From Neutron Star Observables to the Equation of State. II. Bayesian Inference of Equation of State Pressures

Carolyn A. Raithel, Feryal Özel, Dimitrios Psaltis

Research output: Contribution to journalArticle

30 Scopus citations

Abstract

One of the key goals of observing neutron stars is to infer the equation of state (EoS) of the cold, ultradense matter in their interiors. Here, we present a Bayesian statistical method of inferring the pressures at five fixed densities, from a sample of mock neutron star masses and radii. We show that while five polytropic segments are needed for maximum flexibility in the absence of any prior knowledge of the EoS, regularizers are also necessary to ensure that simple underlying EoS are not over-parameterized. For ideal data with small measurement uncertainties, we show that the pressure at roughly twice the nuclear saturation density, Psat, can be inferred to within 0.3 dex for many realizations of potential sources of uncertainties. The pressures of more complicated EoS with significant phase transitions can also be inferred to within ∼30%. We also find that marginalizing the multi-dimensional parameter space of pressure to infer a massradius relation can lead to biases of nearly 1 km in radius, toward larger radii. Using the full, five-dimensional posterior likelihoods avoids this bias.

Original languageEnglish (US)
Article number156
JournalAstrophysical Journal
Volume844
Issue number2
DOIs
StatePublished - Aug 1 2017

Keywords

  • equation of state
  • stars: interiors
  • stars: neutron

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

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