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Related papers: Coarse-Graining Can Beat the Rotating Wave Approxi…

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Inspired by holographic Wilsonian renormalization, we consider coarse graining a quantum system divided between short distance and long distance degrees of freedom, coupled via the Hamiltonian. Observations using purely long distance…

High Energy Physics - Theory · Physics 2018-08-01 Cesar Agon , Vijay Balasubramanian , Skyler Kasko , Albion Lawrence

Molecular dynamics simulations provide theoretical insight into the microscopic behavior of materials in condensed phase and, as a predictive tool, enable computational design of new compounds. However, because of the large temporal and…

Chemical Physics · Physics 2020-06-18 Wujie Wang , Rafael Gómez-Bombarelli

Coarse-grained molecular dynamics often sacrifices accuracy and transferability for computational efficiency, but the use of machine learned potentials is helping coarse-grained models attain performance on par with atomistic molecular…

Chemical Physics · Physics 2026-02-17 Abigail Park , Shriram Chennakesavalu , Grant M. Rotskoff

We demonstrate how the dynamical coarse-graining approach can be systematically extended to higher orders in the coupling between system and reservoir. Up to second order in the coupling constant we explicitly show that dynamical…

Quantum Physics · Physics 2009-03-23 Gernot Schaller , Philipp Zedler , Tobias Brandes

Coarse-graining is central to reducing dimensionality in molecular dynamics, and is typically characterized by a mapping which projects the full state of the system to a smaller class of variables. While extensive literature has been…

Probability · Mathematics 2020-01-08 Frédéric Legoll , Tony Lelièvre , Upanshu Sharma

Structural and thermodynamic consistency of coarse-graining models across multiple length scales is essential for the predictive role of multi-scale modeling and molecular dynamic simulations that use mesoscale descriptions. Our approach is…

Soft Condensed Matter · Physics 2014-07-04 J. McCarty , A. J. Clark , J. Copperman , M. G. Guenza

We apply the functional Renormalisation Group (fRG) to study relaxation in a stochastic process governed by an overdamped Langevin equation with one degree of freedom, exploiting the connection with supersymmetric quantum mechanics in…

Statistical Mechanics · Physics 2023-06-06 Ashley Wilkins , Gerasimos Rigopoulos , Enrico Masoero

Coarse graining enables the investigation of molecular dynamics for larger systems and at longer timescales than is possible at atomic resolution. However, a coarse graining model must be formulated such that the conclusions we draw from it…

We study particle and energy transport in an open quantum system consisting of a three harmonic oscillator chain coupled to thermal baths at different temperatures placed at the ends of the chain. We consider the exact dynamics of the open…

Quantum Physics · Physics 2025-10-28 Melika Babakan , Fabio Benatti , Laleh Memarzadeh

Active matter, responsive ("smart") materials and materials under time-dependent load are systems out of thermal equilibrium. To construct coarse-grained models for such systems, one needs to integrate out a distribution of microstates that…

Statistical Mechanics · Physics 2022-05-17 Tanja Schilling

We present a real-space formulation for coarse-graining Kohn-Sham Density Functional Theory that significantly speeds up the analysis of material defects without appreciable loss of accuracy. The approximation scheme consists of two steps.…

Computational Physics · Physics 2015-06-11 Phanish Suryanarayana , Kaushik Bhattacharya , Michael Ortiz

Constructing atom-resolved states from low-resolution data is of practical importance in many areas of science and engineering. This problem is addressed in this paper in the context of multiscale factorization methods for molecular…

Computational Physics · Physics 2016-04-14 Andrew Abi Mansour , Peter J. Ortoleva

Master equations are a useful tool to describe the evolution of open quantum systems. In order to characterize the mathematical features and the physical origin of the dynamics, it is often useful to consider different kinds of master…

Quantum Physics · Physics 2020-08-24 Nina Megier , Andrea Smirne , Bassano Vacchini

Coarse-grained (CG) models provide an effective route to reducing the complexity of molecular simulations (MD), but conventional approaches depend heavily on long all-atom MD trajectories to adequately sample configurational space. This…

Chemical Physics · Physics 2025-10-28 Maximilian Stupp , P. S. Koutsourelakis

We derive the stochastic equations and consider the non-Markovian dynamics of a system of multiple two-level atoms in a common quantum field. We make only the dipole approximation for the atoms and assume weak atom-field interactions. From…

Quantum Physics · Physics 2015-03-17 C. H. Fleming , N. I. Cummings , Charis Anastopoulos , B. L. Hu

For many complex dynamical systems, a separation of scales prevails between the (microscopic) level of description of the available model, and the (macroscopic) level at which one would like to observe and analyze the system. For this type…

Computational Physics · Physics 2007-05-23 Giovanni Samaey , Wim Vanroose , Dirk Roose , Ioannis G Kevrekidis

We introduce an RG-inspired coarse-graining for extracting the collective features of data. The key to successful coarse-graining lies in finding appropriate pairs of data sets. We coarse-grain the two closest data in a regular real-space…

Data Analysis, Statistics and Probability · Physics 2023-07-19 Jonathan Landy , Tsvi Tlusty , YeongKyu Lee , YongSeok Jho

We report on a molecular dynamics investigation of the wetting properties of graphitic surfaces by various solutions at concentrations 1-8 wt% of commercially available non-ionic surfactants with long hydrophilic chains, linear or T-shaped.…

Chemical Physics · Physics 2012-09-12 Danilo Sergi , Giulio Scocchi , Alberto Ortona

Dynamical systems with large state-spaces are often expensive to thoroughly explore experimentally. Coarse-graining methods aim to define simpler systems which are more amenable to analysis and exploration; most current methods, however,…

Systems and Control · Computer Science 2016-11-01 Michalis Michaelides , Dimitrios Milios , Jane Hillston , Guido Sanguinetti

Stochastic modelling of complex systems plays an essential, yet often computationally intensive role across the quantitative sciences. Recent advances in quantum information processing have elucidated the potential for quantum simulators to…

Quantum Physics · Physics 2021-06-22 Thomas J. Elliott