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We formulate a new theory for how caging constraints in glass-forming liquids at a surface or interface are modified and then spatially transferred, in a layer-by-layer bootstrapped manner, into the film interior in the context of the…

Soft Condensed Matter · Physics 2019-02-20 Anh D. Phan , Kenneth S. Schweizer

A stochastic differential game theoretic model has been proposed to determine optimal behavior of a fish while migrating against water currents both in rivers and oceans. Then, a dynamic objective function is maximized subject to two…

Optimization and Control · Mathematics 2021-06-29 Paramahansa Pramanik

The dynamics of biological systems, from proteins to cells to organisms, is complex and stochastic. To decipher their physical laws, we need to bridge between experimental observations and theoretical modeling. Thanks to progress in…

Soft Condensed Matter · Physics 2024-06-05 Pierre Ronceray

We develop further ideas on how to construct low-dimensional models of stochastic dynamical systems. The aim is to derive a consistent and accurate model from the originally high-dimensional system. This is done with the support of centre…

chao-dyn · Physics 2008-02-03 Chao Xu , A. J. Roberts

We propose a method for developing the flows of stochastic dynamical systems, posed as Ito's stochastic differential equations, on a Riemannian manifold identified through a suitably constructed metric. The framework used for the stochastic…

Mathematical Physics · Physics 2020-07-24 Mariya Mamajiwala , Debasish Roy

To solve control problems via model-based reasoning or planning, an agent needs to know how its actions affect the state of the world. The actions an agent has at its disposal often change the state of the environment in systematic ways.…

Machine Learning · Computer Science 2024-11-04 Tankred Saanum , Peter Dayan , Eric Schulz

We discuss the dynamics and thermodynamics of the Hamiltonian Mean Field model (HMF) which is a prototypical system with long-range interactions. The HMF model can be seen as the one Fourier component of a one-dimensional self-gravitating…

Statistical Mechanics · Physics 2009-11-10 P. H. Chavanis , J. Vatteville , F. Bouchet

We propose Functional Flow Matching (FFM), a function-space generative model that generalizes the recently-introduced Flow Matching model to operate in infinite-dimensional spaces. Our approach works by first defining a path of probability…

Machine Learning · Computer Science 2023-12-07 Gavin Kerrigan , Giosue Migliorini , Padhraic Smyth

How does the brain predict physical outcomes while acting in the world? Machine learning world models compress visual input into latent spaces, discarding the spatial structure that characterizes sensory cortex. We propose isomorphic world…

Neurons and Cognition · Quantitative Biology 2026-02-24 Joshua Nunley

Spacetime foam manifests itself in a variety of ways. It has some attributes of a turbulent fluid. It is the source of the holographic principle. Cosmologically it may play a role in explaining why the energy density has the critical value,…

General Relativity and Quantum Cosmology · Physics 2011-02-24 Y. Jack Ng

As written by statistician George Box "All models are wrong, but some are useful", standard diffusion derivation or Feynman path ensembles use nonphysical infinite velocity/kinetic energy nowhere differentiable trajectories - what seems…

Statistical Mechanics · Physics 2024-04-23 Jarek Duda

It is argued that the world is a dissipative dynamic system, a phase flow of which is formed by conformally-symplectic mapping. The key assumption is that the concept of energy in microcosm makes sense only for the steady motions…

Dynamical Systems · Mathematics 2009-04-08 A. P. Alexandrov

Current theoretical and computational models of dopamine-based reinforcement learning are largely rooted in the classical behaviorist tradition, and envision the organism as a purely reactive recipient of rewards and punishments, with…

Neurons and Cognition · Quantitative Biology 2014-05-01 Randall C. O'Reilly , Thomas E. Hazy , Jessica Mollick , Prescott Mackie , Seth Herd

The present work proposes an approach for fluid-solid and contact interaction problems including thermo-mechanical coupling and reversible phase transitions. The solid field is assumed to consist of several arbitrarily-shaped, undeformable…

Computational Engineering, Finance, and Science · Computer Science 2021-09-14 Sebastian L. Fuchs , Christoph Meier , Wolfgang A. Wall , Christian J. Cyron

The probability distributions, as well as the mean values of stochastic currents and fluxes, associated with a driven Langevin process, provide a good and topologically protected measure of how far a stochastic system is driven out of…

Chemical Physics · Physics 2017-01-04 Michael J. Catanzaro , Vladimir Y. Chernyak , John R. Klein

Levy flights and fractional Brownian motion (fBm) have become exemplars of the heavy tailed jumps and long-ranged memory seen in space physics and elsewhere. Natural time series frequently combine both effects, and Linear Fractional Stable…

Mathematical Physics · Physics 2008-03-20 Nicholas W. Watkins , Daniel Credgington , Raul Sanchez , Sandra C. Chapman

Foundation models (FMs) have emerged as a powerful paradigm, enabling a diverse range of data analytics and knowledge discovery tasks across scientific fields. Inspired by the success of FMs, particularly large language models, researchers…

Machine Learning · Computer Science 2025-11-27 Sean Bin Yang , Ying Sun , Yunyao Cheng , Yan Lin , Kristian Torp , Jilin Hu

Over the past several decades, phase field modeling has been established as a standard simulation technique for mesoscopic science, allowing for seamless boundary tracking of moving interfaces and relatively easy coupling to other physical…

Statistical Mechanics · Physics 2024-12-25 Travis Leadbetter , Prashant K. Purohit , Celia Reina

Soft lubricated contacts exhibit complex interfacial behaviours governed by the coupled effects of multiscale surface roughness and non-linear fluid-solid interactions. Accurately capturing this interplay across thin-film flows is…

Soft Condensed Matter · Physics 2025-11-12 Qian Wang , Suhaib Ardah , Tom Reddyhoff , Daniele Dini

Biological systems commonly exhibit complex spatiotemporal patterns whose underlying generative mechanisms pose a significant analytical challenge. Traditional approaches to spatiodynamic inference rely on dimensionality reduction through…

Quantitative Methods · Quantitative Biology 2025-08-01 Jun Won Park , Kangyu Zhao , Sanket Rane