2023
DOI: 10.1007/jhep06(2023)002
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Bayesian uncertainty quantification of perturbative QCD input to the neutron-star equation of state

Abstract: The equation of state of neutron-star cores can be constrained by requiring a consistent connection to the perturbative Quantum Chromodynamics (QCD) calculations at high densities. The constraining power of the QCD input depends on uncertainties from missing higher-order terms, the choice of the unphysical renormalization scale, and the reference density where QCD calculations are performed. Within a Bayesian approach, we discuss the convergence of the perturbative QCD series, quantify its uncertainties at hig… Show more

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Cited by 14 publications
(2 citation statements)
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References 78 publications
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“…The pressure of cold and dense massless QM in beta equilibrium [54]. Shown are the NLO (blue band), NNLO (yellow), and NNNLO (green) perturbative orders, of which the last one is new and contains one single undetermined coefficient c 0 set to a value determined by a Bayesian estimation performed in [54] (see also [77]).…”
Section: Discussionmentioning
confidence: 99%
“…The pressure of cold and dense massless QM in beta equilibrium [54]. Shown are the NLO (blue band), NNLO (yellow), and NNNLO (green) perturbative orders, of which the last one is new and contains one single undetermined coefficient c 0 set to a value determined by a Bayesian estimation performed in [54] (see also [77]).…”
Section: Discussionmentioning
confidence: 99%
“…At the same time, a growing number of recent works have explored the possibility of building very large sets of EOSs that satisfy all known theoretical and observational constraints and cover the physically allowed space of EOSs (Landry & Essick 2019;Annala et al 2020) and of related quantities, such as the sound speed (Altiparmak et al 2022;Gorda et al 2023a; or the conformal anomaly (Annala et al 2023;Brandes et al 2023;Marczenko et al 2023). These EOSs are built using either generic piecewise polytropes (see, e.g., Read et al 2009;Kurkela et al 2014;Lattimer & Steiner 2014;Tews et al 2018aTews et al , 2018bMost et al 2018;Steiner et al 2018), a parameterization of the sound speed (see, e.g., Annala et al 2020;Altiparmak et al 2022; or nonparametric Gaussian process regression (see, e.g., Landry & Essick 2019;Gorda et al 2023aGorda et al , 2023b.…”
Section: Introductionmentioning
confidence: 99%