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Related papers: The Lennard-Jones potential: when (not) to use it

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The aim of this work is to provide further insight into the qualitative behavior of mechanical systems that are well described by Lennard-Jones type interactions on an atomistic scale. By means of $\Gamma$-convergence techniques, we study…

Analysis of PDEs · Mathematics 2017-06-09 Mathias Schäffner , Anja Schlömerkemper

The folding vs. adsorption behaviour of a coarse-grained off-lattice protein model near an attractive surface is presented within the frame of a Multicanonical Monte Carlo simulations. In the polymer-surface model, the Lennard-Jones…

Soft Condensed Matter · Physics 2015-12-23 Handan Arkin , Hakan Alaboz

A class of Polyakov-loop-modified Nambu--Jona-Lasinio (PNJL) models have been used to support a conjecture that numerical simulations of lattice-regularized quantum chromodynamics (QCD) defined with a chiral chemical potential can provide…

We generalize previous approach of Khrapak and Morfill [J. Chem. Phys. {\bf 134}, 094108 (2011)] to construct simple and sufficiently accurate freezing and melting equations for the conventional Lennard-Jones (LJ) system to $n$-6 LJ…

Soft Condensed Matter · Physics 2016-06-07 Sergey A. Khrapak , Ning Ning

A well known, if little documented, problem in many molecular simulations of aqueous ionic solutions at finite concentrations is that unrealistic cation-cation associations are frequently found. One might suspect a defect in the ion-ion…

Soft Condensed Matter · Physics 2012-07-16 Ph. A. Bopp , K. Ibuki

Machine learning (ML) enables the development of interatomic potentials that promise the accuracy of first principles methods while retaining the low cost and parallel efficiency of empirical potentials. While ML potentials traditionally…

The Polyakov loop extended Nambu--Jona-Lasinio (PNJL) model with imaginary chemical potential is studied. The model possesses the extended ${\mathbb Z}_{3}$ symmetry that QCD does. Quantities invariant under the extended ${\mathbb Z}_{3}$…

High Energy Physics - Phenomenology · Physics 2008-11-26 Yuji Sakai , Kouji Kashiwa , Hiroaki Kouno , Masanobu Yahiro

We discuss the isentropic trajectories on the QCD phase diagram in the temperature and the quark chemical potential plane using the Nambu--Jona-Lasinio model with the Polyakov loop coupling (PNJL model). We impose a constraint on the…

High Energy Physics - Phenomenology · Physics 2010-04-14 Kenji Fukushima

Latent class model (LCM), which is a finite mixture of different categorical distributions, is one of the most widely used models in statistics and machine learning fields. Because of its non-continuous nature and the flexibility in shape,…

Machine Learning · Statistics 2021-03-23 Hao Chen , Lanshan Han , Alvin Lim

Recent years have witnessed the fast development of machine learning potentials (MLPs) and their widespread applications in chemistry, physics, and material science. By fitting discrete ab initio data faithfully to continuous and…

Chemical Physics · Physics 2025-05-13 Junfan Xia , Yaolong Zhang , Bin Jiang

Past experimental observations of gas-liquid and gas-crystal coexistence in low-salinity suspensions of highly charged colloids have suggested the existence of like charge attraction. Evidence for this phenomenon was also observed in…

Soft Condensed Matter · Physics 2025-12-23 Thijs ter Rele , René van Roij , Marjolein Dijkstra

Effective interactions between charged particles dispersed in an electrolyte are most commonly modeled using the Derjaguin-Landau-Verwey-Overbeek (DLVO) potential, where the ions in the suspension are coarse-grained out at mean-field level.…

Soft Condensed Matter · Physics 2025-10-23 Thijs ter Rele , Gerardo Campos-Villalobos , René van Roij , Marjolein Dijkstra

Laser plasma accelerators have the potential to reduce the size of future linacs for high energy physics by more than an order of magnitude, due to their high gradient. Research is in progress at current facilities, including the BELLA…

Accelerator Physics · Physics 2013-10-01 C. G. R. Geddes , J. -L. Vay , C. B. Schroeder , E. Esarey , W. P. Leemans

In this paper we propose the creation of generic LSH families for the angular distance based on Johnson-Lindenstrauss projections. We show that feature hashing is a valid J-L projection and propose two new LSH families based on feature…

Data Structures and Algorithms · Computer Science 2017-05-03 Luis Argerich , Natalia Golmar

This paper explores the potential of Lagrangian duality for learning applications that feature complex constraints. Such constraints arise in many science and engineering domains, where the task amounts to learning optimization problems…

Machine Learning · Computer Science 2020-04-07 Ferdinando Fioretto , Pascal Van Hentenryck , Terrence WK Mak , Cuong Tran , Federico Baldo , Michele Lombardi

A potential between mesons is extracted from 4-point functions within lattice gauge theory taking 2+1 dimensional QED as an example. This theory possesses confinement and dynamical fermions. The resulting meson-meson potential has a…

High Energy Physics - Lattice · Physics 2009-10-28 H. R. Fiebig , O. Linsuain , H. Markum , K. Rabitsch

Sampling from generative models has become a crucial tool for applications like data synthesis and augmentation. Diffusion, Flow Matching and Continuous Normalising Flows have shown effectiveness across various modalities, and rely on…

Machine Learning · Statistics 2025-11-10 Erik Bodin , Alexandru Stere , Dragos D. Margineantu , Carl Henrik Ek , Henry Moss

The thermodynamic potential and thermal dependence of low lying mass spectra of scalars and pseudoscalars are evaluated in a generalized Nambu -- Jona-Lasinio model, which incorporates eight-quark interactions. These are necessary to…

High Energy Physics - Phenomenology · Physics 2009-11-13 B. Hiller , A. A. Osipov , J. Moreira , A. H. Blin

I review the status of the Complex Langevin method, which was invented to make simulations of models with complex action feasible. I discuss the mathematical justification of the procedure, as well as its limitations and open questions.…

High Energy Physics - Lattice · Physics 2018-04-18 Erhard Seiler

Machine learning (ML) has become widely used in the development of interatomic potentials for molecular dynamics simulations. However, most ML potentials are still much slower than classical interatomic potentials and are usually trained…

Materials Science · Physics 2024-08-29 Aslak Fellman , Jesper Byggmästar , Fredric Granberg , Kai Nordlund , Flyura Djurabekova