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We consider second-order partial differential operators $H$ in divergence form on $\Ri^d$ with a positive-semidefinite, symmetric, matrix $C$ of real $L_\infty$-coefficients and establish that $H$ is strongly elliptic if and only if the…

Analysis of PDEs · Mathematics 2007-05-23 A. F. M. ter Elst , Derek W. Robinson , Yueping Zhu

This paper develops and analyzes a fully discrete finite element method for a class of semilinear stochastic partial differential equations (SPDEs) with multiplicative noise. The nonlinearity in the diffusion term of the SPDEs is assumed to…

Numerical Analysis · Mathematics 2018-11-22 Xiaobing Feng , Yukun Li , Yi Zhang

Indistinguishability is an essential concept to understanding mysterious quantum features in the view point of the wave-particle duality of quantum mechanics. The fundamental physics of the indistinguishability lies in quantum superposition…

Quantum Physics · Physics 2022-06-10 Byoung S. Ham

We extend the quantum-mechanical results of Muller & Saunders (2008) establishing the weak discernibility of an arbitrary number of similar fermions in finite-dimensional Hilbert-spaces in two ways: (a) from fermions to bosons for all…

Quantum Physics · Physics 2009-11-10 F. A. Muller , M. P. Seevinck

The traditional kernel density estimator of an unknown density is by construction completely nonparametric, in the sense that it has no preferences and will work reasonably well for all shapes. The present paper develops a class of…

Methodology · Statistics 2026-05-05 Nils Lid Hjort , Ingrid Kristine Glad

We prove weak convergence in a separable Hilbert space for estimators of high-dimensional regression coefficients, which yields asymptotic normality and enables direct use of standard asymptotic tools such as the continuous mapping theorem.…

Statistics Theory · Mathematics 2026-05-05 Kou Fujimori , Koji Tsukuda

We assume that we observe $N$ independent copies of a diffusion process on a time-interval $[0,2T]$. For a given time $t$, we estimate the transition density $p_t(x,y)$, namely the conditional density of $X_{t + s}$ given $X_s = x$, under…

Statistics Theory · Mathematics 2025-05-01 Fabienne Comte , Nicolas Marie

We show that the frame measure function of a frame in certain reproducing kernel Hilbert spaces on metric measure spaces is given by the reciprocal of the Beurling density of its index set. In addition, we show that each such frame with…

Functional Analysis · Mathematics 2025-12-30 Marcin Bownik , Jordy Timo van Velthoven

The solution to nonlinear Fokker-Planck equation is constructed in terms of the minimal Markov semigroup generated by the equation. The semigroup is obtained by a purely functional analytical method via Hille-Yosida theorem. The existence…

Mathematical Physics · Physics 2007-05-23 Hong Qian , Min Qian , Xiang Tang

We consider diffusion processes in media with pockets of large diffusivity. The asymptotic behavior of such processes is described when the diffusion coefficients in the pockets tend to infinity. The limiting process is identified as a…

Probability · Mathematics 2017-10-11 Mark Freidlin , Leonid Koralov , Alexander Wentzell

Consider the following nonlocal integro-differential operator: for $\alpha\in(0,2)$, $$ \cal L^{(\alpha)}_{\sigma,b} f(x):=\mbox{p.v.} \int_{\mathbb{R}^d-\{0\}}\frac{f(x+\sigma(x)z)-f(x)}{|z|^{d+\alpha}}d z+b(x)\cdot\nabla f(x), $$ where…

Probability · Mathematics 2014-04-08 Xicheng Zhang

In this paper we consider the filtering of partially observed multi-dimensional diffusion processes that are observed regularly at discrete times. This is a challenging problem which requires the use of advanced numerical schemes based upon…

Numerical Analysis · Mathematics 2026-01-14 Ajay Jasra , Mohamed Maama , Hernando Ombao

Despite the success of the popular kernelized support vector machines, they have two major limitations: they are restricted to Positive Semi-Definite (PSD) kernels, and their training complexity scales at least quadratically with the size…

Machine Learning · Computer Science 2014-05-28 Omid Aghazadeh , Stefan Carlsson

We propose a new semiparametric approach for modelling nonlinear univariate diffusions, where the observed process is a nonparametric transformation of an underlying parametric diffusion (UPD). This modelling strategy yields a general class…

Econometrics · Economics 2020-05-08 Ruijun Bu , Kaddour Hadri , Dennis Kristensen

We establish necessary and sufficient conditions for stochastic invariance of closed subsets in Hilbert spaces for solutions to infinite-dimensional stochastic differential equations (SDEs) under mild assumptions on the coefficients. Our…

Probability · Mathematics 2026-02-24 Eduardo Abi Jaber , Stefan Tappe

Yor's generalized meander is a temporally inhomogeneous modification of the $2(\nu+1)$-dimensional Bessel process with $\nu > -1$, in which the inhomogeneity is indexed by $\kappa \in [0, 2(\nu+1))$. We introduce the non-colliding particle…

Probability · Mathematics 2007-05-23 Makoto Katori , Hideki Tanemura

We prove H\"older regularity for a general class of parabolic integro-differential equations, which (strictly) includes many previous results. We present a proof which avoids the use of a convex envelop as well as give a new covering…

Analysis of PDEs · Mathematics 2016-07-06 Russell W. Schwab , Luis Silvestre

We analyze a reaction coefficient identification problem for the spectral fractional powers of a symmetric, coercive, linear, elliptic, second-order operator in a bounded domain $\Omega$. We realize fractional diffusion as the…

Numerical Analysis · Mathematics 2019-05-01 Enrique Otarola , Tran Nhan Tam Quyen

Efficient simulation of stochastic partial differential equations (SPDE) on general domains requires noise discretization. This paper employs piecewise linear interpolation of noise in a fully discrete finite element approximation of a…

Numerical Analysis · Mathematics 2024-10-22 Gabriel Lord , Andreas Petersson

We propose a test for model specification of a parametric diffusion process based on a kernel estimation of the transitional density of the process. The empirical likelihood is used to formulate a statistic, for each kernel smoothing…

Statistics Theory · Mathematics 2009-09-29 Song Xi Chen , Jiti Gao , Cheng Yong Tang
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