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A Core-Collapse Supernova Neutrino Parameterization with Enhanced Physical Interpretability
Haihao Shi, Zhenyang Huang, Junda Zhou +2
We introduce a novel parameterization of supernova neutrino energy spectra with a clear physical motivation. Its central parameter, , quantifies the characteristic thermal-di…
Application of interpretable data-driven methods for the reconstruction of supernova neutrino energy spectra following fast neutrino flavor conversions
Haihao Shi, Zhenyang Huang, Qiyu Yan +3
Neutrinos can experience fast flavor conversions (FFCs) in highly dense astrophysical environments, such as core-collapse supernovae and neutron star mergers, potentially affecting…
Hunting Hidden Axion Signals in Pulsar Dispersion Measurements with Machine Learning
Haihao Shi, Zhenyang Huang, Qiyu Yan +3
In axion models, interactions between axions and electromagnetic waves induce frequency-dependent time delays determined by the axion mass and decay constant. These small delays ar…
Dark Matter (S)pins the Planet
Haihao Shi, Junda Zhou, Zhenyang Huang +2
Dark matter heating in planets has been proposed as a potential probe for dark matter detection. Assuming near-equilibrium conditions, we find that the energy input from dark matte…