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Fastest arrival events, where the first among many diffusing particles reaches a target, are central in triggering signal initiation in molecular stochastic systems. Classical approaches to simulate such events rely on full trajectory…

Probability · Mathematics 2026-05-26 Emmanuel Akame Mfoumou , David Holcman

Locally broken symmetries are used across fields to transport matter, particles and information in preferential directions. Beyond local mechanisms, spatially distributed nonlinearities in crystalline media have enabled non-reciprocal…

Soft Condensed Matter · Physics 2026-03-31 Aaron Winn , Justine Parmentier , Eleni Katifori , Martin Brandenbourger

Understanding the transport behavior of quantum many-body systems constitutes an important physical endeavor, both experimentally and theoretically. While a reliable classification into normal and anomalous dynamics is known to be…

Statistical Mechanics · Physics 2025-06-11 Jiaozi Wang , Mats H. Lamann , Robin Steinigeweg , Jochen Gemmer

The dynamics of viscoelastic fluids are governed by a memory function, essential yet challenging to compute, especially when diffusion faces boundary restrictions. We propose a computational method that captures memory effects by analyzing…

Chemical Physics · Physics 2024-01-02 Moe Niknam , Louis-S. Bouchard

Computational tools for normal mode analysis, which are widely used in physics and materials science problems, are designed here in a single package called NMscatt (Normal Modes & scattering) that allows arbitrarily large systems to be…

Computational Physics · Physics 2009-11-13 Franci Merzel , Fabien Fontaine-Vive , Mark R. Johnson

Molecular dynamics (MD) simulations are used to investigate $^1$H nuclear magnetic resonance (NMR) relaxation and diffusion of bulk $n$-C$_5$H$_{12}$ to $n$-C$_{17}$H$_{36}$ hydrocarbons and bulk water. The MD simulations of the $^1$H NMR…

Chemical Physics · Physics 2017-03-08 P. M. Singer , D. Asthagiri , W. G. Chapman , G. J. Hirasaki

Many chemical reactions can be formulated in terms of particle diffusion in a complex energy landscape. Transition path theory (TPT) is a theoretical framework for describing the direct (reaction) pathways from reactant to product states…

Statistical Mechanics · Physics 2023-10-03 Paul C Bressloff

We study the nonlinear propagator, a key ingredient in renormalized perturbation theory (RPT) that allows a well-controlled extension of perturbation theory into the nonlinear regime. We show that it can be thought as measuring the memory…

Astrophysics · Physics 2009-11-13 M. Crocce , R. Scoccimarro

Direct numerical simulations (DNS) of particle-laden turbulent flow in straight, mildly curved and strongly bent pipes are performed in which the solid phase is modelled as small heavy spherical particles. A total of seven populations of…

Fluid Dynamics · Physics 2016-04-20 Azad Noorani , Gaetano Sardina , Luca Brandt , Philipp Schlatter

Atomistic modelling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an…

Computational Physics · Physics 2019-11-06 Federico Giberti , Bingqing Cheng , Gareth Aneurin Tribello , Michele Ceriotti

Advances in intensity-based microscopy techniques have improved our ability to quantify particle motion at microscopic scales, enabling insight into diffusion and collective dynamics. Building on this foundation, we introduce a novel…

Soft Condensed Matter · Physics 2026-04-03 Sophie Hermann , Seyed Saman Banarooei , Adam Carter , Carlos A. Silvera Batista , Sophie Marbach

Molecular dynamics simulations are a powerful tool to study diffusion processes in battery electrolyte and electrode materials. From a single molecular dynamics simulation many properties relevant to diffusion can be obtained, including the…

Chemical Physics · Physics 2018-07-09 Niek J. J. de Klerk , Eveline van der Maas , Marnix Wagemaker

Anisotropic diffusion processes emerge in various fields such as transport in biological tissue and diffusion in liquid crystals. In such systems, the motion is described by a diffusion tensor. For a proper characterization of processes…

Data Analysis, Statistics and Probability · Physics 2013-11-14 Mario Heidernätsch , Michael Bauer , Günter Radons

Single-particle tracking allows to infer the motion of single molecules in living cells. When we observe a long trajectory (more than 100 points), it is possible that the particle switches mode of motion over time. Then, fitting a single…

Methodology · Statistics 2018-04-16 Vincent Briane , Charles Kervrann , Myriam Vimond

Atmospheric turbulence is one of the lead disturbance factors for free-space quantum communication. The quantum states of light in such channels are affected by fluctuating losses characterized by the probability distribution of…

Quantum Physics · Physics 2023-10-02 M. Klen , A. A. Semenov

Porous and heterogeneous materials are found in many applications from composites, membranes, chemical reactors, and other engineered materials to biological matter and natural subsurface structures. In this work we propose an integrated…

Computational Physics · Physics 2019-09-15 Gianluca Boccardo , Eleonora Crevacore , Alberto Passalacqua , Matteo Icardi

An analytical soluble model based on a Continuous Time Random Walk (CTRW) scheme for the adsorption-desorption processes at interfaces, called bulk-mediated surface diffusion, is presented. The time evolution of the effective probability…

Condensed Matter · Physics 2009-11-10 Jorge A. Revelli , Carlos. E. Budde , Domingo Prato , Horacio S. Wio

We present a new approach to carry out non-adiabatic molecular dynamics to study the carrier mobility in an organic monolayer. This approach allows the calculation of a 4802 atom system for 825 fs in about three hours using 51,744 computer…

Materials Science · Physics 2012-03-13 Junfeng Ren , Nenad Vukmirovic , Lin-Wang Wang

Constructing reduced representations of high-dimensional systems is a fundamental problem in physical chemistry. Many unsupervised machine learning methods can automatically find such low-dimensional representations. However, an often…

Chemical Physics · Physics 2024-04-04 Jakub Rydzewski

Diffusion-based models decompose sampling into many small Gaussian denoising steps -- an assumption that breaks down when generation is compressed to a few coarse transitions. Existing few-step methods address this through distillation,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Jiatao Gu , Tianrong Chen , Ying Shen , David Berthelot , Shuangfei Zhai , Josh Susskind
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