20 citations · 38 across the 9 of their papers we have counts for
9 papers
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…
Bayesian Constraints on the Neutron Star Equation of State with a Smooth Hadron-Quark Crossover
Xavier Grundler, Bao-An Li
We perform a Bayesian inference of the dense-matter equation of state (EOS) within a unified framework that incorporates hadronic matter, quark matter, and a smooth hadron-to-quark…
Bayesian Quantification of Observability and Equation of State of Twin Stars
Xavier Grundler, Bao-An Li
The possibility of discovering twin stars, two neutron stars (NSs) with the same mass but different radii, is usually studied in forward modelings by using a restricted number of N…
Bayesian Inference of Hybrid Star Properties from Future High-Precision Measurements of Their Radii
Bao-An Li, Xavier Grundler, Wen-Jie Xie +1
Future high-precision X-ray and gravitational-wave observations of neutron stars (NSs) are expected to constrain NS radii with uncertainties as small as ~km. Such unpr…
Bayesian Inference of Fine-Features of Nuclear Equation of State from Future Neutron Star Radius Measurements to 0.1km Accuracy
Bao-An Li, Xavier Grundler, Wen-Jie Xie +1
To more precisely constrain the Equation of State (EOS) of supradense neutron-rich nuclear matter, future high-precision X-ray and gravitational wave observatories are proposed to…
Neural Network Emulation of Flow in Heavy-Ion Collisions at Intermediate Energies
Nicholas Cox, Xavier Grundler, Bao-An Li
Applications of new techniques in machine learning are speeding up progress in research in various fields. In this work, we construct and evaluate a deep neural network (DNN) to be…