First public GPU-accelerated pulse-profile modeling code for X-ray millisecond pulsars that delivers 10^3–10^4 speedups to 2–5 ms per evaluation at 10^{-3} relative accuracy and removes an interpolation bias in atmosphere tables.
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A constrained Gaussian-process bridge prior generates model-agnostic, nonparametric, thermodynamically consistent priors for neutron-star equation-of-state inference.
Different parametrizations of density dependence in covariant density functionals produce significant variations in the high-density equation of state and symmetry energy, with rational-function forms providing flexibility when saturation properties are adjusted and constrained by multimessenger ast
citing papers explorer
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GPU-Accelerated X-ray Pulse Profile Modeling
First public GPU-accelerated pulse-profile modeling code for X-ray millisecond pulsars that delivers 10^3–10^4 speedups to 2–5 ms per evaluation at 10^{-3} relative accuracy and removes an interpolation bias in atmosphere tables.
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Constrained Gaussian-process bridge prior for neutron-star equation-of-state inference
A constrained Gaussian-process bridge prior generates model-agnostic, nonparametric, thermodynamically consistent priors for neutron-star equation-of-state inference.
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Bayesian inferences on covariant density functionals from multimessenger astrophysical data: Influences of parametrizations of density dependent couplings
Different parametrizations of density dependence in covariant density functionals produce significant variations in the high-density equation of state and symmetry energy, with rational-function forms providing flexibility when saturation properties are adjusted and constrained by multimessenger ast