section for self-annihilation of weakly interacting massive particles for cuspy Navarro-Frenk-White profiles.

Background showers triggered by hadrons represent over 99.9% of all particles arriving at groundbased gamma-ray observatories. An important stage in the data analysis of these observatories, therefore, is the removal of hadron-triggered showers. Currently, the High-Altitude Water Cherenkov (HAWC) gamma-ray observatory employs an algorithm based on a single cut in two variables, unlike other ground-based gamma-ray observatories (e.g. H.E.S.S., VERITAS), which employ a large number of variables to separate the primary particles. In this work, we explore machine learning techniques (Boosted Decision Trees and Neural Networks) to identify the primary particles detected by HAWC. Our new gamma/hadron separation techniques were tested on data from the Crab nebula, the standard reference in Very High Energy astronomy, showing an improvement compared to the standard HAWC background rejection method.

Galaxy clusters' dynamics constitute a major piece of evidence for the existence of dark matter in astrophysical structures. The decay or annihilation of dark matter particles is hypothesized to produce a steady flux of very-high-energy gamma rays correlated with the direction of a cluster of galaxies. The Virgo cluster, being only 16 Mpc away and spanning several degrees across the sky is an excellent target to search for signatures of particle dark matter interactions. The High Altitude Water Cherenkov (HAWC) observatory, due to its wide field of view and sensitivity to gamma rays at an energy-scale of 300 GeV-100 TeV is well-suited to perform the aforementioned search. We perform a search from the Virgo cluster for gamma-ray emission, assuming various dark matter sub-structure models using 1523 days of HAWC data. Our results provide the strongest constraints on the decay life-time of dark matter for masses above 20 TeV.

A wide range of data formats and proprietary software have traditionally been used in γ-ray astronomy, usually developed for a single specific mission or experiment. However, in recent years there has been an increasing effort towards making astronomical data open and easily accessible. Within the γ-ray community this has translated to the creation of a common data format across different γ-ray observatories: the "gamma-astro-data-format" (GADF). Based on a similar premise, opensource analysis packages, such as Gammapy, are being developed and aim to provide a single, robust tool which suits the needs of many experiments at once. In this contribution we show that data from the High-Altitude Water Cherenkov (HAWC) observatory can be made compatible with the GADF and present the first GADF-based production of event lists and instrument response functions for a ground-based wide-field instrument. We use these data products to reproduce with excellent agreement the published HAWC Crab spectrum using Gammapy. Having a common data format and analysis tools facilitates joint analysis between different experiments and effective data sharing. This will be especially important for next-generation instruments, such as the proposed Southern Wide-field Gamma-ray Observatory (SWGO) and the planned Cherenkov Telescope Array (CTA).