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We propose polynomial-time algorithms that sparsify planar and bounded-genus graphs while preserving optimal or near-optimal solutions to Steiner problems. Our main contribution is a polynomial-time algorithm that, given an unweighted graph…

Data Structures and Algorithms · Computer Science 2017-07-12 Marcin Pilipczuk , Michał Pilipczuk , Piotr Sankowski , Erik Jan van Leeuwen

In this paper, we investigate the trigonometric Heckman-Opdam polynomials of type $A_1$. We establish connections with ultraspherical polynomials and derive an explicit expression for the associated Poisson kernel. Using the product…

Classical Analysis and ODEs · Mathematics 2025-12-16 B. Amri , A. Guesmi

We use Stein's method to obtain bounds on the rate of convergence for a class of statistics in geometric probability obtained as a sum of contributions from Poisson points which are exponentially stabilizing, i.e. locally determined in a…

Probability · Mathematics 2007-05-23 Mathew D. Penrose , J. E. Yukich

We define the concept of higher order differential operators on a general noncommutative, nonassociative superalgebra A, and show that a vertex operator superalgebra has plenty of them, namely modes of vertex operators. A linear operator…

q-alg · Mathematics 2016-08-15 Füsun Akman

In this article, we derive Stein's method for approximating a spatial random graph by a generalised random geometric graph, which has vertices given by a finite Gibbs point process and edges based on a general connection function. Our main…

Probability · Mathematics 2024-11-06 Dominic Schuhmacher , Leoni Carla Wirth

If $S=<d_1,...,d_\nu>$ is a numerical semigroup, we call the ring $\C[S]=\C[t^{d_1},...,t^{d_\nu}]$ the semigroup ring of $S$. We study the ring of differential operators on $\C[S]$, and its associated graded in the filtration induced by…

Commutative Algebra · Mathematics 2011-09-29 Valentina Barucci , Ralf Fröberg

We introduce $\textit{Stein transport}$, a novel methodology for Bayesian inference designed to efficiently push an ensemble of particles along a predefined curve of tempered probability distributions. The driving vector field is chosen…

Machine Learning · Statistics 2024-12-02 Nikolas Nüsken

Stein variational gradient descent (SVGD) is a deterministic sampling algorithm that iteratively transports a set of particles to approximate given distributions, based on an efficient gradient-based update that guarantees to optimally…

Machine Learning · Statistics 2017-11-15 Qiang Liu

Stein variational gradient descent (SVGD) was recently proposed as a general purpose nonparametric variational inference algorithm [Liu & Wang, NIPS 2016]: it minimizes the Kullback-Leibler divergence between the target distribution and its…

Machine Learning · Statistics 2018-10-31 Gianluca Detommaso , Tiangang Cui , Alessio Spantini , Youssef Marzouk , Robert Scheichl

New ladder operators are constructed for a rational extension of the harmonic oscillator associated with type III Hermite exceptional orthogonal polynomials and characterized by an even integer $m$. The eigenstates of the Hamiltonian…

Mathematical Physics · Physics 2015-06-15 I. Marquette , C. Quesne

In this paper we establish $L^p$ boundedness properties for maximal operators, Littlewood-Paley functions and variation operators involving Poisson semigroups and resolvent operators associated with nonsymmetric Ornstein-Uhlenbeck…

Classical Analysis and ODEs · Mathematics 2022-02-01 Víctor Almeida , Jorge J. Betancor , Pablo Quijano , Lourdes Rodríguez-Mesa

We consider an algebra $\mathscr A$ of Fourier integral operators on $\mathbb R^n$. It consists of all operators $D: \mathscr S(\mathbb R^n)\to \mathscr S(\mathbb R^n)$ on the Schwartz space $\mathscr S(\mathbb R^n)$ that can be written as…

Operator Algebras · Mathematics 2024-05-29 Anton Savin , Elmar Schrohe

We obtain a Stein characterisation of the distribution of the product of two correlated normal random variables with non-zero means, and more generally the distribution of the sum of independent copies of such random variables. Our Stein…

Probability · Mathematics 2024-09-11 Robert E. Gaunt , Siqi Li , Heather L. Sutcliffe

We introduce the general polynomial algebras characterizing a class of higher order superintegrable systems that separate in Cartesian coordinates. The construction relies on underlying polynomial Heisenberg algebras and their defining…

Mathematical Physics · Physics 2023-07-20 Danilo Latini , Ian Marquette , Yao-Zhong Zhang

We compute explicit bounds in the Gaussian approximation of functionals of infinite Rademacher sequences. Our tools involve Stein's method, as well as the use of appropriate discrete Malliavin operators. Although our approach does not…

Probability · Mathematics 2009-05-21 Ivan Nourdin , Giovanni Peccati , Gesine Reinert

The art of quantum algorithm design is highly nontrivial. Grover's search algorithm constitutes a masterpiece of quantum computational software. In this article, we use methods of geometric algebra (GA) and information geometry (IG) to…

Quantum Physics · Physics 2017-02-01 Carlo Cafaro

We establish inequalities for assessing the distance between the distribution of errors of partially observed high-frequency statistics of multidimensional L\'evy processes and that of a mixed Gaussian random variable. Furthermore, we…

Probability · Mathematics 2025-04-14 Chiara Amorino , Arturo Jaramillo , Mark Podolskij

We give an algebraic/geometric characterization of the classical pseudodifferential operators on a smooth manifold in terms of the tangent groupoid and its natural $\mathbb{R}^\times_+$-action. Specifically, we show that a properly…

Differential Geometry · Mathematics 2017-07-28 Erik Van Erp , Robert Yuncken

It will be shown here that there are differential operators $E,F$ and $H=[E,F]$ for each $n\ge 1$, acting on Diagonal Harmonics, yielding that $DH_n$ is a representation of $sl[2]$ (see [3] Chapter 3). Our main effort here is to use $sl[2]$…

Combinatorics · Mathematics 2022-04-20 Adriano Garsia , Mike Zabrocki

Motivated by questions in quantum theory, we study Hilbert space valued Gaussian processes, and operator-valued kernels, i.e., kernels taking values in B(H) (= all bounded linear operators in a fixed Hilbert space H). We begin with a…

Functional Analysis · Mathematics 2024-08-21 Palle E. T. Jorgensen , James Tian