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The Mori-Zwanzig formalism is applied to derive an equation for the evolution of linear observables of the overdamped Langevin equation. To illustrate the resulting equation and its use in deriving approximate models, a particular benchmark…

Dynamical Systems · Mathematics 2018-10-19 Thomas Hudson , Xingjie Helen Li

Brute-force simulations for dynamics on very large networks are quite expensive. While phenomenological treatments may capture some macroscopic properties, they often ignore important microscopic details. Fortunately, one may be only…

Physics and Society · Physics 2016-05-17 Chuansheng Shen , Hanshuang Chen , Zhonghuai Hou , Jürgen Kurths

We present an effective evolution equation for a coarse-grained distribution function of a long-range-interacting system preserving the symplectic structure of the non-collisional Boltzmann, or Vlasov, equation. We first derive a general…

Statistical Mechanics · Physics 2020-07-01 Guido Giachetti , Alessandro Santini , Lapo Casetti

We introduce a general framework for deriving effective dynamics from arbitrary time-dependent generators, based on a systematic operator cumulant expansion. Unlike traditional approaches, which typically assume periodic or adiabatic…

Mathematical Physics · Physics 2025-10-02 Leon Bello , Tal Rubin , Wentao Fan , Nathaniel Fisch , Hakan Türeci

From known phase diagram regions of different model Hamiltonians describing strongly correlated systems we deduced new domains of the ground state phase diagram of the same model by an unitary transformation. Different types of extended…

Strongly Correlated Electrons · Physics 2017-08-23 E Kovacs , Zs. Gulacsi

A data-driven ab initio generalized Langevin equation (AIGLE) approach is developed to learn and simulate high-dimensional, heterogeneous, coarse-grained conformational dynamics. Constrained by the fluctuation-dissipation theorem, the…

Biological Physics · Physics 2024-09-13 Pinchen Xie , Yunrui Qiu , Weinan E

A Hamiltonian formulation of generic many-particle systems with space-dependent balanced loss and gain coefficients is presented. It is shown that the balancing of loss and gain necessarily occurs in a pair-wise fashion. Further, using a…

Mathematical Physics · Physics 2019-08-30 Debdeep Sinha , Pijush K. Ghosh

Atomistic or ab-initio molecular dynamics simulations are widely used to predict thermodynamics and kinetics and relate them to molecular structure. A common approach to go beyond the time- and length-scales accessible with such…

Starting from the detailed catalytic mechanism of a biocatalyst we provide a coarse-graining procedure which, by construction, is thermodynamically consistent. This procedure provides stoichiometries, reaction fluxes (rate laws), and…

Statistical Mechanics · Physics 2018-04-27 Artur Wachtel , Riccardo Rao , Massimiliano Esposito

With the birth of quantum information science, many tools have been developed to deal with many-body quantum systems. Although a complete description of such systems is desirable, it will not always be possible to achieve this goal, as the…

Quantum Physics · Physics 2020-12-01 Cristhiano Duarte , Barbara Amaral , Marcelo Terra Cunha , Matthew Leifer

We investigate two different types of non-Markovian coarse-grained models extracted from a linear, non-equilibrium microscopic system, featuring a tagged particle coupled to underdamped oscillators. The first model is obtained by…

Statistical Mechanics · Physics 2023-10-06 Gerhard Jung

Multiscale phenomena which include several processes occuring simultaneously at different length scales and exchanging energy with each other, are widespread in magnetism. These phenomena often govern the magnetization reversal dynamics,…

Materials Science · Physics 2009-10-31 V. V. Dobrovitski , M. I. Katsnelson , B. N. Harmon

The optimization of the conversion of thermal energy into work and the minimization of dissipation for nano- and mesoscopic systems is a complex challenge because of the important role fluctuations play on the dynamics of small systems. We…

Quantum Physics · Physics 2025-09-24 Alberto Rolandi

Coarse-grained (CG) models are simplified representations of soft matter systems that are commonly employed to overcome size and time limitations in computational studies. Many approaches have been developed to construct and parametrise…

Statistical Mechanics · Physics 2022-09-27 Piero Luchi , Roberto Menichetti , Gianluca Lattanzi , Raffaello Potestio

Autonomous vehicles (AVs) enable more efficient and sustainable transportation systems. Ample studies have shown that controlling a small fraction of AVs can smooth traffic flow and mitigate traffic congestion. However, deploying AVs in…

Systems and Control · Electrical Eng. & Systems 2023-10-12 Sirui Li , Roy Dong , Cathy Wu

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems…

Machine Learning · Computer Science 2025-12-30 Quercus Hernandez , Max Win , Thomas C. O'Connor , Paulo E. Arratia , Nathaniel Trask

We analyze the dynamics of a two-level system subject to driving by large-amplitude external fields, focusing on the resonance properties in the case of driving around the region of avoided level crossing. In particular, we consider three…

Quantum Physics · Physics 2009-07-17 S. Ashhab , J. R. Johansson , A. M. Zagoskin , Franco Nori

A driven system of three species of particle diffusing on a ring is studied in detail. The dynamics is local and conserves the three densities. A simple argument suggesting that the model should phase separate and break the translational…

Statistical Mechanics · Physics 2009-10-31 M. R. Evans , Y. Kafri , H. M. Koduvely , D. Mukamel

The data-based discovery of effective, coarse-grained (CG) models of high-dimensional dynamical systems presents a unique challenge in computational physics and particularly in the context of multiscale problems. The present paper offers a…

Computational Physics · Physics 2021-02-10 Sebastian Kaltenbach , Phaedon-Stelios Koutsourelakis

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insight by isolating the essential degrees of freedom that dictate the…

Statistical Mechanics · Physics 2023-04-12 Shriram Chennakesavalu , David J. Toomer , Grant M. Rotskoff