Related papers: Constraining Model Uncertainty in Plasma Equation-…
We study the equation of state (EOS) of nuclear matter as function of density. We expand the energy per particle (E/A) of symmetric infinite nuclear matter in powers of the density to take into account 2,3,. . .,N-body forces. New EOS are…
The isothermal compression of a dilute nucleonic gas invoking cluster degrees of freedom is studied in an equilibrium statistical model; this clusterized system is found to be more stable than the pure nucleonic system. The equation of…
The nuclear equation of state (EoS) at high densities and/or extreme isospin is one of the longstanding problems of nuclear physics. In the last years substantial progress has been made to constrain the EoS both, from the astrophysical side…
Core-collapse simulations of massive stars are performed using the equation of state (EOS) based on the microscopic variational calculation with realistic nuclear forces. The progenitor models with the initial masses of $15M_\odot$,…
We present a physics-informed Bayesian neural-network framework to infer neutron-star equations of state from theoretical priors and to propagate the associated uncertainties to stellar observables. Trained on a large and representative…
This paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphysics Object-Oriented Simulation Environment (MOOSE), an…
A new scheme for testing the nuclear matter (NM) equation of state (EoS) at high densities using constraints from compact star (CS) phenomenology is applied to neutron stars with a core of deconfined quark matter (QM). An acceptable EoS…
Accurate modeling of the neutron star crust is essential for interpreting multimessenger observations and constraining the nuclear equation of state (EoS). However, standard phenomenological EoS models often rely on heuristic extrapolations…
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…
Unreliable predictions can occur when using artificial intelligence (AI) systems with negative consequences for downstream applications, particularly when employed for decision-making. Conformal prediction provides a model-agnostic…
A new scheme for testing the nuclear matter (NM) equation of state (EoS) at high densities using constraints from compact star (CS) phenomenology is applied to neutron stars with a core of deconfined quark matter (QM). An acceptable EoS…
Bayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model…
We apply Bayesian approach to construct a large number of minimally constrained equations of state (EOSs) and study their correlations with a few selected properties of a neutron star (NS). Our set of minimal constraints includes a few…
We propose a new analytical form of the quark-gluon plasma equation of state (EoS). This new EoS satisfies all qualitative features observed in the lattice QCD calculations and gives a good quantitative description of the lattice results in…
In this paper we apply the equation of state (EOS) of QCD at finite chemical potential and zero temperature proposed in H. S. Zong and W. M. Sun [Int. J. Mod. Phys. {\bf A23}, 3591 (2008)] to the study of properties of quark star. This EOS…
The study of the nuclear equation-of-state (EoS) is a one of the primary goals of experimental and theoretical heavy-ion physics. The comparison of recent high statistics data from the STAR Collaboration with transport models provides a…
Wide range equation of state (EOS) for liquid hydrogen is ultimately built by combining two kinds of density functional theory (DFT) molecular dynamics simulations, namely, first-principles molecular dynamics simulations and orbital-free…
In this work, we discuss the dense matter equation of state (EOS) for the extreme range of conditions encountered in neutron stars and their mergers. The calculation of the properties of such an EOS involves modeling different degrees of…
Fitting models to data is an important part of the practice of science. Advances in machine learning have made it possible to fit more -- and more complex -- models, but have also exacerbated a problem: when multiple models fit the data…
Impacts between planetary-sized bodies can explain the origin of satellites orbiting large ($R>500$~km) trans-Neptunian objects. Their water rich composition, along with the complex phase diagram of water, make it important to accurately…