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Motivated by the rapidly growing field of mathematics for operator approximation with neural networks, we present a novel universal operator approximation theorem for a broad class of encoder-decoder architectures. In this study, we focus…

Functional Analysis · Mathematics 2025-04-01 Janek Gödeke , Pascal Fernsel

We investigate the theory of finite observables, i.e., resolutions of the finite-dimensional identity by means of positive operators, that have a physical interpretation in terms of measurement schemes. We focus on extremal and rank-one…

Quantum Physics · Physics 2019-07-01 Heinz-Jürgen Schmidt

The problems of optimal recovery of unbounded operators are studied. Optimality means the highest possible accuracy and the minimal amount of discrete information involved. It is established that the truncation method, when certain…

Numerical Analysis · Mathematics 2025-05-13 Oleg Davydov , Sergei Solodky

This paper classifies the set of supersolutions of a general class of periodic-parabolic problems in the presence of a positive supersolution. From this result we characterize the positivity of the underlying resolvent operator through the…

Analysis of PDEs · Mathematics 2018-03-20 I Anton , J Lopez-Gomez

We introduce a notion of subunit vector field for fully nonlinear degenerate elliptic equations. We prove that an interior maximum of a viscosity subsolution of such an equation propagates along the trajectories of subunit vector fields.…

Analysis of PDEs · Mathematics 2018-12-27 Martino Bardi , Alessandro Goffi

We establish a coupled fixed points theorem for a meaningful class of mixed monotone multivalued operators and then we use it to derive some results on existence of quasisolutions and solutions to first--order functional differential…

Classical Analysis and ODEs · Mathematics 2011-04-13 Rubén Figueroa , Rodrigo López Pouso

In this paper, we derive sufficient and necessary maximum principles for a stochastic optimal control problem where the system state is given by a controlled stochastic differential equation with default. We prove existence of a unique…

Optimization and Control · Mathematics 2021-05-26 Khalida Bachir Cherif , Nacira Agram , Kristina Dahl

In recent years, considerable work has been done to tackle the issue of designing control laws based on observations to allow unknown dynamical systems to perform pre-specified tasks. At least as important for autonomy, however, is the…

Optimization and Control · Mathematics 2020-05-06 Luiz F. O. Chamon , Santiago Paternain , Alejandro Ribeiro

For an optimal control problem, the concept of a strong local infimum is introduce, for which necessary conditions consisting of some family of "maximum principles" are formulated. If a function delivers a strong local minimum in this…

Optimization and Control · Mathematics 2018-09-06 Evgeny Avakov , Georgii Magaril-Il'yaev

In this short note, we establish an operator theoretic version of the Wiener-Ikehara tauberian theorem, and point out how this leads to a new proof of the Prime number theorem that should be accessible to anyone with a basic knowledge of…

Functional Analysis · Mathematics 2020-11-16 Jan-Fredrik Olsen

An inconsistent knowledge base can be abstracted as a set of arguments and a defeat relation among them. There can be more than one consistent way to evaluate such an argumentation graph. Collective argument evaluation is the problem of…

Artificial Intelligence · Computer Science 2017-06-20 Edmond Awad , Martin Caminada , Gabriella Pigozzi , Mikołaj Podlaszewski , Iyad Rahwan

We study different maximum principles for non-local non-linear operators with non-standard growth that arise naturally in the context of fractional Orlicz-Sobolev spaces and whose most notable representative is the fractional $g-$Laplacian:…

Analysis of PDEs · Mathematics 2021-02-26 Sandra Molina , Ariel Salort , Hernán Vivas

Let $\mathcal{X}$ be a p-adic Hilbert space. Let $A:\mathcal{D}(A)\subseteq \mathcal{X}\to \mathcal{X}$ and $B: \mathcal{D}(B)\subseteq \mathcal{X}\to \mathcal{X}$ be possibly unbounded self-adjoint linear operators. For $x \in…

Functional Analysis · Mathematics 2026-01-21 K. Mahesh Krishna

The expectation value <O> of an arbitrary operator O can be obtained via a universal measuring apparatus that is independent of O, by changing only the data-processing of the outcomes. Such a ``universal detector'' performs a joint…

Quantum Physics · Physics 2007-05-23 G. M. D'Ariano , P. Perinotti , M. F. Sacchi

Ideas and formalisms from far-from-equilibrium thermodynamics are ported to the context of stochastic computational processes, via following and extending Tadaki's algorithmic thermodynamics. A Principle of Maximum Algorithmic Caliber is…

Artificial Intelligence · Computer Science 2020-05-12 Ben Goertzel

In this paper, we establish a general stochastic maximum principle for optimal control for systems described by a continuous-time Markov regime-switching stochastic recursive utilities model. The control domain is postulated not to be…

Optimization and Control · Mathematics 2019-05-02 Liangquan Zhang , Xun Li

In a recent paper we presented a general perturbation result for generators of $C_0$-semigroups. The aim of the present paper is to replace, in case the unperturbed semigroup is analytic, the various conditions appearing in this result by…

Functional Analysis · Mathematics 2015-05-07 Martin Adler , Miriam Bombieri , Klaus-Jochen Engel

We develop a systematic theory of eventually positive semigroups of linear operators mainly on spaces of continuous functions. By eventually positive we mean that for every positive initial condition the solution to the corresponding Cauchy…

Functional Analysis · Mathematics 2015-12-01 Daniel Daners , Jochen Glück , James B. Kennedy

This article is a contribution to the spectral theory of so-called eventually positive operators, i.e.\ operators $T$ which may not be positive but whose powers $T^n$ become positive for large enough $n$. While the spectral theory of such…

Spectral Theory · Mathematics 2016-09-28 Jochen Glück

In this paper, we address the adversarial training of neural ODEs from a robust control perspective. This is an alternative to the classical training via empirical risk minimization, and it is widely used to enforce reliable outcomes for…

Optimization and Control · Mathematics 2024-04-02 Cristina Cipriani , Alessandro Scagliotti , Tobias Wöhrer