20 citations · 83 across the 14 of their papers we have counts for
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Symbolic Regression for Interpretable Emulation of Proton Collective Flow in Intermediate-Energy Heavy-Ion Collisions
Nicholas Cox, Xavier Grundler, Bao-An Li
Symbolic regression provides an interpretable machine-learning approach for constructing explicit analytic relations between physical inputs and observables. In this work, we devel…
Quantifying the Information Gain from Future High-Precision Radius Measurements for Identifying Twin Neutron Stars
Bao-An Li, Xavier Grundler
Twin neutron stars (NSs), characterized by identical gravitational masses but different radii, are among the most promising astrophysical signatures of a strong first-order hadron-…
How Neutron Star Radii Encode the Dense-Matter Equation of State and Hadron-Quark Transition
Bao-An Li, Xavier Grundler
We investigate how future high-precision neutron star (NS) radius measurements encode microscopic information about the dense-matter equation of state (EOS), focusing on a possible…
Bayesian Inference of fine-features of dense matter EOS from future high-precision data of neutron star radii
Bao-An Li, Xavier Grundler, Wen-Jie Xie +1
Future high-precision X-ray and gravitational wave observatories are expected to measure the radii of neutron stars (NSs) with an accuracy better than about 0.1 km. However, it rem…
Universal EOS-Radius Inverse Mappings Govern Precision-Dependent Inference of the Neutron Star Equation of State
Bao-An Li
Bayesian inference of the neutron star (NS) equation of state (EOS) generally assumes that improved observations primarily reduce posterior uncertainties while leaving inferred EOS…