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The internal dynamics of macro-molecular systems is characterized by widely separated time scales, ranging from fraction of ps to ns. In ordinary molecular dynamics simulations, the elementary time step dt used to integrate the equation of…

Soft Condensed Matter · Physics 2015-05-19 Pietro Faccioli

Physicochemical models can be powerful tools to trace the chemical evolution of a protostellar system and allow to constrain its physical conditions at formation. The aim of this work is to assess whether source-tailored modelling is needed…

Solar and Stellar Astrophysics · Physics 2020-08-19 Beatrice M. Kulterer , Maria N. Drozdovskaya , Audrey Coutens , Sébastien Manigand , Gwendoline Stéphan

Reaction-diffusion systems are ubiquitous in nature and in engineering applications, and are often modeled using a non-linear system of governing equations. While robust numerical methods exist to solve them, deep learning-based reduced…

Computational Engineering, Finance, and Science · Computer Science 2020-06-11 Kaushik Balakrishnan , Devesh Upadhyay

Theoretical concepts in condensed matter physics are typically verified and also developed by exploiting computer simulations mostly in simple models. Predictions based on these usually isotropic models are often at odds with measurement…

Soft Condensed Matter · Physics 2020-11-13 K. Koperwas , A. Grzybowski , M. Paluch

Dynamical systems theory provides powerful methods to extract effective macroscopic dynamics from complex systems with slow modes and fast modes. Here we derive and theoretically support a macroscopic, spatially discrete, model for a class…

Analysis of PDEs · Mathematics 2010-03-12 Wei Wang , A. J. Roberts

Developing new molecular compounds is crucial to address pressing challenges, from health to environmental sustainability. However, exploring the molecular space to discover new molecules is difficult due to the vastness of the space. Here…

Machine Learning · Computer Science 2025-05-23 Manuel Ruiz-Botella , Marta Sales-Pardo , Roger Guimerà

Despite their empirical success, how diffusion models generalize remains poorly understood from a mechanistic perspective. We demonstrate that diffusion models trained with flow-matching objectives exhibit grokking--delayed generalization…

Machine Learning · Computer Science 2026-04-21 Joon Hyeok Kim , Yong-Hyun Park , Mattis Dalsætra Østby , Jiatao Gu

A generalization of the Heisenberg algebra has been recently constructed. This generalized algebra has a characteristic function which depends on one of its generators. When this function is linear, $qJ_0+s$, it is possible to construct a…

High Energy Physics - Phenomenology · Physics 2016-09-06 C. I. Ribeiro-Silva , N. M. Oliveira-Neto

The Grey System Theory (GST) is a powerful mathematical framework employed for modeling systems with uncertain or incomplete information. This paper proposes an integration of the GST with time scales, a generalized approach that…

Applications · Statistics 2025-01-17 Wanli Xie

A new lattice Boltzmann model for reactive ideal gas mixtures is presented. The model is an extension to reactive flows of the recently proposed multi-component lattice Boltzmann model for compressible ideal gas mixtures with Stefan-Maxwell…

Fluid Dynamics · Physics 2021-01-06 N. Sawant , B. Dorschner , I. V. Karlin

Generalized mode-coupling theory (GMCT) has recently emerged as a promising first-principles theory to study the poorly understood dynamics of glass-forming materials. Formulated as a hierarchical extension of standard mode-coupling theory…

Soft Condensed Matter · Physics 2021-12-21 Vincent E. Debets , Chengjie Luo , Simone Ciarella , Liesbeth M. C. Janssen

Diffusion probabilistic models excel at sampling new images from learned distributions. Originally motivated by drift-diffusion concepts from physics, they apply image perturbations such as noise and blur in a forward process that results…

Image and Video Processing · Electrical Eng. & Systems 2024-06-07 Pascal Peter

This note shows how classical tools from linear control theory can be leveraged to provide a global analysis of nonlinear reaction-diffusion models. The approach is differential in nature. It proceeds from classical tools of contraction…

Systems and Control · Electrical Eng. & Systems 2020-12-18 Felix Miranda-Villatoro , Rodolphe Sepulchre

Aim of this note is to analyse branching Brownian motion within the class of models introduced in the recent paper [4] and called chemical diffusion master equations. These models provide a description for the probabilistic evolution of…

Probability · Mathematics 2024-01-23 Alberto Lanconelli , Berk Tan Perçin

Reaction-diffusion equations describe various spatially extended processes that unfold as traveling fronts moving at constant velocity. We introduce and solve analytically a model that, besides such fronts, supports solutions advancing as…

Biological Physics · Physics 2026-02-13 Louis Brezin , Kyle J. Shaffer , Kirill S. Korolev

Coarse-grained Langevin-type effective field equations are derived for classical systems of particles. These equations include the effects of thermal fluctuation and dissipation which may arise from coupling to an external bath, as in the…

Nuclear Theory · Physics 2009-10-30 L. P. Csernai , S. Jeon , J. I. Kapusta

Reaction-diffusion systems have been proposed as a model for pattern formation and morphogenesis. The Fickian diffusion typically employed in these constructions model the Brownian motion of particles. The biological and chemical elements…

Quantitative Methods · Quantitative Biology 2023-11-09 Siddhartha Srivastava , Krishna Garikipati

Motivated by the recent increased interest in energy non-conserving models in cosmology, we extend the analysis of the cosmological consequences of the Classical Channel Model of Gravity (CCG). This model is based on the classical-quantum…

General Relativity and Quantum Cosmology · Physics 2017-06-09 Romain Pascalie , Natacha Altamirano , Robert B. Mann

We propose a new model for the description of complex granular particles and their interaction in molecular dynamics simulations of granular material in two dimensions. The grains are composed of triangles which are connected by deformable…

adap-org · Physics 2012-08-29 Thorsten Poeschel , Volkhard Buchholtz

Understanding the structure and dynamics of liquids is pivotal for the study of larger spatiotemporal processes, especially in glass-forming materials at low temperatures. Density scaling, observed in many molecular systems through…

Soft Condensed Matter · Physics 2024-10-29 Jaehyeok Jin , David R. Reichman , Jeppe C. Dyre , Ulf R. Pedersen