English
Related papers

Related papers: Bures distance and transition probability for $\al…

200 papers

On a W*-algebra M, for given two positive linear forms f,g and algebra elements a,b a variational expression for the Bures-distance d_B(f^a,g^b) between the inner derived positive linear forms f^a=f(a* . a) and g^b=g(b* . b) is obtained.…

Mathematical Physics · Physics 2015-11-18 Peter M. Alberti , Armin Uhlmann

If the symmetry, (an operator $J$ satisfying $J=J^*=J^{-1}$) which defines the Krein space, is replaced by a (not necessarily self-adjoint) unitary, then we have the notion of an $S$-space which was introduced by Szafraniec. In this paper,…

Functional Analysis · Mathematics 2024-04-30 Priyabrata Bag , Azad Rohilla , Harsh Trivedi

We study positive definiteness of kernels $K(x,y)$ on two-point homogeneous spaces. As opposed to the classical case, which has been developed and studied in the existing literature, we allow the kernel to have an (integrable) singularity…

Classical Analysis and ODEs · Mathematics 2024-10-30 Dmitriy Bilyk , Peter Grabner

In this article we study the field of Hilbertian metrics and positive definit (pd) kernels on probability measures, they have a real interest in kernel methods. Firstly we will make a study based on the Alpha-Beta-divergence to have a…

Methodology · Statistics 2018-09-18 Mactar Ndaw , Macoumba Ndour , Papa Ngom

We derive simple and unified closed-form expressions for projections with respect to fidelity (equivalently, the Bures and purified distances) onto several sets of interest. These include projections of bipartite positive semidefinite (PSD)…

Quantum Physics · Physics 2026-02-17 A. Afham , Marco Tomamichel

This document reviews the definition of the kernel distance, providing a gentle introduction tailored to a reader with background in theoretical computer science, but limited exposure to technology more common to machine learning,…

Computational Geometry · Computer Science 2011-03-11 Jeff M. Phillips , Suresh Venkatasubramanian

D. Bures had defined a metric on the set of normal states on a von Neumann algebra using GNS representations of states. This notion has been extended to completely positive maps between $C^*$-algebras by D. Kretschmann, D. Schlingemann and…

Operator Algebras · Mathematics 2013-05-02 B. V. Rajarama Bhat , K. Sumesh

The geometry of spaces with indefinite inner product, known also as Krein spaces, is a basic tool for developing Operator Theory therein. In the present paper we establish a link between this geometry and the algebraic theory of…

Functional Analysis · Mathematics 2009-07-08 Franciszek Hugon Szafraniec , Michal Wojtylak

Starting with a similarity function between objects, it is possible to define a distance metric on pairs of objects, and more generally on probability distributions over them. These distance metrics have a deep basis in functional analysis,…

Computational Geometry · Computer Science 2011-03-15 Sarang Joshi , Raj Varma Kommaraju , Jeff M. Phillips , Suresh Venkatasubramanian

This paper studies transition probabilities from a Borel subset of a Polish space to a product of two Borel subsets of Polish spaces. For such transition probabilities it introduces and studies the property of semi-uniform Feller…

Probability · Mathematics 2023-01-09 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

We prove that kernel covariance embeddings lead to information-theoretically perfect separation of distinct continuous probability distributions. In statistical terms, we establish that testing for the \emph{equality} of two non-atomic…

Machine Learning · Statistics 2026-05-14 Leonardo V. Santoro , Kartik G. Waghmare , Victor M. Panaretos

We study cubic differentials and their spectral networks on Riemann surfaces, focusing on the polynomial case on the Riemann sphere. We introduce the notion of spectral core as the primary tool for our study, refining the classical notion…

Algebraic Geometry · Mathematics 2025-07-11 Omar Kidwai , Guillaume Tahar

We study a category of probability spaces and measure-preserving Markov kernels up to almost sure equality. This category contains, among its isomorphisms, mod-zero isomorphisms of probability spaces. It also gives an isomorphism between…

Probability · Mathematics 2025-08-05 Noé Ensarguet , Paolo Perrone

We investigate the notion of conditionally positive definite in the context of Hilbert $C^*$-modules and present a characterization of the conditionally positive definiteness in terms of the usual positive definiteness. We give a Kolmogorov…

Operator Algebras · Mathematics 2017-09-26 Mohammad Sal Moslehian

We introduce a natural concept of positive definiteness for bundle maps between Fell bundles over (possibly different) discrete groups and describe several examples. Such maps induce completely positive maps between the associated full…

Operator Algebras · Mathematics 2025-07-03 Erik Bédos , Roberto Conti

Let $A$ be a unital $C^*$-algebra and $H$ a Hilbert space. The cone $\CP(A,B(H))$ of completely positive maps carries the Bures metric $\beta$, closely related to the cb-norm. We introduce a family of Bures--Kuratowski (BK) metrics on…

Operator Algebras · Mathematics 2026-04-07 Remus Floricel , Sarah Plosker , Avner Sadikov

A mesh-free numerical method for solving linear elliptic PDE's using the local kernel theory that was developed for manifold learning is proposed. In particular, this novel approach exploits the local kernel theory which allows one to…

Numerical Analysis · Mathematics 2019-07-02 Faheem Gilani , John Harlim

We prove a number of results to the general effect that, under obviously necessary numerical and determinant constraints, "most" morphisms between fixed bundles on a complex elliptic curve produce (co)kernels which can either be specified…

Algebraic Geometry · Mathematics 2024-07-11 Alexandru Chirvasitu

In this paper we investigate the approximation properties of kernel interpolants on manifolds. The kernels we consider will be obtained by the restriction of positive definite kernels on $\R^d$, such as radial basis functions (RBFs), to a…

Functional Analysis · Mathematics 2011-01-19 Edward Fuselier , Grady Wright

In this work, we construct an explicit, theoretically rigorous deconvolution method that relies entirely on iterative forward convolutions, thus can be numerically implemented. We first prove that convolution with an even Schwartz kernel…

Signal Processing · Electrical Eng. & Systems 2026-04-20 Alfredo González-Calvin
‹ Prev 1 2 3 10 Next ›