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Lack of knowledge about the detailed many-particle motion on the microscopic scale is a key issue in any theoretical description of a macroscopic experiment. For systems at or close to thermal equilibrium, statistical mechanics provides a…

Statistical Mechanics · Physics 2016-03-03 Peter Reimann

Molecular property prediction is essential for drug discovery. In recent years, deep learning methods have been introduced to this area and achieved state-of-the-art performances. However, most of existing methods ignore the intrinsic…

Biomolecules · Quantitative Biology 2022-11-04 Yuancheng Sun , Yimeng Chen , Weizhi Ma , Wenhao Huang , Kang Liu , Zhiming Ma , Wei-Ying Ma , Yanyan Lan

Ring polymer molecular dynamics (RPMD) has proven to be an accurate approach for calculating thermal rate coefficients of various chemical reactions. For wider application of this methodology, efficient ways to generate the underlying…

Chemical Physics · Physics 2020-01-08 Ivan S. Novikov , Alexander V. Shapeev , Yury V. Suleimanov

The model quantum system of fermions in a one dimensional harmonic oscillator potential is investigated by a molecular dynamics method at constant temperature. Although in quantum mechanics the equipartition theorem cannot be used like in…

Statistical Mechanics · Physics 2015-06-25 J. Schnack

In this work, we introduce a novel approach for predicting thermodynamic properties of binary mixtures, which we call the similarity-based method (SBM). The method is based on quantifying the pairwise similarity of components, which we…

Chemical Physics · Physics 2025-02-20 Nicolas Hayer , Thomas Specht , Justus Arweiler , Dominik Gond , Hans Hasse , Fabian Jirasek

Physics-informed machine learning (PIML) as a means of solving partial differential equations (PDE) has garnered much attention in the Computational Science and Engineering (CS&E) world. This topic encompasses a broad array of methods and…

Machine Learning · Computer Science 2024-09-05 Michael Penwarden , Houman Owhadi , Robert M. Kirby

We propose a methodology for fully automated calculation of thermal rate coefficients of gas phase chemical reactions, which is based on combining the ring polymer molecular dynamics (RPMD) with the machine-learning interatomic potentials…

Chemical Physics · Physics 2018-12-26 Ivan S. Novikov , Yury V. Suleimanov , Alexander V. Shapeev

Constant potential method molecular dynamics simulation (CPM MD) enables the accurate modelling of atomistic electrode charges when studying the electrode-electrolyte interface at the nanoscale. Here we extend the theoretical framework of…

Materials Science · Physics 2023-05-26 Shern Ren Tee , Debra J. Searles

Modeling many-body quantum systems with strong interactions is one of the core challenges of modern physics. A range of methods has been developed to approach this task, each with its own idiosyncrasies, approximations, and realm of…

Statistical Mechanics · Physics 2018-11-21 Brett Larder , Dirk Gericke , Scott Richardson , Paul Mabey , Thomas White , Gianluca Gregori

Exposing a molecule to intense light pulses may bring this molecule to a nonstationary quantum state, thus launching correlated dynamics of electronic and nuclear subsystems. Although much had been achieved in the understanding of…

Chemical Physics · Physics 2024-04-11 Nikolay V. Golubev , Jiří Vaníček

Molecular dynamics with the stochastic process provides a convenient way to compute structural and thermodynamic properties of chemical, biological, and materials systems. It is demonstrated that the virtual dynamics case that we proposed…

Statistical Mechanics · Physics 2018-03-20 Dezhang Li , Zifei Chen , Zhijun Zhang , Jian Liu

Micro-Electro-Mechanical Systems (MEMS) normally have fixed or moving structures with cross-sections of the order of microns ($\mu m$) and lengths of the order of tens or hundreds of microns. These structures are often plates or array of…

Computational Physics · Physics 2007-05-23 N. Majumdar , S. Mukhopadhyay

Comparing probability distributions is a core challenge across the natural, social, and computational sciences. Existing methods, such as Maximum Mean Discrepancy (MMD), struggle in high-dimensional and non-compact domains. Here we…

Machine Learning · Statistics 2025-09-09 Logan S. McCarty

The algebraic reformulation of molecular Quantum Electrodynamics (mQED) at finite temperatures is applied to Nuclear Magnetic Resonance (NMR) in order to provide a foundation for the reconstruction of much more detailed molecular…

Quantum Physics · Physics 2020-09-25 Kolja Them

Potential energy landscape (PEL) is essential to determine phase stability, reaction path, and other important physical as well as chemical properties. Whereas given PEL can reasonably determine the properties in thermodynamically…

Disordered Systems and Neural Networks · Physics 2018-10-17 Koretaka Yuge

Precision physics aims to use atoms and molecules to test and develop the fundamental theory of matter, possibly beyond the Standard Model. Most of the atomic and molecular phenomena are described by the QED (quantum electrodynamics) sector…

Chemical Physics · Physics 2024-06-11 Ádám Nonn , Ádám Margócsy , Edit Mátyus

In order to predict the potential energy surface (PES) from measured structure in equilibrium state, one should typically perform trial-and-error statistical thermodynamic simulation with assumed multibody interactions. Very recently, we…

Disordered Systems and Neural Networks · Physics 2017-07-11 Koretaka Yuge

We present extensive new \emph{ab initio} path integral Monte Carlo (PIMC) simulations of the uniform electron gas (UEG) in the high-temperature regime, $8\leq\theta=k_\textnormal{B}T/E_\textnormal{F}\leq128$. This allows us to study the…

Developing new methods for the accurate and efficient calculations of real-time quantum correlation functions is deemed one of the most challenging problems of modern condensed matter theory. Many popular methods, such as centroid molecular…

Chemical Physics · Physics 2025-10-16 Nathan London , Mohammad R. Momeni

Symmetries play a pivotal role in our understanding of the properties of quantum many-body systems. While there are theorems and a well-established toolbox for systems in thermal equilibrium, much less is known about the role of symmetries…