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Mode separation, namely how sharply a distribution fragments into barrier-separated clusters, is a fundamental geometric property of densities, difficult to quantify in high dimensions. It is structurally distinct from dispersion, yet…

Machine Learning · Statistics 2026-05-12 Shaul Tolkovsky , Ori Meidler , Or Zuk

This paper provides an elementary, self-contained analysis of diffusion-based sampling methods for generative modeling. In contrast to existing approaches that rely on continuous-time processes and then discretize, our treatment works…

Machine Learning · Statistics 2025-06-25 Galen Reeves , Henry D. Pfister

We present a formalism for which a dissipative system is given by a variational principle. The formalism applies to dynamical systems where its trajectory is monotonic. Subsequently, we derive its Lagrangian and Hamiltonian. From the…

Quantum Physics · Physics 2017-05-12 N. Emir Anuar

We consider a drift-diffusion process with a time-independent and divergence-free random drift that is of white-noise character. We are interested in the critical case of two space dimensions, where one has to impose a small-scale cut-off…

Probability · Mathematics 2025-11-26 Felix Otto , Christian Wagner

The one-dimensional coagulation-diffusion process describes the strongly fluctuating dynamics of particles, freely hopping between the nearest-neighbour sites of a chain such that one of them disappears with probability 1 if two particles…

Statistical Mechanics · Physics 2016-02-23 Xavier Durang , Jean-Yves Fortin , Malte Henkel

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 introduce the concept of Randomly Modulated Gaussian Processes as a unifying framework for modeling, analyzing and classifying anomalous diffusion models in heterogeneous media. This formulation incorporates correlations in the…

Biological Physics · Physics 2026-03-16 Yann Lanoiselée , Denis S. Grebenkov , Gianni Pagnini

We show that the chaos representation of some Compound Poisson Type processes displays an underlying intrinsic combinatorial structure, partly independent of the chosen process. From the computational viewpoint, we solve the arising…

Probability · Mathematics 2016-11-08 L. Dello Schiavo

In this article, it is proved that for any cumulative distribution function with compact support and a specified t > 0, there exists a diffusion martingale which has this law at time t. The article proves existence; no claims are made about…

Probability · Mathematics 2012-10-01 John M. Noble

We discuss several examples of point processes (all taken from Hough, Krishnapur, Peres, Vir\'ag (2009)) for which the autocorrelation and diffraction measures can be calculated explicitly. These include certain classes of determinantal and…

Mathematical Physics · Physics 2015-07-22 Michael Baake , Holger Kösters , Robert V. Moody

The infinitely-many-neutral-alleles model has recently been extended to a class of diffusion processes associated with Gibbs partitions of two-parameter Poisson-Dirichlet type. This paper introduces a family of infinite-dimensional…

Probability · Mathematics 2013-02-15 Matteo Ruggiero , Stephen G. Walker , Stefano Favaro

It is generally understood that a given one-dimensional diffusion may be transformed by Cameron-Martin-Girsanov measure change into another one-dimensional diffusion with the same volatility but a different drift. But to achieve this we…

Mathematical Finance · Quantitative Finance 2020-12-08 Sascha Desmettre , Gunther Leobacher , L. C. G. Rogers

We present new extensions to a method for constructing several families of solvable one-dimensional time-homogeneous diffusions whose transition densities are obtainable in analytically closed-form. Our approach is based on a dual…

Pricing of Securities · Quantitative Finance 2014-12-03 Giuseppe Campolieti , Roman N. Makarov

We study various temporal correlation functions of a tagged particle in one-dimensional systems of interacting point particles evolving with Hamiltonian dynamics. Initial conditions of the particles are chosen from the canonical thermal…

Statistical Mechanics · Physics 2015-06-25 Anjan Roy , Abhishek Dhar , Onuttom Narayan , Sanjib Sabhapandit

We obtain error approximation bounds between expected suprema of canonical processes that are generated by random vectors with independent coordinates and expected suprema of Gaussian processes. In particular, we obtain a sharper proximity…

Probability · Mathematics 2024-11-06 Shivam Sharma

Diffusion processes govern fundamental phenomena such as phase transformations, doping, and intercalation in van der Waals (vdW) bonded materials. Here, we quantify the diffusion dynamics of W atoms by visualizing the motion of individual…

An interesting line of research is the investigation of the laws of random variables known as Dirichlet means. However, there is not much information on interrelationships between different Dirichlet means. Here, we introduce two…

Statistics Theory · Mathematics 2010-10-11 Lancelot F. James

We consider consistent diffusion dynamics, leaving the celebrated Hua-Pickrell measures, depending on a complex parameter $s$, invariant. These, give rise to Feller-Markov processes on the infinite dimensional boundary $\Omega$ of the…

Probability · Mathematics 2019-02-15 Theodoros Assiotis

We consider Gaussian measures $\mu, \tilde{\mu}$ on a separable Hilbert space, with fractional-order covariance operators $A^{-2\beta}$ resp. $\tilde{A}^{-2\tilde{\beta}}$, and derive necessary and sufficient conditions on $A, \tilde{A}$…

Probability · Mathematics 2023-07-19 David Bolin , Kristin Kirchner

Strong anomalous diffusion is characterized by asymptotic power-law growth of the moments of displacement, with exponents that do not depend linearly on the order of the moment. The exponents concerning small-order moments are dominated by…

Statistical Mechanics · Physics 2021-01-27 Jürgen Vollmer , Lamberto Rondoni , Muhammad Tayyab , Claudio Giberti , Carlos Mejía-Monasterio