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We consider small-time asymptotics for diffusion processes conditioned by their initial and final positions, under the assumption that the diffusivity has a sub-Riemannian structure, not necessarily of constant rank. We show that, if the…

Probability · Mathematics 2018-10-16 Ismael Bailleul , Laurent Mesnager , James Norris

Single-file diffusion behaves as normal diffusion at small time and as anomalous subdiffusion at large time. These properties can be described by fractional Brownian motion with variable Hurst exponent or multifractional Brownian motion. We…

Statistical Mechanics · Physics 2015-05-13 S. C. Lim , L. P. Teo

Restrictions to molecular motion by barriers (membranes) are ubiquitous in biological tissues, porous media and composite materials. A major challenge is to characterize the microstructure of a material or an organism nondestructively using…

Soft Condensed Matter · Physics 2011-03-11 Dmitry S. Novikov , Els Fieremans , Jens H. Jensen , Joseph A. Helpern

In this paper, we establish new quantitative convergence bounds for a class of functional autoregressive models in weighted total variation metrics. To derive our results, we show that under mild assumptions, explicit minorization and…

Probability · Mathematics 2020-05-05 Valentin De Bortoli , Alain Durmus

We investigate long-time behaviors of empirical measures associated with subordinated Dirichlet diffusion processes on a compact Riemannian manifold $M$ with boundary $\partial M$ to some reference measure, under the quadratic Wasserstein…

Probability · Mathematics 2022-06-09 Huaiqian Li , Bingyao Wu

As a continuation to \cite{MRW} where the Poincar\'e and log-Sobolev inequalities were studied for the sticky-reflected Brownian motion on Riemannian manifolds with boundary, this paper establishes the super and weak Poincar\'e inequalities…

Probability · Mathematics 2025-08-27 Feng-Yu Wang

We consider in this work a one parameter family of hypoelliptic diffusion processes on the unit tangent bundle $T^1 \mathcal M$ of a Riemannian manifold $(\mathcal M,g)$, collectively called kinetic Brownian motions, that are random…

Probability · Mathematics 2015-01-16 Jürgen Angst , Ismaël Bailleul , Camille Tardif

Diffusion denoising models have become a popular approach for image generation, but they often suffer from slow convergence during training. In this paper, we identify that this slow convergence is partly due to the complexity of the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Yumeng Ren , Yaofang Liu , Aitor Artola , Laurent Mertz , Raymond H. Chan , Jean-michel Morel

Diffusive transport in many complex systems features a crossover between anomalous diffusion at short times and normal diffusion at long times. This behavior can be mathematically modeled by cutting off (tempering) beyond a mesoscopic…

Statistical Mechanics · Physics 2021-10-15 Thomas Vojta , Zachary Miller , Samuel Halladay

We consider a diffusion process with coefficients that are periodic outside of an 'interface region' of finite thickness. The question investigated in the articles [1,2] is the limiting long time / large scale behaviour of such a process…

Probability · Mathematics 2009-10-05 Martin Hairer , Charles Manson

In this paper, we study univariate and planar random motions with variable propagation speeds. We first consider motions with space-varying velocity, which can be reduced to constant-velocity motions by means of suitable nonlinear…

Probability · Mathematics 2026-01-27 Manfred Marvin Marchione , Enzo Orsingher

We consider the minor process of (Hermitian) matrix diffusions with constant diagonal drifts. At any given time, this process is determinantal and we provide an explicit expression for its correlation kernel. This is a measure on the…

Mathematical Physics · Physics 2014-04-24 Patrik L. Ferrari , René Frings

We study the problem of lateral diffusion on a static, quasi-planar surface generated by a stationary, ergodic random field possessing rapid small-scale spatial fluctuations. The aim is to study the effective behaviour of a particle…

Probability · Mathematics 2014-02-03 A. B. Duncan

For a given normalized Gaussian symmetric matrix-valued process $Y^{(n)}$, we consider the process of its eigenvalues $\{(\lambda_{1}^{(n)}(t),\dots, \lambda_{n}^{(n)}(t)); t\ge 0\}$ as well as its corresponding process of empirical…

Probability · Mathematics 2018-01-09 Arturo Jaramillo , Juan Carlos Pardo , José Luis Pérez

Denoising diffusion models have recently emerged as the predominant paradigm for generative modelling on image domains. In addition, their extension to Riemannian manifolds has facilitated a range of applications across the natural…

Machine Learning · Computer Science 2023-11-10 Nic Fishman , Leo Klarner , Emile Mathieu , Michael Hutchinson , Valentin de Bortoli

For three constrained Brownian motions, the excursion, the meander, and the reflected bridge, the densities of the maximum and of the time to reach it were expressed as double series by Majumdar, Randon-Furling, Kearney, and Yor (2008).…

Probability · Mathematics 2018-07-25 Robin Khanfir

Diffusion is the result of repeated random scattering. It governs a wide range of phenomena from Brownian motion, to heat flow through window panes, neutron flux in fuel rods, dispersion of light in human tissue, and electronic conduction.…

Mesoscale and Nanoscale Physics · Physics 2018-07-04 Zhou Shi , Azriel Z. Genack

It is well-known under the name of `periodic homogenization' that, under a centering condition of the drift, a periodic diffusion process on R^d converges, under diffusive rescaling, to a d-dimensional Brownian motion. Existing proofs of…

Probability · Mathematics 2014-09-22 Martin Hairer , Etienne Pardoux

We consider the weak convergence of the Euler-Maruyama approximation for Schr\"odinger-F\"ollmer diffusions, which are solutions of Schr\"odinger bridge problems and can be used for sampling from given distributions. We show that the…

Probability · Mathematics 2024-06-04 Koya Endo , Yumiharu Nakano

Fractional Brownian motion (FBM), a non-Markovian self-similar Gaussian stochastic process with long-ranged correlations, represents a widely applied, paradigmatic mathematical model of anomalous diffusion. We report the results of…