English
Related papers

Related papers: Gaussian random permutation and the boson point pr…

200 papers

We study spatial permutations with cycle weights that are bounded or slowly diverging. We show that a phase transition occurs at an explicit critical density. The long cycles are macroscopic and their cycle lengths satisfy a…

Probability · Mathematics 2012-05-01 Volker Betz , Daniel Ueltschi

We consider a finite sequence of random points in a finite domain of a finite-dimensional Euclidean space. The points are sequentially allocated in the domain according to a model of cooperative sequential adsorption. The main peculiarity…

Probability · Mathematics 2009-11-11 V. Shcherbakov

We study invasion percolation on Aldous' Poisson-weighted infinite tree, and derive two distinct Markovian representations of the resulting process. One of these is the $\sigma\to\infty$ limit of a representation discovered by Angel et al.…

Probability · Mathematics 2012-10-05 Louigi Addario-Berry , Simon Griffiths , Ross J. Kang

Random walk is an explainable approach for modeling natural processes at the molecular level. The Random Permutation Set Theory (RPST) serves as a framework for uncertainty reasoning, extending the applicability of Dempster-Shafer Theory.…

Artificial Intelligence · Computer Science 2024-09-27 Jiefeng Zhou , Zhen Li , Yong Deng

Consider the point process (in $\mathbb{R}^d$) of local maxima of smooth Gaussian fields, with sufficient decay of correlation at infinity, above a level $u$. We show that this point process, rescaled appropriately, converges weakly to a…

Probability · Mathematics 2026-02-25 Dmitry Beliaev , Akshay Hegde

The study of spectrum statistics, such as the consecutive-gap ratio distribution, has revealed many interesting properties of many-body complex systems. Here we propose a two-parameter surmise expression for such distribution to describe…

Disordered Systems and Neural Networks · Physics 2025-12-18 Gerson C. Duarte-Filho , Julian Siegl , John Schliemann , J. Carlos Egues

We consider the statistical properties of the gravitational field F in an infinite one-dimensional homogeneous Poisson distribution of particles, using an exponential cut-off of the pair interaction to control and study the divergences…

Statistical Mechanics · Physics 2015-05-14 Andrea Gabrielli , Michael Joyce

We give a dimension-independent sparsification result for suprema of centered Gaussian processes: Let $T$ be any (possibly infinite) bounded set of vectors in $\mathbb{R}^n$, and let $\{\boldsymbol{X}_t := t \cdot \boldsymbol{g} \}_{t\in…

Machine Learning · Statistics 2025-11-11 Anindya De , Shivam Nadimpalli , Ryan O'Donnell , Rocco A. Servedio

Under the assumption of two fluid kinematics of a nonrelativistic Bose liquid in the presence of a local velocity field $v(x)$, local Galilei transformations are used to derive formulas for the spatial distribution of superfluidity. The…

Quantum Physics · Physics 2018-08-01 T. J. Volkoff , Yongkyung Kwon

Gaussian Multiplicative Chaos (GMC) is informally defined as a random measure $e^{\gamma X} \mathrm{d} x$ where $X$ is Gaussian field on $\mathbb R^d$ (or an open subset of it) whose correlation function is of the form $ K(x,y)= \log…

Probability · Mathematics 2020-12-23 Hubert Lacoin

Let $\alpha$ and $\beta$ be uniformly random permutations of orders $2$ and $3$, respectively, in $S_{N}$, and consider, say, the permutation $\alpha\beta\alpha\beta^{-1}$. How many fixed points does this random permutation have on average?…

Group Theory · Mathematics 2022-12-07 Doron Puder , Tomer Zimhoni

In this paper, we propose a data based transformation for infinite-dimensional Gaussian processes and derive its limit theorem. For a classification problem, this transformation induces complete separation among the associated Gaussian…

Statistics Theory · Mathematics 2022-03-25 Juan A. Cuesta-Albertos , Subhajit Dutta

Aggregation patterns are often visually detected in sets of location data. These clusters may be the result of interesting dynamics or the effect of pure randomness. We build an asymptotically Gaussian test for the hypothesis of randomness…

Methodology · Statistics 2010-06-09 Gabriel Lang , Eric Marcon

Several stochastic processes related to transient L\'evy processes with potential densities $u(x,y)=u(y-x)$, that need not be symmetric nor bounded on the diagonal, are defined and studied. They are real valued processes on a space of…

Probability · Mathematics 2013-11-11 Yves Le Jan , Michael B. Marcus , Jay Rosen

One of the main problems in the studies of large scale galaxy structures concerns the relation of the correlation properties of a certain population of objects with those of a selected subsample of it, when the selection is performed by…

Astrophysics · Physics 2007-05-23 Francesco Sylos Labini

We consider the multi-time correlation and covariance structure of a random surface growth with a wall introduced in arXiv:0904.2607. It is shown that the correlation functions associated with the model along space-like paths have…

Probability · Mathematics 2022-03-31 Zhengye Zhou

Let $\Delta\subsetneq\V$ be a proper subset of the vertices $\V$ of the defining graph of an irreducible and aperiodic shift of finite type $(\Sigma_{A}^{+},\S)$. Let $\Sigma_{\Delta}$ be the subshift of allowable paths in the graph of…

Dynamical Systems · Mathematics 2008-04-17 J. -R. Chazottes , Z. Coelho , P. Collet

Proofs of sharp phase transition and noise sensitivity in percolation have been significantly simplified by the use of randomized algorithms, via the OSSS inequality (proved by O'Donnell, Saks, Schramm and Servedio (2005)) and the…

Probability · Mathematics 2022-09-22 Günter Last , Giovanni Peccati , D. Yogeshwaran

A universal quantum computer of large scale is not available yet, however, intermediate models of quantum computation would still permit demonstrations of a quantum computational advantage over classical computing and could challenge the…

Quantum Physics · Physics 2024-11-15 Raphael A. Abrahao , Arman Mansouri , Austin P. Lund

Gaussian process regression is a powerful Bayesian nonlinear regression method. Recent research has enabled the capture of many types of observations using non-Gaussian likelihoods. To deal with various tasks in spatial modeling, we benefit…

Machine Learning · Statistics 2025-08-26 Yuta Shikuri