activity
20052022
most cited3He Spin-Dependent Cross Sections and Sum Rules

24 citations · 40 across the 9 of their papers we have counts for

collaborators

14 papers

hep-ex20211 cited

Combined dark matter searches towards dwarf spheroidal galaxies with Fermi-LAT, HAWC, H.E.S.S., MAGIC, and VERITAS

Celine Armand, Eric Charles, Mattia di Mauro +13

Cosmological and astrophysical observations suggest that 85\% of the total matter of the Universe is made of Dark Matter (DM). However, its nature remains one of the most challengi…

astro-ph.HE2021

Particle Acceleration in the Cygnus Superbubble

B. Hona

The Cygnus Cocoon is the first gamma-ray superbubble powered by a massive stellar association, the OB2 association. It was postulated that the combined effects of the stellar winds…

astro-ph.HE2021

The all-particle cosmic ray energy spectrum measured with HAWC

J. A. Morales-Soto, J. C. Arteaga-Velázquez

Thanks to recent technological development, a new generation of cosmic ray experiments have been developed with more sensitivity to study these particles in the primary energy inte…

astro-ph.HE20215 cited

Searching for very-high-energy electromagnetic counterparts to gravitational-wave events with the Cherenkov Telescope Array

Barbara Patricelli, Alessandro Carosi, Lara Nava +27

The detection of electromagnetic (EM) emission following the gravitational wave (GW) event GW170817 opened the era of multi-messenger astronomy with GWs and provided the first dire…

astro-ph.HE2021

NuSTAR broad-band X-ray observational campaign of energetic pulsar wind nebulae in synergy with VERITAS, HAWC and Fermi gamma-ray telescopes

Kaya Mori, Hongjun An, Daniel Burgess +13

We report recent progress on the on-going NuSTAR observational campaign of 8 TeV-detected pulsar wind nebulae (PWNe). This campaign constitutes a major part of our NuSTAR study of…

physics.ins-det2021

Horizontal muon track identification with neural networks in HAWC

J. R. Angeles Camacho, H. León Vargas

Nowadays the implementation of artificial neural networks in high-energy physics has obtained excellent results on improving signal detection. In this work we propose to use neural…