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Finite-temperature Equations of State for Neutron Star Mergers

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arxiv 1906.08440 v2 pith:XNPU3M6J submitted 2019-06-20 astro-ph.HE hep-phhep-thnucl-th

classification astro-ph.HEhep-phhep-thnucl-th
keywords equationsstatematterneutronstardensityfamilygravitational
verification ladder T0 review T1 audit T2 compute T3 formal
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The detection of gravitational waves from a neutron star merger has opened up the possibility of detecting the presence or creation of deconfined quark matter using the gravitational wave signal. To investigate this possibility, we construct a family of neutron star matter equations of state at nonzero density and temperature by combining state-of-the-art nuclear matter equations of state with holographic equations of state for strongly interacting quark matter. The emerging picture consistently points toward a strong first order deconfinement transition, with a temperature-dependent critical density and latent heat that we quantitatively examine. Recent neutron star mass measurements are further used to discriminate between the different equations of state obtained, leaving a tightly constrained family of preferred equations of state.

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Cited by 3 Pith papers

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

  1. Quark flavors in hot and dense holographic QCD: setup and comparison to data

    hep-ph 2025-07 conditional novelty 7.0 of 10

    A 2+1 flavor holographic QCD model fitted to lattice thermodynamics predicts a smoother nuclear-to-quark matter transition with lower latent heat than earlier V-QCD models.

  2. Locating the QCD critical point with neutron-star observations

    astro-ph.HE 2025-06 conditional novelty 6.0 of 10

    Bayesian analysis of a hybrid holographic EOS with neutron-star constraints locates the QCD critical endpoint at μ≈626 MeV and T≈119 MeV and predicts a strong first-order deconfinement transition at zero temperature.

  3. TTE-CAM: Self-Explainable Class Activation Maps for Pretrained Black-Box CNNs

    cs.CV 2026-03 unverdicted novelty 5.0 of 10

    A test-time convolution-head replacement converts pretrained CNNs into self-explainable models that keep black-box accuracy and produce faithful class activation maps.

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