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We introduce and explore an approach for constructing force fields for small molecules, which combines intuitive low body order empirical force field terms with the concepts of data driven statistical fits of recent machine learned…

化学物理 · 物理学 2020-10-26 Alice Allen , Gábor Csányi , Geneviève Dusson , Christoph Ortner

In the field of pharmacokinetics and pharmacodynamics (PKPD) modeling, which plays a pivotal role in the drug development process, traditional models frequently encounter difficulties in fully encapsulating the complexities of drug…

定量方法 · 定量生物学 2024-09-23 Nazanin Ahmadi Daryakenari , Shupeng Wang , George Karniadakis

Force-matched water models provide a practical route from first-principles reference data to long classical and path-integral molecular simulations. Previous flexible four-site potentials in the spirit of q-TIP4P/F showed that fitting…

化学物理 · 物理学 2026-05-26 Jan Kessler , Thomas Spura , Kristof Karhan , Thomas D. Kühne

We present a new approach based on real time domain Feynman path integrals (RTPI) for electronic structure calculations and quantum dynamics, which includes correlations between particles exactly but within the numerical accuracy. We…

量子物理 · 物理学 2015-10-09 Ilkka Ruokosenmäki , Hosein Gholizade , Ilkka Kylänpää , Tapio T. Rantala

Dirac-delta distributions are often crucial components of the solid-fluid coupling operators in immersed solution methods for fluid-structure interaction (FSI) problems. This is certainly so for methods like the Immersed Boundary Method…

数值分析 · 数学 2013-02-06 Luca Heltai , Francesco Costanzo

The phase-integral method (PIM) is an asymptotic method of the geometrical optics or semi-classical type for solving approximately, but in many cases very accurately, a wide class of differential equations in physics. Unlike the related…

数学物理 · 物理学 2010-01-05 S. Yngve , B. Thidé

This paper introduces an interacting-particle optimization method tailored to possibly non-convex composite optimization problems, which arise widely in signal processing. The proposed method, \emph{ProxiCBO}, integrates consensus-based…

最优化与控制 · 数学 2026-04-20 Haoyu Zhang , Yanting Ma , Ruangrawee Kitichotkul , Joshua Rapp , Petros Boufounos

We have implemented a variant of the force gradient integrator proposed by Kennedy et.al. and are using it in our production 2+1 flavor DWF simulations with pion masses of 180 MeV in (4.5fm)3 volumes. We find modest speed-ups (\sim 20%)…

高能物理 - 格点 · 物理学 2011-12-05 Hantao Yin , Robert D. Mawhinney

Machine learning interatomic potentials (MLIPs) enable efficient modeling of molecular interactions with quantum mechanical (QM) accuracy. However, constructing robust and representative training datasets that capture subtle,…

化学物理 · 物理学 2026-01-28 Lejia Zeng , Xintong Zhang , Yuchan Pei , Lifeng Zhao , Lan Hua , Jincai Yang , Niu Huang

This paper invites the reader to experiment with an easy-to-use MATLAB implementation of Metropolis integrators for Molecular Dynamics (MD) simulation. These integrators are analysis-based, in the sense that they can rigorously simulate…

计算物理 · 物理学 2013-09-20 Nawaf Bou-Rabee

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…

Understanding how the complex intermolecular- and nano-structure present in organic semiconductor donor-acceptor blends impacts charge carrier motion, interactions, and recombination behavior is a critical fundamental issue with a…

材料科学 · 物理学 2016-06-08 Michael C. Heiber , Thuc-Quyen Nguyen , Carsten Deibel

We present quasi-exact ab initio path integral Monte Carlo (PIMC) results for the partial static density responses and local field factors of hydrogen in the warm dense matter regime, from solid density conditions to the strongly compressed…

Grand canonical Monte Carlo (GCMC) simulations are essential for screening metal-organic frameworks (MOFs) for gas adsorption, yet their accuracy is limited by underlying interatomic potentials. Universal machine-learned interatomic…

材料科学 · 物理学 2026-02-17 Connor W. Edwards , Fengxu Yang , Konstantin Stracke , Jack D. Evans

Path integrals for particles in curved spaces can be used to compute trace anomalies in quantum field theories, and more generally to study properties of quantum fields coupled to gravity in first quantization. While their construction in…

高能物理 - 理论 · 物理学 2017-04-26 Fiorenzo Bastianelli , Olindo Corradini , Edoardo Vassura

Molecular dynamics (MD)-based path sampling algorithms are a very important class of methods used to study the energetics and kinetics of rare (bio)molecular events. They sample the highly informative but highly unlikely reactive…

计算物理 · 物理学 2025-07-08 Nitin Malapally , Marta Devodier , Giulia Rossetti , Paolo Carloni , Davide Mandelli

Particle Markov Chain Monte Carlo (PMCMC) is a general computational approach to Bayesian inference for general state space models. Our article scales up PMCMC in terms of the number of observations and parameters by generating the…

统计方法学 · 统计学 2023-07-04 David Gunawan , Chris Carter , Robert Kohn

This paper deals with the numerical integration of Hamiltonian systems in which a stiff anharmonic potential causes highly oscillatory solution behavior with solution-dependent frequencies. The impulse method, which uses micro- and…

数值分析 · 数学 2014-07-23 Christian Lubich , Daniel Weiss

In this work the path integral formulation for rigid rotors, proposed by M\"user and Berne [Phys. Rev. Lett. {\bf 77}, 2638 (1996)], is described in detail. It is shown how this formulation can be used to perform Monte Carlo simulations of…

统计力学 · 物理学 2012-11-08 Eva G. Noya , Luis M. Sesé , Rafael Ramírez , Carl McBride , Maria M. Conde , Carlos Vega

We present a molecular simulation method to simultaneously find multiple transition pathways, and their associated free-energy profiles. The scheme extends path-metadynamics (PMD) [Phys. Rev. Lett. 109, 020601 (2012)] with multiple paths…

统计力学 · 物理学 2025-06-23 Alberto Pérez de Alba Ortíz , Bernd Ensing