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The core of quantum tomography is the possibility of writing a generally unbounded complex operator in form of an expansion over operators that are generally nonlinear functions of a generally continuous set of spectral densities--the…

Quantum Physics · Physics 2015-05-13 G. M. D'Ariano , M. F. Sacchi

This paper studies the diameter of the numerical range of bounded operators on Hilbert space and the induced seminorm, called the numerical diameter, on bounded linear maps between operator systems which is sensible in the case of unital…

Functional Analysis · Mathematics 2024-07-03 Niel de Beaudrap , Christopher Ramsey

We extend a number of results from one dimensional dynamics based on spectral properties of the Ruelle-Perron-Frobenius transfer operator to Anosov diffeomorphisms on compact manifolds. This allows to develop a direct operator approach to…

Chaotic Dynamics · Physics 2009-11-07 Michael Blank , Gerhard Keller , Carlangelo Liverani

This paper presents a novel Koopman composition operator representation framework for control systems in reproducing kernel Hilbert spaces (RKHSs) that is free of explicit dictionary or input parametrizations. By establishing fundamental…

Systems and Control · Electrical Eng. & Systems 2025-09-03 Petar Bevanda , Bas Driessen , Lucian Cristian Iacob , Stefan Sosnowski , Roland Tóth , Sandra Hirche

In this paper, we investigate the multilinear boundedness properties of the higher ($n$-th) order Calder\'on commutator for dimensions larger than two. We establish all multilinear endpoint estimates for the target space…

Classical Analysis and ODEs · Mathematics 2018-08-02 Xudong Lai

The manifold hypothesis suggests that the generalization performance of machine learning methods improves significantly when the intrinsic dimension of the input distribution's support is low. In the context of KRR, we investigate two…

Machine Learning · Computer Science 2026-01-23 Rustem Takhanov

Resolvents of quasi-linear operators and operator algebras in Banach spaces over the quaternion field are investigated. Spectral theory of unbounded nonlinear operators in quaternion Banach spaces is studied. Strongly continuous semigroups…

Operator Algebras · Mathematics 2018-12-18 S. V. Ludkovsky

The concepts of controlled frames and it's dual in n-Hilbert spaces and their tensor products have been introduced and then some of their characterizations are given. We further study the relationship between controlled frame and bounded…

Functional Analysis · Mathematics 2021-09-06 Prasenjit Ghosh , T. K. Samanta

This article investigates the approximate controllability of second order non-autonomous functional evolution equations involving non-instantaneous impulses and nonlocal conditions. First, we discuss the approximate controllability of…

Optimization and Control · Mathematics 2022-01-03 Sumit Arora , Soniya Singh , Manil T. Mohan , Jaydev Dabas

The spatial distribution has been widely used to develop various nonparametric procedures for finite dimensional multivariate data. In this paper, we investigate the concept of spatial distribution for data in infinite dimensional Banach…

Methodology · Statistics 2014-07-04 Anirvan Chakraborty , Probal Chaudhuri

We examine nonlinear Kolmogorov partial differential equations (PDEs). Here the nonlinear part of the PDE comes from its Hamiltonian where one maximizes over all possible drift and diffusion coefficients which fall within a…

Numerical Analysis · Mathematics 2026-04-15 Daniel Bartl , Ariel Neufeld , Kyunghyun Park

The Kolmogorov $N$-width $d_N(\mathcal{M})$ describes the rate of the worst-case error (w.r.t.\ a subset $\mathcal{M}\subset H$ of a normed space $H$) arising from a projection onto the best-possible linear subspace of $H$ of dimension…

Numerical Analysis · Mathematics 2019-04-11 Constantin Greif , Karsten Urban

We prove an inequality for the entropy numbers in terms of nonlinear Kolmogorov's widths. This inequality is in a spirit of known inequalities of this type and it is adjusted to the form convenient in applications for $m$-term…

Metric Geometry · Mathematics 2013-02-01 Vladimir Temlyakov

Learning operators between infinitely dimensional spaces is an important learning task arising in wide applications in machine learning, imaging science, mathematical modeling and simulations, etc. This paper studies the nonparametric…

Machine Learning · Statistics 2022-01-04 Hao Liu , Haizhao Yang , Minshuo Chen , Tuo Zhao , Wenjing Liao

The Koopman operator is a mathematical tool that allows for a linear description of non-linear systems, but working in infinite dimensional spaces. Dynamic Mode Decomposition and Extended Dynamic Mode Decomposition are amongst the most…

Machine Learning · Computer Science 2021-03-26 Francesco Zanini , Alessandro Chiuso

Quantum phenomena of interest in connection with applications to computation and communication almost always involve generating specific transfers between eigenstates, and their linear superpositions. For some quantum systems, such as spin…

Quantum Physics · Physics 2016-11-18 A. M. Bloch , R. W. Brockett , C. Rangan

A set of n non-collinear points in the Euclidean plane defines at least n different lines. Chen and Chv\'tal in 2008 conjectured that the same results is true in metric spaces for an adequate definition of line. More recently, it was…

Combinatorics · Mathematics 2024-10-30 Gabriela Araujo-Pardo , Martín Matamala , Juan P. Peña , José Zamora

In this paper we obtain order estimates for the Kolmogorov widths of the set $B_{p_0}^m\cap \nu B_{p_1}^m$ in $l_q^m$; here $0\le n\le m/2$, $p_0>p_1$, $q<\infty$.

Functional Analysis · Mathematics 2020-07-10 A. A. Vasil'eva

We investigate discrete-time dynamical systems generated by an infinite-dimensional non-linear operator that maps the Banach space $l_1$ to itself. It is demonstrated that this operator possesses up to seven fixed points. By leveraging the…

Dynamical Systems · Mathematics 2024-02-26 U. R. Olimov , U. A. Rozikov

We study the universal approximation properties of transformers and neural integral operators for operators in Banach spaces. In particular, we show that the transformer architecture is a universal approximator of integral operators between…

Machine Learning · Computer Science 2026-04-28 Emanuele Zappala , Maryam Bagherian