Equation-of-state-informed pulse profile modeling
Mariska Hoogkamer, Nathan Rutherford, Daniela Huppenkothen, Benjamin Ricketts, Anna L. Watts, Melissa Mendes, Isak Svensson, Achim Schwenk, Michael Kramer, Kai Hebeler, Tuomo Salmi, Devarshi Choudhury

TL;DR
This paper introduces an EOS-informed prior into pulse profile modeling of pulsars using normalizing flows, enabling more accurate and computationally efficient joint inference of neutron star parameters and the equation of state.
Contribution
It presents a novel intermediate approach that integrates EOS constraints into PPM, improving parameter estimation without the complexity of full hierarchical Bayesian inference.
Findings
Narrower radius credible intervals with EOS-informed priors.
EOS models favor different neutron star radii, affecting inferred properties.
Inclusion of PPM posteriors further constrains the EOS and neutron star parameters.
Abstract
NICER has enabled mass-radius inferences for pulsars using pulse profile modeling (PPM), providing constraints on the equation of state (EOS) of cold, dense matter. To date, PPM and EOS inference have been carried out as two separate steps, with the former using EOS-agnostic priors. This approach has several drawbacks. Ideally, one would perform a fully hierarchical Bayesian inference where the pulse profile and EOS model parameters are jointly fit, but implementing such a framework is complex and computationally demanding. Here, we present an intermediate solution introducing an EOS-informed prior on mass-radius into the existing PPM pipeline using normalizing flows. By focusing on the parameter space consistent with certain EOSs, this approach both tightens constraints on neutron star parameters while reducing computational costs and requiring minimal additional implementation effort.…
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Taxonomy
TopicsLaser-Matter Interactions and Applications · Spectroscopy and Quantum Chemical Studies · Laser-Plasma Interactions and Diagnostics
