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Fix $p>1$, not necessarily integer, with $p(d-2)<d$. We study the $p$-fold self-intersection local time of a simple random walk on the lattice $\Z^d$ up to time $t$. This is the $p$-norm of the vector of the walker's local times, $\ell_t$.…

Probability · Mathematics 2011-06-10 Mathias Becker , Wolfgang König

In this paper, we study a natural discretization of the smooth Gaussian curvature on surfaces, which is defined as the quotient of the angle defect and the area of a geodesic disk at a vertex of a polyhedral surface. It is proved that each…

Differential Geometry · Mathematics 2023-09-14 Xu Xu , Chao Zheng

Recently, it has been shown in [Hairer, M., Hutzenthaler, M., Jentzen, A., Loss of regularity for Kolmogorov equations, Ann. Probab. 43, 2 (2015), 468--527] that there exists a system of stochastic differential equations (SDE) on the time…

Probability · Mathematics 2016-09-27 Larisa Yaroslavtseva

We investigate the local times of a continuous-time Markov chain on an arbitrary discrete state space. For fixed finite range of the Markov chain, we derive an explicit formula for the joint density of all local times on the range, at any…

Probability · Mathematics 2009-09-29 David Brydges , Remco van der Hofstad , Wolfgang König

The Kardar-Parisi-Zhang (KPZ) equation on the real line is well-known to admit Brownian motion with a linear drift as a stationary distribution (modulo additive constants). We show that these solutions are attractive, a result known as a…

Probability · Mathematics 2022-11-15 Christopher Janjigian , Firas Rassoul-Agha , Timo Seppäläinen

We develop numerical methods for computing statistics of stochastic processes on surfaces of general shape with drift-diffusion dynamics $d\mathbf{X}_t = a(\mathbf{X}_t)dt + \mathbf{b}(\mathbf{X}_t)d\mathbf{W}_t$. We formulate descriptions…

Numerical Analysis · Mathematics 2023-02-28 B. J. Gross , P. Kuberry , P. J. Atzberger

This paper studies the large scale limits of multi-type invariant distributions and Busemann functions of planar stochastic growth models in the Kardar-Parisi-Zhang (KPZ) class. We identify a set of sufficient hypotheses for convergence of…

Probability · Mathematics 2025-02-06 Ofer Busani , Timo Seppäläinen , Evan Sorensen

We study the critical case of first-passage percolation in two dimensions. Letting $(t_e)$ be i.i.d. nonnegative weights assigned to the edges of $\mathbb{Z}^2$ with $\mathbb{P}(t_e=0)=1/2$, consider the induced pseudometric (passage time)…

Probability · Mathematics 2019-12-17 Michael Damron , David Harper

There has been much success in describing the limiting spatial fluctuations of growth models in the Kardar-Parisi-Zhang (KPZ) universality class. A proper rescaling of time should introduce a non-trivial temporal dimension to these limiting…

Probability · Mathematics 2012-10-29 Ivan Corwin , P. L. Ferrari , S. Peche

This work builds upon the recent monograph [5] on self-similar Markov trees. A self-similar Markov tree is a random real tree equipped with a function from the tree to $[0,\infty)$ that we call the decoration. Here, we construct local time…

Probability · Mathematics 2026-01-16 Jean Bertoin , Armand Riera , Alejandro Rosales-Ortiz

We study the convergence in rough path topology of a certain class of discrete processes, the hidden Markov walks, to a Brownian motion with an area anomaly. This area anomaly, which is a new object, keeps track of the time-correlation of…

Probability · Mathematics 2020-03-20 Olga Lopusanschi , Damien Simon

Under the assumption that sequences of graphs equipped with resistances, associated measures, walks and local times converge in a suitable Gromov-Hausdorff topology, we establish asymptotic bounds on the distribution of the…

Probability · Mathematics 2025-09-30 George Andriopoulos

We consider translation invariant measures on families of nearest-neighbor semi-infinite walks on the integer lattice. We assume that once walks meet, they coalesce. In $2d$, we classify the collective behavior of these walks under mild…

Probability · Mathematics 2019-01-01 Jon Chaika , Arjun Krishnan

We study geodesics in the Brownian map $(\mathcal{S},d,\nu)$, the random metric measure space which arises as the Gromov-Hausdorff scaling limit of uniformly random planar maps. Our results apply to all geodesics including those between…

Probability · Mathematics 2023-09-13 Jason Miller , Wei Qian

Stochastic gradient Langevin dynamics (SGLD) is a fundamental algorithm in stochastic optimization. Recent work by Zhang et al. [2017] presents an analysis for the hitting time of SGLD for the first and second order stationary points. The…

Machine Learning · Statistics 2020-03-17 Xi Chen , Simon S. Du , Xin T. Tong

Last passage percolation (LPP) is a model of a directed metric and a zero-temperature polymer where the main observable is a directed path evolving in a random environment accruing as energy the sum of the random weights along itself. When…

Probability · Mathematics 2025-01-07 Shirshendu Ganguly , Victor Ginsburg , Kyeongsik Nam

In dynamical critical site percolation on the triangular lattice or bond percolation on \Z^2, we define and study a local time measure on the exceptional times at which the origin is in an infinite cluster. We show that at a typical time…

Probability · Mathematics 2013-04-11 Alan Hammond , Gábor Pete , Oded Schramm

For first passage percolation (FPP) on integer lattice with i.i.d. passage time distributions, in order to show existence of semi-infinite geodesics along a fixed direction, one requires unproven assumptions on the limiting shape. We…

Probability · Mathematics 2017-07-12 Kumarjit Saha

In this paper, a class of statistics based on high frequency observations of oscillating and skew Brownian motion is considered. Their convergence rate towards the local time of the underlying process is obtained in form of a functional…

Probability · Mathematics 2024-04-04 Sara Mazzonetto

We present a novel geometric perspective on the latent space of diffusion models. We first show that the standard pullback approach, utilizing the deterministic probability flow ODE decoder, is fundamentally flawed. It provably forces…

Machine Learning · Computer Science 2026-02-27 Rafał Karczewski , Markus Heinonen , Alison Pouplin , Søren Hauberg , Vikas Garg
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