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Phase Transition Phenomenology with Nonparametric Representations of the Neutron Star Equation of State

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arxiv 2305.07411 v2 pith:3SY7JOYC submitted 2023-05-12 astro-ph.HE gr-qcnucl-exnucl-th

classification astro-ph.HEgr-qcnucl-exnucl-th
keywords phasetransitionsequationstateneutronobservationsmodelswill
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abstract

Astrophysical observations of neutron stars probe the structure of dense nuclear matter and have the potential to reveal phase transitions at high densities. Most recent analyses are based on parametrized models of the equation of state with a finite number of parameters and occasionally include extra parameters intended to capture phase transition phenomenology. However, such models restrict the types of behavior allowed and may not match the true equation of state. We introduce a complementary approach that extracts phase transitions directly from the equation of state without relying on, and thus being restricted by, an underlying parametrization. We then constrain the presence of phase transitions in neutron stars with astrophysical data. Current pulsar mass, tidal deformability, and mass-radius measurements disfavor only the strongest of possible phase transitions (latent energy per particle $\gtrsim 100\,\mathrm{MeV}$). Weaker phase transitions are consistent with observations. We further investigate the prospects for measuring phase transitions with future gravitational-wave observations and find that catalogs of \result{$O(100)$} events will (at best) yield Bayes factors of $\sim 10:1$ in favor of phase transitions even when the true equation of state contains very strong phase transitions. Our results reinforce the idea that neutron star observations will primarily constrain trends in macroscopic properties rather than detailed microscopic behavior. Fine-tuned equation of state models will likely remain unconstrained in the near future.

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Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Gaussian Process framework for constraining the nuclear equation of state from microscopic calculations with correlated uncertainties

    nucl-th 2026-08 conditional novelty 6.0 of 10

    GPDiff fits a hierarchical Gaussian process to microscopic asymmetric-matter energies and propagates correlated uncertainties to EOS parameters and neutron-star matter properties.

  2. Towards constraining QCD phase transitions in neutron star interiors: Bayesian Inference with TOV linear response analysis

    nucl-th 2025-01 conditional novelty 6.0 of 10

    A Bayesian framework with analytical TOV linear-response gradients and a neural-network equation of state reconstructs neutron star EoSs and constrains first-order phase transition parameters from simulated mass-radius data.

  3. Probing Neutron Star Interiors and the Properties of Cold Ultra-dense Matter with the SKAO

    astro-ph.HE 2026-07 accept novelty 3.5 of 10

    SKAO's sensitivity, surveys and sub-arraying will deliver tighter NS mass, MoI, spin, glitch and precession constraints that, with X-ray and GW data, probe cold ultra-dense matter.

  4. Toward a Unified Understanding of the Dense Matter Equation of State

    nucl-th 2025-11 conditional novelty 2.0 of 10

    A review of three Bayesian/computational frameworks for combining heavy-ion and astrophysical constraints on the dense-matter equation of state, plus a proposed unified integration workflow.

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