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Related papers: Drived diffusion of vector fields

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We present a novel diffusion-based framework for synthesizing 2D vector fields from sparse, coherent inputs (i.e., streamlines) while maintaining physical plausibility. Our method employs a conditional denoising diffusion probabilistic…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Nguyen K. Phan , Ricardo Morales , Sebastian D. Espriella , Guoning Chen

We study the disorder-induced deterministic dispersion of particles uniformly driven in an array of narrow tracks. For different toy models with quenched disorder we obtain exact analytical expressions for the steady-state mean velocity $v$…

Disordered Systems and Neural Networks · Physics 2022-12-01 Federico Elías , Alejandro B. Kolton

We experimentally study the transport prop- erties of dipolar and fundamental modes on one di- mensional (1D) coupled waveguide arrays. By carefully modulating a wide optical beam, we are able to effec- tively excite dipolar or fundamental…

Vector-valued Gaussian mixtures form an important special subset of vector-valued distributions. In general, vector-valued distributions constitute natural representations for physical entities, which can mutate or transit among alternative…

Machine Learning · Statistics 2022-11-11 Jiening Zhu , Kaiming Xu , Allen Tannenbaum

We study here the random diffusion model. This is a continuum model for a conserved scalar density field $\phi$ driven by diffusive dynamics. The interesting feature of the dynamics is that the {\it bare} diffusion coefficient $D$ is…

Soft Condensed Matter · Physics 2009-11-13 Gene F. Mazenko

This paper addresses the problem of generating dynamically admissible trajectories for control tasks using diffusion models, particularly in scenarios where the environment is complex and system dynamics are crucial for practical…

Robotics · Computer Science 2025-10-15 Darshan Gadginmath , Fabio Pasqualetti

Denoising diffusion models are a popular class of generative models providing state-of-the-art results in many domains. One adds gradually noise to data using a diffusion to transform the data distribution into a Gaussian distribution.…

Machine Learning · Computer Science 2023-08-21 Francisco Vargas , Will Grathwohl , Arnaud Doucet

Diffusive transport is a universal phenomenon, throughout both biological and physical sciences, and models of diffusion are routinely used to interrogate diffusion-driven processes. However, most models neglect to take into account the…

Quantitative Methods · Quantitative Biology 2015-10-28 Paul R. Taylor , Christian A. Yates , Matthew J. Simpson , Ruth E. Baker

For electron transport in parallel-plane semiconducting structures, a model is developed that unifies ballistic and diffusive transport and thus generalizes the Drude model. The unified model is valid for arbitrary magnitude of the mean…

Materials Science · Physics 2009-11-07 R. Lipperheide , T. Weis , U. Wille

A conditional diffusion model has been developed to analyze intricate conductance fluctuations called universal conductance fluctuations or quantum fingerprints appearing in quantum transport phenomena. The model reconstructs impurity…

Mesoscale and Nanoscale Physics · Physics 2025-06-11 Naoto Yokoi , Yuki Tanaka , Yukito Nonaka , Shunsuke Daimon , Junji Haruyama , Eiji Saitoh

An ordinary differential equation perturbed by a null-recurrent diffusion will be considered in the case where the averaging type perturbation is strong only when a fast motion is close to the origin. The normal deviations of these…

Probability · Mathematics 2015-08-24 Zsolt Pajor-Gyulai , Michael Salins

Diffusion and rectification of Brownian particles powered by a rotating wheel are numerically investigated in a two-dimensional channel. The nonequilibrium driving comes from the rotating wheel, which can break thermodynamical equilibrium…

Statistical Mechanics · Physics 2017-07-24 Bao-quan Ai

We develop a quantum dynamical field theory for studying phase transitions in driven open systems coupled to Markovian noise, where non-linear noise effects and fluctuations beyond semiclassical approximations influence the critical…

Quantum Gases · Physics 2016-09-07 Jamir Marino , Sebastian Diehl

We characterize a transition from normal to ballistic diffusion in a bouncing ball dynamics. The system is composed of a particle, or an ensemble of non-interacting particles, experiencing elastic collisions with a heavy and periodically…

Statistical Mechanics · Physics 2018-04-04 André L. P. Livorati , Tiago Kroetz , Carl P. Dettmann , Iberê L. Caldas , Edson D. Leonel

Transport and diffusion of heat in one dimensional (1D) nonlinear systems which {\it conserve momentum} is typically thought to proceed anomalously. Notable exceptions, however, exist of which the rotator model is a prominent case.…

Statistical Mechanics · Physics 2015-05-05 Yunyun Li , Sha Liu , Nianbei Li , Peter Hanggi , Baowen Li

With a scalar potential and a bivector potential, the vector field associated with the drift of a diffusion is decomposed into a generalized gradient field, a field perpendicular to the gradient, and a divergence-free field. We give such…

Statistical Mechanics · Physics 2021-05-26 Ying-Jen Yang , Yu-Chen Cheng

We generalize the two-channel (Edwards) fermion-boson model describing quantum transport in a background medium to the more realistic case of dispersive bosons. Using the variational exact diagonalization technique, we numerically solve the…

Quantum Gases · Physics 2024-04-11 Monodeep Chakraborty , Holger Fehske

Excluded-volume effects can play an important role in determining transport properties in diffusion of particles. Here, the diffusion of finite-sized hard-core interacting particles in two or three dimensions is considered systematically…

Analysis of PDEs · Mathematics 2012-01-06 Maria Bruna , S. Jonathan Chapman

We study the coherent dynamics of excitations on vibrating chains. By applying an external field and matching the field strength with the oscillation frequency of the chain it is possible to obtain an (average) transport of an initial…

Quantum Physics · Physics 2015-05-20 Oliver Muelken , Maximilian Bauer

Diffusion Models (DMs) are powerful generative models that add Gaussian noise to the data and learn to remove it. We wanted to determine which noise distribution (Gaussian or non-Gaussian) led to better generated data in DMs. Since DMs do…

Machine Learning · Computer Science 2023-04-13 Alexia Jolicoeur-Martineau , Kilian Fatras , Ke Li , Tal Kachman