most citedSearch for directional associations between Baikal Gigaton Volume Detector neutrino-induced cascades and high-energy astrophysical sources

22 citations · 27 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.IM2023

Track-Like Event Analysis at the Baikal-GVD Neutrino Telescope

V. M. Aynutdinov, V. A. Allakhverdyan, A. D. Avrorin +62

Reconstructed tracks of muons produced in neutrino interactions provide the precise probe for the neutrino direction. Therefore, track-like events are a powerful tool to search for…

astro-ph.IM2023

Time Calibration of the Baikal-GVD Neutrino Telescope with Atmospheric Muons

V. M. Aynutdinov, V. A. Allakhverdyan, A. D. Avrorin +62

We present a new procedure for time calibration of the Baikal-GVD neutrino telescope. The track reconstruction quality depends on accurate measurements of arrival times of Cherenko…

astro-ph.HE202322 cited

Search for directional associations between Baikal Gigaton Volume Detector neutrino-induced cascades and high-energy astrophysical sources

V. A. Allakhverdyan, A. D. Avrorin, A. V. Avrorin +65

Baikal-GVD has recently published its first measurement of the diffuse astrophysical neutrino flux, performed using high-energy cascade-like events. We further explore the Baikal-G…

astro-ph.HE2023

Baikal-GVD Astrophysical Neutrino Candidate near the Blazar TXS~0506+056

V. M. Aynutdinov, V. A. Allakhverdyan, A. D. Avrorin +71

We report on the observation of a rare neutrino event detected by Baikal-GVD in April 2021. The event GVD210418CA is the highest-energy cascade observed by Baikal-GVD so far from t…

astro-ph.IM20215 cited

Deep learning method for identifying mass composition of ultra-high-energy cosmic rays

O. Kalashev, I. Kharuk, M. Kuznetsov +4

We introduce a novel method for identifying the mass composition of ultra-high-energy cosmic rays using deep learning. The key idea of the method is to use a chain of two neural ne…