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Diffusion models have been successful on a range of conditional generation tasks including molecular design and text-to-image generation. However, these achievements have primarily depended on task-specific conditional training or…

Machine Learning · Statistics 2024-11-26 Luhuan Wu , Brian L. Trippe , Christian A. Naesseth , David M. Blei , John P. Cunningham

We study lower and upper bounds for the density of a diffusion process in ${\mathbb{R}}^n$ in a small (but not asymptotic) time, say $\delta$. We assume that the diffusion coefficients $\sigma_1,\ldots,\sigma_d$ may degenerate at the…

Probability · Mathematics 2019-12-03 Vlad Bally , Lucia Caramellino , Paolo Pigato

We present a rigorous study of quantum diffusion of a relativistic particle subjected to a time-dependent random potential with $\delta$ correlation in time. We find that in the asymptotic time limit the particle wave packet spreads…

Disordered Systems and Neural Networks · Physics 2015-09-28 Reza Sepehrinia

For a diffusion process $X(t)$ of drift $\mu(x)$ and of diffusion coefficient $D=1/2$, we study the joint distribution of the two local times $A(t)= \int_{0}^{t} d\tau \delta(X(\tau)) $ and $B(t)= \int_{0}^{t} d\tau \delta(X(\tau)-L) $ at…

Statistical Mechanics · Physics 2023-05-04 Alain Mazzolo , Cécile Monthus

It has been conjectured that transport in integrable one-dimensional (1D) systems is necessarily ballistic. The large diffusive response seen experimentally in nearly ideal realizations of the S=1/2 1D Heisenberg model is therefore puzzling…

Strongly Correlated Electrons · Physics 2010-12-01 J. Sirker , R. G. Pereira , I. Affleck

We investigate the diffusive motion of an overdamped classical particle in a 1D random potential using the mean first-passage time formalism and demonstrate the efficiency of this method in the investigation of the large-time dynamics of…

Superconductivity · Physics 2009-10-31 D. A. Gorokhov , G. Blatter

When the unconditioned process is a diffusion living on the half-line $x \in ]-\infty,a[$ in the presence of an absorbing boundary condition at position $x=a$, we construct various conditioned processes corresponding to finite or infinite…

Statistical Mechanics · Physics 2022-10-17 Cécile Monthus , Alain Mazzolo

We study the biased diffusion of particles moving in one direction under the action of a constant force in the presence of a piecewise linear random potential. Using the overdamped equation of motion, we represent the first and second…

Statistical Mechanics · Physics 2010-07-08 S. I. Denisov , E. S. Denisova , H. Kantz

Contextual situations are those in which seemingly "the same" random variable changes its identity depending on the conditions under which it is recorded. Such a change of identity is observed whenever the assumption that the variable is…

Quantum Physics · Physics 2015-06-19 Ehtibar N. Dzhafarov , Janne V. Kujala

The dynamics of a freely diffusing particle in a two-dimensional channel with cross sectional area $A(x)$, can be effectively described by a one-dimensional diffusion equation under the action of a potential of mean force $U(x)=-k_BT\ln…

Statistical Mechanics · Physics 2019-02-28 Matan Sivan , Oded Farago

In this work we present a general derivation of the non-Fickian behavior for the self-diffusion of identically interacting particle systems with excluded mutual passage. We show that the conditional probability distribution of finding a…

Statistical Mechanics · Physics 2009-11-07 Markus Kollmann

We consider a random walk in a random environment on $\mathbb{Z}^d$ under ballisticity condition $(T)$. We show the existence of the invariant measure $Q$ with respect to the environment viewed from the particle for $d=2$ and $d=3$, which…

Probability · Mathematics 2025-08-05 Tal Peretz

We consider a run an tumble particle with two velocity states $\pm v_0$, in an inhomogeneous force field $f(x)$ in one dimension. We obtain exact formulae for its velocity $V_L$ and diffusion constant $D_L$ for arbitrary periodic $f(x)$ of…

Statistical Mechanics · Physics 2020-06-17 Pierre Le Doussal , Satya N. Majumdar , Gregory Schehr

This is an attempt to address diffusion phenomena from the point of view of information theory. We imagine a regular hamiltonian system under the random perturbation of thermal (molecular) noise and chaotic instability. The irregularity of…

Statistical Mechanics · Physics 2007-05-23 Qiuping A. Wang

A considerable number of systems have recently been reported in which Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability…

Statistical Mechanics · Physics 2018-11-26 V. Sposini , A. V. Chechkin , F. Seno , G. Pagnini , R. Metzler

We are concerned with random walks on $\mathbb{Z}^d$, $d\geq 3$, in an i.i.d. random environment with transition probabilities $\epsilon$-close to those of simple random walk. We assume that the environment is balanced in one fixed…

Probability · Mathematics 2016-12-28 Erich Baur

The problem of natural selection in dispersal-structured populations consisting of individuals characterized by different diffusion coefficients is studied. The competition between the organisms is taken into account through the assumption…

Adaptation and Self-Organizing Systems · Physics 2020-05-01 E. Heinsalu , D. Navidad Maeso , M. Patriarca

In this paper two hypotheses are developed. The first hypothesis is the existence of random phenomena/experiments in which the events cannot generally be assigned a definite probability but that nevertheless admit a class of nearly certain…

Quantum Physics · Physics 2023-02-24 Bruno Galvan

We study a Brownian particle diffusing under a time-modulated stochastic resetting mechanism to a fixed position. The rate of resetting r(t) is a function of the time t since the last reset event. We derive a sufficient condition on r(t)…

Statistical Mechanics · Physics 2016-05-18 Arnab Pal , Anupam Kundu , Martin R. Evans

Diffusion Models (DMs) iteratively denoise random samples to produce high-quality data. The iterative sampling process is derived from Stochastic Differential Equations (SDEs), allowing a speed-quality trade-off chosen at inference. Another…

Machine Learning · Computer Science 2024-09-27 Mattias Cross , Anton Ragni