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The aim of the present text is twofold: to provide a compendium of Lagrangian and Hamiltonian geometries and to introduce and investigate new analytical Mechanics: Finslerian, Lagrangian and Hamiltonian. The fundamental equations (or…

Differential Geometry · Mathematics 2012-03-20 Radu Miron

Incorporating atomistic and molecular information into models of cellular behaviour is challenging because of a vast separation of spatial and temporal scales between processes happening at the atomic and cellular levels. Multiscale or…

Computational Physics · Physics 2019-08-28 Radek Erban

Coarse graining techniques offer a promising alternative to large-scale simulations of complex dynamical systems, as long as the coarse-grained system is truly representative of the initial one. Here, we investigate how the dynamical…

Disordered Systems and Neural Networks · Physics 2009-11-13 David Gfeller , Paolo De Los Rios

We propose a method to describe the evolution of two spins coupled by hyperfine interaction in an external time-dependent magnetic field. We apply the approach to the case of hyperfine interaction with axial symmetry, which can be solved…

Quantum Physics · Physics 2021-07-07 Yuri Belousov , Roberto Grimaudo , Antonino Messina , Agostino Migliore , Alessandro Sergi

The Weak-form Sparse Identification of Nonlinear Dynamics algorithm (WSINDy) has been demonstrated to offer coarse-graining capabilities in the context of interacting particle systems (https://doi.org/10.1016/j.physd.2022.133406). In this…

Computational Physics · Physics 2023-12-04 Daniel A. Messenger , Joshua W. Burby , David M. Bortz

Algebraic multigrid (AMG) methods derive their optimal efficiency from the interplay between a relaxation process and a corresponding coarse grid correction. In many standard formulations, relaxation and coarse-graining are analyzed and…

Numerical Analysis · Mathematics 2026-03-30 Rayan Moussa , Karsten Kahl

Starting from the stochastic thermodynamics description of two coupled underdamped Brownian particles, we showcase and compare three different coarse-graining schemes leading to an effective thermodynamic description for the first of the…

Statistical Mechanics · Physics 2020-02-20 Tim Herpich , Kamran Shayanfard , Massimiliano Esposito

Reasoning about the physical world requires models that are endowed with the right inductive biases to learn the underlying dynamics. Recent works improve generalization for predicting trajectories by learning the Hamiltonian or Lagrangian…

Machine Learning · Computer Science 2020-10-27 Marc Finzi , Ke Alexander Wang , Andrew Gordon Wilson

Markov state models (MSMs)---or discrete-time master equation models---are a powerful way of modeling the structure and function of molecular systems like proteins. Unfortunately, MSMs with sufficiently many states to make a quantitative…

Biomolecules · Quantitative Biology 2015-06-03 Gregory R. Bowman

After reviewing the Lagrangian-Hamiltonian unified formalism (i.e, the Skinner-Rusk formalism) for higher-order (non-autonomous) dynamical systems, we state a unified geometrical version of the Variational Principles which allows us to…

Mathematical Physics · Physics 2014-01-16 Pedro D. Prieto-Martínez , Narciso Román-Roy

We introduce a novel approach to obtaining mathematically rigorous results on the global dynamics of ordinary differential equations. Motivated by models of regulatory networks, we construct a state transition graph from a piecewise affine…

Dynamical Systems · Mathematics 2015-08-12 Tomas Gedeon , Shaun Harker , Hiroshi Kokubu , Konstantin Mischaikow , Hiroe Oka

Multilevel techniques are efficient approaches for solving the large linear systems that arise from discretized partial differential equations and other problems. While geometric multigrid requires detailed knowledge about the underlying…

Numerical Analysis · Mathematics 2023-01-23 Tareq. U. Zaman , Scott P. MacLachlan , Luke N. Olson , Matt West

A novel expansion -- which generalizes Magnus expansion -- of the evolution operator associated with a (in general, time-dependent) perturbed Hamiltonian is introduced. It is shown that it has a wide range of possible solutions that can be…

Quantum Physics · Physics 2007-05-23 P. Aniello

We use an "equation-free", coarse-grained computational approach to accelerate molecular dynamics-based computations of demixing (segregation) of dissimilar particles subject to an upward gas flow (gas-fluidized beds). We explore the…

Soft Condensed Matter · Physics 2009-11-11 Sung Joon Moon , S. Sundaresan , I. G. Kevrekidis

We systematically derive an exact coarse-grained description for interacting particles with thermodynamically consistent stochastic dynamics, applicable across different observation scales, the mesoscopic and the macroscopic. We implement…

Statistical Mechanics · Physics 2026-03-05 Atul Tanaji Mohite , Heiko Rieger

Hybrid multiscale modelling has emerged as a useful framework for modelling complex biological phenomena. However, when accounting for stochasticity in the internal dynamics of agents, these models frequently become computationally…

Quantitative Methods · Quantitative Biology 2021-05-11 Daria Stepanova , Helen M. Byrne , Philip K. Maini , Tomás Alarcón

We propose a method for quantization of Lagrangians for which the Hamiltonian, as a function of momentum, is a branched function with cusps. Appropriate boundary conditions, which we identify, insure unitary time evolution. In special cases…

Quantum Physics · Physics 2013-05-30 Alfred Shapere , Frank Wilczek

We have recently presented an extension of the standard variational calculus to include the presence of deformed derivatives in the Lagrangian of a system of particles and in the Lagrangian density of field-theoretic models. Classical…

Mathematical Physics · Physics 2017-06-30 J. Weberszpil , J. A. Helayël-Neto

Cellular automata and other discrete dynamical systems have long been studied as models of emergent complexity. Recently, neural cellular automata have been proposed as models to investigate the emerge of a more general artificial…

Cellular Automata and Lattice Gases · Physics 2025-07-28 Sanyam Jain , Stefano Nichele

Transient bonds between fast linkers and slower particles are widespread in physical and biological systems. In spite of their diverse structure and function, a commonality is that the linkers diffuse on timescales much faster compared to…

Soft Condensed Matter · Physics 2023-06-06 Sophie Marbach , Christopher E. Miles
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