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We establish the universal edge scaling limit of random partitions with the infinite-parameter distribution called the Schur measure. We explore the asymptotic behavior of the wave function, which is a building block of the corresponding…

Statistical Mechanics · Physics 2021-05-12 Taro Kimura , Ali Zahabi

We discuss the propagation of scalars in a large class of non-extremal black hole and black p-brane geometries in generic dimensions. We show that the radial wave equation near the horizon possesses the SL(2,R) structure in every case;…

High Energy Physics - Theory · Physics 2016-08-25 Yuji Satoh

A recently proposed generalised continuum theory of curved dislocations describes the spatial and temporal evolution of statistically stored and geometrically necessary dislocation densities as well as the curvature. The dynamics follow…

Materials Science · Physics 2026-01-13 István Groma , Dénes Berta , Lóránt Sándli , Péter Dusán Ispánovity

We propose a new theoretical framework that exploits convolution kernels to transform a Volterra-type path-dependent (non-Markovian) stochastic process into a standard (Markovian) diffusion process. Remarkably, it is also possible to go…

Mathematical Finance · Quantitative Finance 2025-10-10 Ofelia Bonesini , Giorgia Callegaro , Martino Grasselli , Gilles Pagès

In the present study we examine non-Gaussian spreading of solutes subject to advection, dispersion and kinetic sorption (adsorption/desorption). We start considering the behavior of a single particle and apply a random walk to describe…

Probability · Mathematics 2011-01-14 Gerard Uffink , Amro Elfeki , Michel Dekking , Johannes Bruining , Cor Kraaikamp

The nonlinear diffusion equation $\frac{\partial \rho}{\partial t}=D \tilde{\Delta} \rho^\nu$ is analyzed here, where $\tilde{\Delta}\equiv \frac{1}{r^{d-1}}\frac{\partial}{\partial r} r^{d-1-\theta} \frac{\partial}{\partial r}$, and $d$,…

Statistical Mechanics · Physics 2009-10-31 L. C. Malacarne , R. S. Mendes , I. T. Pedron , E. K. Lenzi

We calculate the spectral dimension of a wide class of tree-like fractals by solving the random walk problem through a new analytical technique, based on invariance under generalized cutting-decimation transformations. These fractals are…

Statistical Mechanics · Physics 2009-10-30 Raffaella Burioni , Davide Cassi , Alberto Pirati , Sofia Regina

Finding the mode of a high dimensional probability distribution $D$ is a fundamental algorithmic problem in statistics and data analysis. There has been particular interest in efficient methods for solving the problem when $D$ is…

Machine Learning · Computer Science 2023-06-05 Xinyu Luo , Christopher Musco , Cas Widdershoven

In a recent string theory motivated paper, Nicolini, Smailagic and Spallucci (NSS) presented an interesting model for a noncommutative inspired, Schwarzschild-like black hole solution in 4-dimensions. The essential effect of having…

High Energy Physics - Phenomenology · Physics 2009-11-11 Thomas G. Rizzo

The modeling of coupled-channel effects has become increasingly important due to the availability of highly precise data for a large variety of hadronic (re)scattering processes. The K-matrix is a powerful, yet comparatively simple, method…

High Energy Physics - Phenomenology · Physics 2026-01-16 Nils Hüsken , Eric S. Swanson , Adam Szczepaniak

We study the problem of distributional approximations to high-dimensional non-degenerate $U$-statistics with random kernels of diverging orders. Infinite-order $U$-statistics (IOUS) are a useful tool for constructing simultaneous prediction…

Statistics Theory · Mathematics 2019-12-11 Yanglei Song , Xiaohui Chen , Kengo Kato

We consider the defocusing nonlinear Schr{\"o}dinger equation with a gauge invariant power-like nonlinearity. We prove global dispersive estimates in a semi-classical scaling, after rescaling the solution thanks to a suitable distorsion of…

Analysis of PDEs · Mathematics 2020-12-16 Rémi Carles

We provide finite-particle convergence rates for the Stein Variational Gradient Descent (SVGD) algorithm in the Kernelized Stein Discrepancy ($\mathsf{KSD}$) and Wasserstein-2 metrics. Our key insight is that the time derivative of the…

Statistics Theory · Mathematics 2025-06-10 Sayan Banerjee , Krishnakumar Balasubramanian , Promit Ghosal

A central challenge in Bayesian inference is efficiently approximating posterior distributions. Stein Variational Gradient Descent (SVGD) is a popular variational inference method which transports a set of particles to approximate a target…

Machine Learning · Statistics 2025-12-05 Moritz Melcher , Simon Weissmann , Ashia C. Wilson , Jakob Zech

In this paper, we derive rigorously a non-local cross-diffusion system from an interacting stochastic many-particle system in the whole space. The convergence is proved in the sense of probability by introducing an intermediate particle…

Probability · Mathematics 2023-08-22 Yue Li , Li Chen , Zhipeng Zhang

Kernel density estimation (KDE) is a popular statistical technique for estimating the underlying density distribution with minimal assumptions. Although they can be shown to achieve asymptotic estimation optimality for any input…

Computation · Statistics 2011-02-15 Dongryeol Lee , Alexander G. Gray , Andrew W. Moore

Riemannian diffusion models draw inspiration from standard Euclidean space diffusion models to learn distributions on general manifolds. Unfortunately, the additional geometric complexity renders the diffusion transition term inexpressible…

Machine Learning · Computer Science 2023-11-01 Aaron Lou , Minkai Xu , Stefano Ermon

The separated radial part of a sourceless massive complex scalar field equation on the Kerr-Newman black hole background is shown to be a generalized spin-weighted spheroidal wave equation of imaginary number order. While the separated…

General Relativity and Quantum Cosmology · Physics 2015-06-25 S. Q. Wu , X. Cai

In this article, using kernel convolution of order based dependent Dirichlet process (Griffin and Steel (2006)) we construct a nonstationary, nonseparable, nonparametric space-time process, which, as we show, satisfies desirable properties,…

Methodology · Statistics 2020-05-04 Moumita Das , Sourabh Bhattacharya

We consider the mass-dependent aggregation process (k+1)X -> X, given a fixed number of unit mass particles in the initial state. One cluster is chosen proportional to its mass and is merged into one either with k-neighbors in one…

Data Analysis, Statistics and Probability · Physics 2011-11-02 Seung-Woo Son , Claire Christensen , Golnoosh Bizhani , Peter Grassberger , Maya Paczuski