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Fractional Brownian motion is a non-Markovian Gaussian process $X_t$, indexed by the Hurst exponent $H$. It generalises standard Brownian motion (corresponding to $H=1/2$). We study the probability distribution of the maximum $m$ of the…

Statistical Mechanics · Physics 2015-11-25 Mathieu Delorme , Kay Joerg Wiese

We investigate the fluctuations around the average density profile in the weakly asymmetric exclusion process with open boundaries in the steady state. We show that these fluctuations are given, in the macroscopic limit, by a centered…

Other Condensed Matter · Physics 2009-11-11 B. Derrida , C. Enaud , C. Landim , S. Olla

In this paper, we study a random field constructed from the two-dimensional Gaussian free field (GFF) by modifying the variance along the scales in the neighborhood of each point. The construction can be seen as a local martingale transform…

Probability · Mathematics 2022-05-25 Louis-Pierre Arguin , Frédéric Ouimet

We study fluctuations of an ensemble of $N$ independent particles undergoing anomalous diffusion with random renewal resetting. The anomalous diffusion is modeled by the scaled Brownian motion (sBm): a Gaussian process, characterized by a…

Statistical Mechanics · Physics 2026-03-17 Ohad Vilk , Baruch Meerson

A scaling limit for the simple random walk on the largest connected component of the Erdos-Renyi random graph in the critical window is deduced. The limiting diffusion is constructed using resistance form techniques, and is shown to satisfy…

Probability · Mathematics 2012-10-23 David A. Croydon

We consider Bienaym\'e-Galton-Watson trees in random environment, where each generation $k$ is attributed a random offspring distribution $\mu_k$, and $(\mu_k)_{k\geq 0}$ is a sequence of independent and identically distributed random…

Probability · Mathematics 2023-01-30 Guillaume Conchon--Kerjan , Daniel Kious , Cécile Mailler

We consider a system of multiscale stochastic differential equations whose slow component is drivenby a fractional Brownian motion with Hurst parameter H greater than 1/2. Under ergodic assumptions ensuring the applicability of the…

Probability · Mathematics 2025-12-10 Xue-Mei Li , Colin Piernot , Szymon Sobczak , Kexing Ying

With large-scale Monte Carlo simulations, we investigate the nonsteady relaxation at the dynamic depinning transition in the two-dimensional Gaussian random-field Ising model. The dynamic scaling behavior is carefully analyzed, and the…

Statistical Mechanics · Physics 2023-06-21 Xiaohui Qian , Gaotian Yu , Nengji Zhou

One reason why standard formulations of the central limit theorems are not applicable in high-dimensional and non-stationary regimes is the lack of a suitable limit object. Instead, suitable distributional approximations can be used, where…

Statistics Theory · Mathematics 2024-12-20 Fabian Mies

In order to scale standard Gaussian process (GP) regression to large-scale datasets, aggregation models employ factorized training process and then combine predictions from distributed experts. The state-of-the-art aggregation models,…

Machine Learning · Statistics 2018-06-05 Haitao Liu , Jianfei Cai , Yi Wang , Yew-Soon Ong

We investigate a model in which an ensemble of chemically identical Brownian particles are continuously growing by condensation and at the same time undergo irreversible aggregation whenever two particles come into contact upon collision.…

Statistical Mechanics · Physics 2011-04-12 M. K. Hassan , M. Z. Hassan

Functional limit theorems are presented for the rescaled occupation time fluctuations process of a critical finite variance branching particle system in $R^d$ with symmetric a-stable motion starting off from either a standard Poisson random…

Probability · Mathematics 2009-11-04 Piotr Milos

The monotone rearrangement of a function is the non-decreasing function with the same distribution. The convex rearrangement of a smooth function is obtained by integrating the monotone rearrangement of its derivative. This operator can be…

Probability · Mathematics 2011-03-10 Raphael Lachieze-Rey , Youri Davydov

Generative modeling of spatio-temporal fields is crucial for a variety of applications, including stochastic weather generators and climate-model surrogates. However, many such fields exhibit complex dependence structures that vary across…

Methodology · Statistics 2026-05-06 Carrie J. Lei-Cramer , Jian Cao , Matthias Katzfuss

We obtain an elementary invariance principle for multi-dimensional Brownian sheet where the underlying random fields are not necessarily independent or stationary. Possible applications include unit-root tests for spatial as well as panel…

Probability · Mathematics 2019-10-08 Michael C. Tseng

We study n-qubit operation rules on (n+1)-sphere with the target to help developing a (photon or other technique) based programmable quantum computer. In the meanwhile, we derive the scaling limits (called reflecting Gaussian random fields…

Quantum Physics · Physics 2024-02-20 Wanyang Dai

We consider Brownian motions with one-sided collisions, meaning that each particle is reflected at its right neighbour. For a finite number of particles a Sch\"{u}tz-type formula is derived for the transition probability. We investigate an…

Mathematical Physics · Physics 2015-04-23 Patrik L. Ferrari , Herbert Spohn , Thomas Weiss

We continue the study of the maximum of the scale-inhomogeneous discrete Gaussian free field in dimension two. In this paper, we consider the regime of weak correlations and prove the convergence in law of the centred maximum to a randomly…

Probability · Mathematics 2020-10-05 Maximilian Fels , Lisa Hartung

A flexible model for non-stationary Gaussian random fields on hypersurfaces is introduced.The class of random fields on curves and surfaces is characterized by an amplitude spectral density of a second order elliptic differential…

Numerical Analysis · Mathematics 2024-12-02 Erik Jansson , Annika Lang , Mike Pereira

Gaussian fields $(g_x)$ on $\mathbb{Z}_q^d$ are constructed from a class of reversible long range random walks $(X_t)_{t\in \mathbb{N}}$ on $\mathbb{Z}_q^d$ in arXiv:2510.22554. The construction is from taking the covariance function of…

Probability · Mathematics 2026-02-24 Robert Griffiths , Shuhei Mano
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