Work

Chasing the Neutrino Blazar Candidates

Year: 2024

Type: article

Abstract: In our study of the correlations between IceCube-detected neutrino events and γ-ray properties of blazars, we recognize the inherent challenges posed by the limited detection of neutrinos. In this paper, we explore few-shot learning to deal with the class imbalance and few-shot issues presented in the incremental version of the 12 yr Fermi-LAT γ-ray source catalog (4FGL_ DR3). Specifically, we train a triplet network to transform the blazars with neutrino emission (NBs) and nonblazar samples into an embedding space where their similarities can be measured. With two-way three-shot learning, 199 out of 3708 blazars without neutrino emission (non-NBs) are considered as the potential blazars emitting neutrinos (NB candidates, or NBCs for short), with a similarity score against NBs exceeding 98%. Moreover, the Kolmogorov–Smirnov test supports our identification of NBCs.

Source: The Astrophysical Journal Supplement Series

DOI: 10.3847/1538-4365/ad7730

Authors: Jingtian Zhu, Haitao Cao, Hubing Xiao, Zhiyuan Pei, JunHui Fan, Denis Bastieri

Language: English

Topic: Astrophysics and Cosmic Phenomena

Subfield: Nuclear and High Energy Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $4,499

Funders: Shanghai Science and Technology Development Foundation, Foundation for Innovative Research Groups of the National Natural Science Foundation of China

Awards: G1935991767, G640080281