Speaker
Description
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 measure the radii of neutron stars (NSs) with an accuracy better than about 0.1 km. However, it remains unclear which aspects of the EOS will be better constrained and by how much. In this talk, we address this issue based on our recent work [1,2,3] within a Bayesian framework using a meta-model EOS for NSs. In particular, we infer the posterior probability distributions (PDFs) of incompressibility and skewness of symmetric nuclear matter, as well as the slope, curvature, and skewness characterizing the density dependence of the nuclear symmetry energy, from high-precision mock radius data with accuracies ranging from about 1.0 km to 0.1 km. Effects of high-precision NS radius measurements on determining properties of the first-order hadron-quark phase transition and the formation of twin stars will also be discussed.
References
[1] Bayesian Inference of Hybrid Star Properties from Future High-Precision Measurements of Their Radii, Bao-An Li, Xavier Grundler, Wen-Jie Xie and Nai-Bo Zhang, ArXiV: 2505.00194, The Astrophysical Journal (2026) in press.
[2] Bayesian quantification of observability and equation of state of twin stars, Xavier Grundler and Bao-An Li, Phys. Rev. D 112 (2025) 10, 103012
[3] Bayesian inference of fine features of the nuclear equation of state from future neutron star radius measurements to 0.1 km accuracy, Bao-An Li, Xavier Grundler, Wen-Jie Xie and Nai-Bo Zhang, Phys. Rev. D 110 (2024) 10, 103040
