2022
DOI: 10.1103/physrevd.105.043016
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Implicit correlations within phenomenological parametric models of the neutron star equation of state

Abstract: The rapid increase in the number and precision of astrophysical probes of neutron stars in recent years allows for the inference of their equation of state. Observations target different macroscopic properties of neutron stars which vary from star to star, such as mass and radius, but the equation of state allows for a common description of all neutron stars. To connect these observations and infer the properties of dense matter and neutron stars simultaneously, models for the equation of state are introduced.… Show more

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Cited by 38 publications
(37 citation statements)
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References 81 publications
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“…The nonparametric model we use is deliberately constructed to emphasize flexibility in EoS morphology and impose few correlations between high and low densities besides those dictated by the physical requirements of causality and thermodynamic stability. The intra-density correlations introduced by different parametric and nonparametric EoS models will be investigated in quantitative detail in upcoming work [72].…”
Section: Discussionmentioning
confidence: 99%
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“…The nonparametric model we use is deliberately constructed to emphasize flexibility in EoS morphology and impose few correlations between high and low densities besides those dictated by the physical requirements of causality and thermodynamic stability. The intra-density correlations introduced by different parametric and nonparametric EoS models will be investigated in quantitative detail in upcoming work [72].…”
Section: Discussionmentioning
confidence: 99%
“…1 of [84]. This nonparametric approach offers two further advantages over more traditional parametric models [85][86][87]: it avoids (i) systematic errors and (ii) strong (and perhaps opaque) intra-density correlations [72] that arise from restricting the EoS to a specific functional form with finite parameters which will inevitably not match the correct EoS or prior information about it.…”
Section: B Nonparametric Eos Modelmentioning
confidence: 99%
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“…At the current state of investigations with a limited neutron star data base and correspondingly large uncertainties, it is still justified to use parametric functional forms as long as they are sufficiently general. In the future many more data are expected and a non-parametric description of the EoS in terms of a Gaussian Process [39,40,74,128] or neural network [129] will be useful.…”
Section: A General Priorsmentioning
confidence: 99%
“…Other methods for constructing phenomenological parametric EOSs exist, such as the spectral method (Lindblom & Indik 2014). Legred et al (2022) have shown that parametric EOSs can introduce correlations between the pressures at different densities that add artificial restrictions to the EOSs that can bias inference results, and show that nonparametric methods, such as the Gaussian process method (Landry & Essick 2019) do not suffer from this type of bias.…”
Section: Equations Of Statementioning
confidence: 99%