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Related papers: Nuclear liquid-gas phase transition with machine l…

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Based on deep neural networks (DNNs), deep learning has been successfully applied to many problems, but its mechanism is still not well understood -- especially the reason why over-parametrized DNNs can generalize. A recent statistical…

Disordered Systems and Neural Networks · Physics 2025-06-10 Gang Huang , Lai Shun Chan , Hajime Yoshino , Ge Zhang , Yuliang Jin

Two roads are presently being followed in order to establish the existence of a liquid-gas phase transition in finite nuclear systems from nuclear reactions at high energy. The clean experiment of observing the thermodynamic properties of a…

Nuclear Experiment · Physics 2009-11-10 W. Trautmann

We simulate high-pressure hydrogen in its liquid phase close to molecular dissociation using a machine-learned interatomic potential. The model is trained with density functional theory (DFT) forces and energies, with the…

Statistical Mechanics · Physics 2024-12-20 Mathieu Istas , Scott Jensen , Yubo Yang , Markus Holzmann , Carlo Pierleoni , David M. Ceperley

Recently, machine learning has emerged as an alternative, powerful approach for predicting quantum-mechanical properties of molecules and solids. Here, using kernel ridge regression and atomic fingerprints representing local environments of…

Materials Science · Physics 2018-03-08 Teppei Suzuki , Ryo Tamura , Tsuyoshi Miyazaki

A relativistic mean-field model of nuclear matter with arbitrary proton fraction is studied at finite temperature. An analysis is performed of the liquid-gas phase transition in a system with two conserved charges (baryon number and…

Nuclear Theory · Physics 2008-11-26 Horst Mueller , Brian D. Serot

The equation of state (EOS) of finite nuclei is constructed in the relativistic Thomas-Fermi theory using the non-linear $\sigma-\omega -\rho$ model. The caloric curves are calculated by confining the nuclei in the freeze-out volume taken…

Nuclear Theory · Physics 2009-11-06 Tapas Sil , B. K. Agrawal , J. N. De , S. K. Samaddar

The liquid-gas phase transition in hot asymmetric nuclear matter is investigated within relativistic mean-field model using the density dependence of nuclear symmetry energy constrained from the measured neutron skin thickness of finite…

Nuclear Theory · Physics 2014-11-20 Bharat K. Sharma , Subrata Pal

We present first-principle predictions for the liquid-gas phase transition in symmetric nuclear matter employing both two- and three-nucleon chiral interactions. Our discussion focuses on the sources of systematic errors in microscopic…

Nuclear Theory · Physics 2018-08-31 Arianna Carbone , Artur Polls , Arnau Rios

More than two decades ago, the van der Waals behavior of the nucleon - nucleon force inspired the idea of a liquid-gas phase transition in nuclear matter. Heavy-ion reactions at relativistic energies offer the unique possibility for…

Nuclear Experiment · Physics 2007-05-23 J. Pochodzalla , ALADIN collaboration

Based on recent studies of the temperature dependence of the energy and specific heat of liquid nuclear matter, a phase transition is suggested at a temperature $\sim .8$ MeV. We apply Landau Ginzburg theory to this transition and determine…

Nuclear Theory · Physics 2009-10-30 R. A. Ritchie , H. G. Miller , F. C. Khanna

An exact analytical solution of the statistical multifragmentation model is found in thermodynamic limit. The model exhibits a 1-st order phase transition of the liquid-gas type. The mixed phase region of the phase diagram, where the gas of…

Nuclear Theory · Physics 2009-11-06 K. A. Bugaev , M. I. Gorenstein , I. N. Mishustin , W. Greiner

Detection of phase transitions is a critical task in statistical physics, traditionally pursued through analytic methods and direct numerical simulations. Recently, machine-learning techniques have emerged as promising tools in this…

Statistical Mechanics · Physics 2025-02-19 Burak Çivitcioğlu , Rudolf A. Römer , Andreas Honecker

We propose a systematic methodology to identify the topological phase transition through a self-supervised machine learning model, which is trained to correlate system parameters to the non-local observables in time-of-flight experiments of…

Quantum Gases · Physics 2021-09-01 Chi-Ting Ho , Daw-Wei Wang

In this talk I discuss three main topics concerning the theoretical description and observable signatures of possible phase transitions in nuclear collisions. The first one is related to the multifragmentation of thermalized sources and its…

Nuclear Theory · Physics 2010-12-13 I. N. Mishustin

It is commonly accepted that strongly interacting matter has several phase transitions in different domains of temperature and baryon density. In this contribution I discuss two most popular phase transitions which in principle can be…

High Energy Physics - Phenomenology · Physics 2009-11-11 I. N. Mishustin

In recent years, machine learning has emerged as a powerful computational tool and novel problem-solving perspective for physics, offering new avenues for studying strongly interacting QCD matter properties under extreme conditions. This…

High Energy Physics - Phenomenology · Physics 2023-12-05 Kai Zhou , Lingxiao Wang , Long-Gang Pang , Shuzhe Shi

We study the latent heat of the liquid-gas phase transition in symmetric nuclear matter using self-consistent mean-field calculations with a few Skyrme forces. The temperature dependence of the latent heat is rather independent of the…

Nuclear Theory · Physics 2011-05-05 Arianna Carbone , Artur Polls , Arnau Rios , Isaac Vidaña

An analysis is performed of the liquid-gas phase transition of nuclear matter obtained from different versions of scalar derivate coupling suggested by Zimanyi and Moszkowski (ZM) and the results are compared with those obtained from the…

Nuclear Theory · Physics 2016-09-08 M. Malheiro , A. Delfino , C. T. Coelho

In this paper, we investigate the liquid gas phase transition for the spin polarized nuclear matter. Applying the lowest order constrained variational (LOCV) method, and using two microscopic potentials, $AV_{18}$ and $UV_{14}$+TNI, we…

Nuclear Theory · Physics 2015-09-29 Z. Rezaei , M. Bigdeli , G. H. Bordbar

Predicting solid-solid phase transitions remains a long-standing challenge in materials science. Solid-solid transformations underpin a wide range of functional properties critical to energy conversion, information storage, and thermal…

Materials Science · Physics 2025-06-03 Cibrán López , Joshua Ojih , Ming Hu , Josep Lluis Tamarit , Edgardo Saucedo , Claudio Cazorla