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We discuss the structure of the equation of motion that governs nucleation processes at first order phase transitions. From the underlying microscopic dynamics of a nucleating system, we derive by means of a non-equilibrium projection…

Statistical Mechanics · Physics 2019-12-04 Anja Kuhnhold , Hugues Meyer , Graziano Amati , Philipp Pelagejcev , Tanja Schilling

Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying…

Quantum computing exploits fundamentally new models of computation based on quantum mechanical properties instead of classical physics, and it is believed that quantum computers are able to dramatically improve computational power for…

Understanding nuclear effects is essential for improving the sensitivity of neutrino oscillation measurements. Validating nuclear models solely through neutrino scattering data is challenging due to limited statistics and the broad energy…

High Energy Physics - Phenomenology · Physics 2025-02-25 Seisho Abe

Path-integral molecular dynamics (PIMD) simulations are crucial for accurately capturing nuclear quantum effects in materials. However, their computational intensity and reliance on multiple software packages often limit their applicability…

We present a novel application of the multi-modal, multi-level quantum complex exponential least squares (MM-QCELS) algorithm, a state-of-the-art, early fault-tolerant quantum phase estimation (QPE) technique, to the simulation and analysis…

Quantum Physics · Physics 2026-03-04 Antonio Marquez Romero , Josh J. M. Kirsopp , Giuseppe Buonaiuto , Michal Krompiec

Various condensed phases of water, spanning from the liquid state to multiple ice phases, have been systematically investigated under extreme conditions of pressure and temperature to delineate their stability boundaries. This study focuses…

Chemical Physics · Physics 2024-05-29 Carlos P. Herrero , Rafael Ramirez

Machine learning potentials have emerged as a means to enhance the accuracy of biomolecular simulations. However, their application is constrained by the significant computational cost arising from the vast number of parameters compared to…

The Direct Simulation Monte Carlo (DSMC) method is the gold standard for non-equilibrium rarefied gas dynamics, yet its computational cost can be prohibitive, especially for near-continuum regimes and high-fidelity \emph{ab initio}…

Computational Physics · Physics 2026-02-26 Ehsan Roohi , Ahmad Shoja-Sani , Stefan Stefanov

A classical computer simulating Schrodinger dynamics of a quantum system requires resources which scale exponentially with the size of the system, and is regarded as inefficient for such purposes. However, a quantum computer made up of a…

Quantum Physics · Physics 2015-06-16 Ravi Shankar , Swathi S. Hegde , T. S. Mahesh

Nuclear quantum effects play critical roles in a variety of molecular processes, especially in systems that contain hydrogen and other light nuclei, such as water. For water at ambient conditions, nuclear quantum effects are often…

Chemical Physics · Physics 2023-09-12 Richard C. Remsing

In this work, a path integral Car-Parrinello molecular dynamics simulation of liquid water is performed. It is found that the inclusion of nuclear quantum effects systematically improves the agreement of first principles simulations of…

Soft Condensed Matter · Physics 2009-11-13 Joseph A. Morrone , Roberto Car

We develop a new master equation as a unified description of the effects of both quantum noise (system-bath interaction) and classical noise on a system's dynamics, using a two-dimensional series expansion method. When quantum and classical…

Quantum Physics · Physics 2020-04-30 Li Yu

Structure and reaction studies with a method of antisymmetrized molecular dynamics (AMD) were reviewed. Applications of time-independent and time-dependent versions of the AMD were described. In applications of time-independent AMD to…

Nuclear Theory · Physics 2012-02-10 Yoshiko Kanada-En'yo , Masaaki Kimura , Akira Ono

Simulating spontaneous structural rearrangements in macromolecules with classical Molecular Dynamics (MD) is an outstanding challenge. Conventional supercomputers can access time intervals up to tens of $\mu$s, while many key events occur…

Biological Physics · Physics 2026-03-19 Danial Ghamari , Roberto Covino , Pietro Faccioli

Atomistic spin dynamics (ASD) is a standard tool to model the magnetization dynamics of a variety of materials. The fundamental dynamical model underlying ASD is entirely classical. In this paper, we present two approaches to effectively…

Materials Science · Physics 2024-07-01 Marco Berritta , Stefano Scali , Federico Cerisola , Janet Anders

Quantum computational chemistry holds great promise for simulating molecular systems more efficiently than classical methods by leveraging quantum bits to represent molecular wavefunctions. However, current implementations face significant…

Quantum Physics · Physics 2025-09-10 Weitang Li , Shi-Xin Zhang , Zirui Sheng , Cunxi Gong , Jianpeng Chen , Zhigang Shuai

Magneto-optical effect is a fundamental but broad concept in magnetic mediums. Here we propose a scheme for its quantum emulation using ultracold atoms. By representing the light-medium interaction in the quantum-emulation manner, the…

Quantum Gases · Physics 2022-02-17 Zhen Zheng , Z. D. Wang

Low energy nucleon dynamics in the effective field theory (EFT) of nuclear forces is investigated by using the formalism of the generalized quantum dynamics (GQD). This formalism is based on a generalized dynamical equation derived as the…

Nuclear Theory · Physics 2007-05-23 Renat Kh. Gainutdinov , Aigul A. Mutygullina

We describe a fast implementation of the quasi-centroid molecular dynamics (QCMD) method in which the quasi-centroid potential of mean force is approximated as a separable correction to the classical interaction potential. This correction…

Chemical Physics · Physics 2021-11-24 Theo Fletcher , Andrew Zhu , Joseph E. Lawrence , David E. Manolopoulos
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