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Simulations of relativistic heavy-ion collisions within the three-fluid model employing a purely hadronic equation of state (EoS) and two versions of the EoS involving deconfinement transition are presented. The latter are an EoS with the…

Nuclear Theory · Physics 2014-01-23 Yu. B. Ivanov

Power flow analysis plays a critical role in the control and operation of power systems. The high computational burden of traditional solution methods led to a shift towards data-driven approaches, exploiting the availability of digital…

Systems and Control · Electrical Eng. & Systems 2024-09-17 Victor Eeckhout , Hossein Fani , Md Umar Hashmi , Geert Deconinck

We perform a Bayesian inference of the dense-matter equation of state (EOS) within a unified framework that incorporates hadronic matter, quark matter, and a smooth hadron-to-quark crossover. The EOS is constrained using physical…

Nuclear Theory · Physics 2026-05-11 Xavier Grundler , Bao-An Li

This report describes a new equation of state (EOS) for helium. The PANDA code was used to construct separate EOS tables for the solid and fluid phases. The solid and fluid EOS were then assembled into a multiphase EOS table using the PANDA…

Chemical Physics · Physics 2013-06-28 Gerald I. Kerley

A modified version of the density dependent covariant density functional model proposed in [T. Malik, M. Ferreira, B. K. Agrawal and C. Provid\^encia, ApJ 930, 17 (2022)] is employed in a Bayesian analysis to determine the equation of state…

Nuclear Theory · Physics 2023-04-12 Mikhail V. Beznogov , Adriana R. Raduta

High-fidelity shock experiments were performed on copper powders with controlled porosity via improved target fabrication and assembly. Optical velocimetry and multi-channel pyrometry were used to obtain Hugoniot data, isentropic release…

Applied Physics · Physics 2025-11-25 Yufeng Wang , Long Hao , Lixin Liu , Fengchao Wu , Shijia Ye , Yuanchao Gan , Yi Sun , Hua Y. Geng

We introduce a general method to merge multidimensional equations of state (EoSs) by combining them in a two-fluid equilibrium statistical mixture in the grand canonical ensemble. The merged grand potential density $\omega$ is built…

Context. A unified equation of state (EoS) should describe the crust and the core of a neutron star using the same physical model. The Brussels-Montreal group has recently derived a family of such EoSs based on the nuclear energy-density…

Solar and Stellar Astrophysics · Physics 2015-05-14 A. Y. Potekhin , A. F. Fantina , N. Chamel , J. M. Pearson , S. Goriely

We study characteristics of the relativistic equation of state (EOS) for collapse-driven supernovae, which is derived by relativistic nuclear many body theory. Recently the relativistic EOS table has become available as a new complete set…

Nuclear Theory · Physics 2015-06-26 K. Sumiyoshi , H. Suzuki , S. Yamada , H. Toki

The equation of state (EOS) of dense matter is an essential ingredient for numerical simulations of core-collapse supernovae and neutron star mergers. The properties of matter near and above nuclear saturation density are uncertain, which…

High Energy Astrophysical Phenomena · Physics 2017-12-13 Andre da Silva Schneider , Luke F. Roberts , Christian D. Ott

Modeling the internal structure of self-gravitating solid and liquid bodies presents a challenge, as existing approaches are often limited to either overly simplistic constant-density approximations or more complex numerical equations of…

Earth and Planetary Astrophysics · Physics 2025-07-31 Bartosz Żbik , Andrzej Odrzywołek

This work deals with the modeling of plasmas, which are charged-particle fluids. Thanks to machine leaning, we construct a closure for the one-dimensional Euler-Poisson system valid for a wide range of collision regimes. This closure, based…

Numerical Analysis · Mathematics 2020-11-13 Léo Bois , Emmanuel Franck , Laurent Navoret , Vincent Vigon

We construct the equation of state (EOS) of dense matter covering a wide range of temperature, proton fraction, and density for the use of core-collapse supernova simulations. The study is based on the relativistic mean-field (RMF) theory,…

High Energy Astrophysical Phenomena · Physics 2012-03-26 H. Shen , H. Toki , K. Oyamatsu , K. Sumiyoshi

In fluid physics, data-driven models to enhance or accelerate solution methods are becoming increasingly popular for many application domains, such as alternatives to turbulence closures, system surrogates, or for new physics discovery. In…

The combination of high-dimensionality and disparity of time scales encountered in many problems in computational physics has motivated the development of coarse-grained (CG) models. In this paper, we advocate the paradigm of data-driven…

Computational Physics · Physics 2018-03-05 L. Felsberger , P. S. Koutsourelakis

Observations of neutron stars (NSs) by the LIGO-Virgo and NICER collaborations have provided reasonably precise measurements of their various macroscopic properties. In this paper, we employ a Bayesian framework to combine them and place…

High Energy Astrophysical Phenomena · Physics 2021-05-26 Bhaskar Biswas , Prasanta Char , Rana Nandi , Sukanta Bose

Neutron star observables like masses, radii, and tidal deformability are direct probes to the dense matter equation of state~(EoS). A novel deep learning method that optimizes an EoS in the automatic differentiation framework of solving…

High Energy Astrophysical Phenomena · Physics 2023-05-03 Shriya Soma , Lingxiao Wang , Shuzhe Shi , Horst Stöcker , Kai Zhou

The Van der Waals equation (VdW-EoS) is a prototype equation of state for realistic systems, because it contains the excluded volume and the particle interactions. Additionally, the simulated annealing (and the similar simulated…

Soft Condensed Matter · Physics 2016-09-30 Peter Friedel

Observations of gravitational-wave signals from binary neutron-star mergers, like GW170817, can be used to constrain the neutron-star equation of state (EoS). One method involves modeling the EoS and measuring the model parameters through…

General Relativity and Quantum Cosmology · Physics 2019-01-09 Matthew F. Carney , Leslie E. Wade , Burke S. Irwin

We discuss deep learning inference for the neutron star equation of state (EoS) using the real observational data of the mass and the radius. We make a quantitative comparison between the conventional polynomial regression and the neural…

Nuclear Theory · Physics 2021-06-14 Yuki Fujimoto , Kenji Fukushima , Koichi Murase
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