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Abstract axiomatic formulation of mathematical structures are extensively used to describe our physical world. We take here the reverse way. By making basic assumptions as starting point, we reconstruct some features of both geometry and…

History and Overview · Mathematics 2021-02-12 B. F. Rizzuti , L. M. Gaio , C. Duarte

Extending the notion of parallelism we introduce the concept of approximate parallelism in normed spaces and then substantially restrict ourselves to the setting of Hilbert space operators endowed with the operator norm. We present several…

Functional Analysis · Mathematics 2019-08-15 Mohammad Sal Moslehian , Ali Zamani

Computers calculate transcendental functions by approximating them through the composition of a few limited-precision instructions. For example, an exponential can be calculated with a Taylor series. These approximation methods were…

Neural and Evolutionary Computing · Computer Science 2023-12-15 Esteban Real , Yao Chen , Mirko Rossini , Connal de Souza , Manav Garg , Akhil Verghese , Moritz Firsching , Quoc V. Le , Ekin Dogus Cubuk , David H. Park

Two approximations, derived from continuous expansions of Riemann-Liouville fractional derivatives into series involving integer order derivatives, are studied. Using those series, one can formally transform any problem that contains…

Optimization and Control · Mathematics 2013-05-10 Shakoor Pooseh , Ricardo Almeida , Delfim F. M. Torres

Completing Loo-Keng Hua's approach to the real number system pioneered in 1962, this paper defines arithmetical operations directly on infinite decimals without appealing to any ordering structure. Therefore, the widespread belief that…

Number Theory · Mathematics 2018-07-31 Nicolas Fardin , Liangpan Li

A new approach to normal operators in real Hilbert spaces is discussed, and a spectral representation is obtained, derived directly from the complex case. The results are then applied to quaternionic normal operators, regarded as a special…

Functional Analysis · Mathematics 2025-07-28 Florian-Horia Vasilescu

We consider solving a probably infinite dimensional operator equation, where the operator is not modeled by physical laws but is specified indirectly via training pairs of the input-output relation of the operator. Neural operators have…

Numerical Analysis · Mathematics 2026-05-06 Otmar Scherzer , Thi Lan Nhi Vu , Jikai Yan

For nearly any challenging scientific problem evaluation of the likelihood is problematic if not impossible. Approximate Bayesian computation (ABC) allows us to employ the whole Bayesian formalism to problems where we can use simulations…

Computation · Statistics 2011-07-04 Chris Barnes , Sarah Filippi , Michael P. H. Stumpf , Thomas Thorne

Quantum physics can only make statistical predictions about possible measurement outcomes, and these predictions originate from an operator algebra that is fundamentally different from the conventional definition of probability as a…

Quantum Physics · Physics 2020-06-11 Holger F. Hofmann

In this work we present a theoretical model for differentiable programming. We construct an algebraic language that encapsulates formal semantics of differentiable programs by way of Operational Calculus. The algebraic nature of Operational…

Formal Languages and Automata Theory · Computer Science 2019-01-08 Žiga Sajovic , Martin Vuk

We consider Hadamard fractional derivatives and integrals of variable fractional order. A new type of fractional operator, which we call the Hadamard-Marchaud fractional derivative, is also considered. The objective is to represent these…

Classical Analysis and ODEs · Mathematics 2015-03-17 Ricardo Almeida , Delfim F. M. Torres

We examine a variety of numerical methods that arise when considering dynamical systems in the context of physics-based simulations of deformable objects. Such problems arise in various applications, including animation, robotics, control…

Graphics · Computer Science 2021-08-19 Uri M. Ascher , Egor Larionov , Seung Heon Sheen , Dinesh K. Pai

We show that, in spite of a rather common opinion, quantum mechanics can be represented as an approximation of classical statistical mechanics. The approximation under consideration is based on the ordinary Taylor expansion of physical…

Statistical Mechanics · Physics 2009-11-11 Andrei Khrennikov

Families of operator identities appeared as a consequence of an existence of finite-dimensional representation of (super) Lie algebras of first-order differential operators and $q$-deformed (quantum) algebras of first-order…

High Energy Physics - Theory · Physics 2009-10-22 Alexander Turbiner , Gerhard Post

Advances in numerical optimization have supported breakthroughs in several areas of signal processing. This paper focuses on the recent enhanced variants of the proximal gradient numerical optimization algorithm, which combine quasi-Newton…

Signal Processing · Electrical Eng. & Systems 2020-01-28 Niccolò Antonello , Lorenzo Stella , Panagiotis Patrinos , Toon van Waterschoot

In this paper we introduce an enclosure of the numerical range of a class of rational operator functions. In contrast to the numerical range the presented enclosure can be computed exactly in the infinite dimensional case as well as in the…

Functional Analysis · Mathematics 2017-04-25 Christian Engström , Axel Torshage

In [S\'eries Gevrey de type arithm\'etique I Th\'eor\'emes de puret\'e et de dualit\'e, Annals of Math. 151 (2000), 705--740], Andr\'e has introduced E-operators, a class of differential operators intimately related to E-functions, and…

Number Theory · Mathematics 2014-06-24 Stephane Fischler , Tanguy Rivoal

A mathematical proposition with a trainable pair, operator and quantum circuit, are introduced to approximate functions expressed as cubic Taylor polynomials, numerical simulations illustrate three cases.

Quantum Physics · Physics 2018-04-03 Alberto Delgado

Recent results on the construction and applications of the transmutation (transformation) operators are discussed. Three new representations for solutions of the one-dimensional Schr\"odinger equation are considered. Due to the fact that…

Classical Analysis and ODEs · Mathematics 2017-08-03 Vladislav V. Kravchenko , Sergii M. Torba , Kira V. Khmelnytskaya

Approximate Bayesian computation performs approximate inference for models where likelihood computations are expensive or impossible. Instead simulations from the model are performed for various parameter values and accepted if they are…

Computation · Statistics 2015-12-16 Dennis Prangle
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