GPDiff fits a hierarchical Gaussian process to microscopic asymmetric-matter energies and propagates correlated uncertainties to EOS parameters and neutron-star matter properties.
Assessing equation of state-independent relations for neutron stars with nonparametric models
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abstract
Relations between neutron star properties that do not depend on the nuclear equation of state offer insights on neutron star physics and have practical applications in data analysis. Such relations are obtained by fitting to a range of phenomenological or nuclear physics equation of state models, each of which may have varying degrees of accuracy. In this study we revisit commonly-used relations and re-assess them with a very flexible set of phenomenological nonparametric equation of state models that are based on Gaussian Processes. Our models correspond to two sets: equations of state which mimic hadronic models, and equations of state with rapidly changing behavior that resemble phase transitions. We quantify the accuracy of relations under both sets and discuss their applicability with respect to expected upcoming statistical uncertainties of astrophysical observations. We further propose a goodness-of-fit metric which provides an estimate for the systematic error introduced by using the relation to model a certain equation-of-state set. Overall, the nonparametric distribution is more poorly fit with existing relations, with the I-Love-Q relations retaining the highest degree of universality. Fits degrade for relations involving the tidal deformability, such as the Binary-Love and compactness-Love relations, and when introducing phase transition phenomenology. For most relations, systematic errors are comparable to current statistical uncertainties under the nonparametric equation of state distributions.
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A Gaussian Process framework for constraining the nuclear equation of state from microscopic calculations with correlated uncertainties
GPDiff fits a hierarchical Gaussian process to microscopic asymmetric-matter energies and propagates correlated uncertainties to EOS parameters and neutron-star matter properties.