Systematics from NICER Pulse Profiles Drive Uncertainty in Multi-Messenger Inference of the Neutron Star Equation of State

TL;DR

This paper demonstrates that systematics in NICER pulse profile modeling significantly influence neutron star EOS constraints, emphasizing the importance of joint multi-messenger data analysis to reduce uncertainties.

Contribution

It systematically assesses how observational and modeling choices affect neutron star EOS inference, highlighting the dominant role of pulse profile systematics.

Findings

Pulse profile systematics dominate EOS uncertainties.

Choice of hot spot geometry impacts inferred EOS stiffness.

Bayesian analysis favors specific pulse profile models.

Abstract

We present new constraints on the neutron star equation of state (EOS) and mass distribution using a unified Bayesian inference framework that incorporates latest NICER measurements, including PSR J0614$-$3329, alongside gravitational wave data, radio pulsar masses, and nuclear theory. By systematically comparing four inference scenarios--varying in the inclusion of PSR J0614$-$3329 and in the pulse profile model used for PSR J0030+0451--we quantify the impact of observational and modeling choices on dense matter inference. We find that pulse profile systematics dominate EOS uncertainties: the choice of hot spot geometry for PSR J0030+0451 leads to significant shifts in the inferred stiffness of the EOS and maximum neutron star mass. In contrast, PSR J0614$-$3329 mildly softens the EOS at low densities, reducing the radius at \(1.4\,M_\odot\) by \(\sim 100\)~m. A Bayesian model comparison yields a Bayes factor of $\log_{10} \mathrm{BF} \approx 1.58$ in favor of the ST+PDT model over PDT-U, providing strong evidence that multi-messenger EOS inference can statistically discriminate between competing NICER pulse profile models. These results highlight the critical role of NICER systematics in dense matter inference and the power of joint analyses in breaking modeling degeneracies.