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Loading functions into quantum computers represents an essential step in several quantum algorithms, such as quantum partial differential equation solvers. Therefore, the inefficiency of this process leads to a major bottleneck for the…

Quantum Physics · Physics 2024-03-28 Javier Gonzalez-Conde , Thomas W. Watts , Pablo Rodriguez-Grasa , Mikel Sanz

A simple proof is given of the known fact that an m-times continuously differentiable function on the real line can be approximated along with its derivatives by an entire function and its respective derivatives.

Complex Variables · Mathematics 2019-08-15 Paul M. Gauthier , Julie Kienzle

Quantum computation has received great attention in recent years for its possible application to difficult problem in classical calculation. Despite the experimental problems of implementing quantum devices, theoretical physicists have…

Quantum Physics · Physics 2007-05-23 G. Florio , D. Picca

In this article, we compare the methods implementing the real-time evolution operator generated by a unitary diagonal matrix where its entries obey a known underlying real function. When the size of the unitary diagonal matrix is small, a…

Quantum Physics · Physics 2025-03-18 Xinchi Huang , Taichi Kosugi , Hirofumi Nishi , Yu-ichiro Matsushita

In the context of data-driven control of nonlinear systems, many approaches lack of rigorous guarantees, call for nonconvex optimization, or require knowledge of a function basis containing the system dynamics. To tackle these drawbacks, we…

Systems and Control · Electrical Eng. & Systems 2023-10-05 Tim Martin , Frank Allgöwer

Approximate computing is a research area where we investigate a wide spectrum of techniques to trade off computation accuracy for better performance or energy consumption. In this work, we provide a general introduction to approximate…

Programming Languages · Computer Science 2017-12-12 M. Ammar Ben Khadra

A typical quantum experiment has a bunch of apparatuses placed so that quantum systems can pass between them. We regard each use of an apparatus, along with some given outcome on the apparatus (a certain detector click or a certain meter…

Quantum Physics · Physics 2015-06-03 Lucien Hardy

Recent years have witnessed the introduction and development of extremely fast rational function algorithms. Many ideas in this realm arose from polynomial-based linear-algebraic algorithms. However, polynomial approximation is occasionally…

Numerical Analysis · Mathematics 2025-10-03 James Chok , Geoffrey M. Vasil

The problem of reconstructing functions from their asymptotic expansions in powers of a small variable is addressed by deriving a novel type of approximants. The derivation is based on the self-similar approximation theory, which presents…

Statistical Mechanics · Physics 2009-11-07 S. Gluzman , V. I. Yukalov , D. Sornette

Generalizations of some known results on the best, best linear and best one-sided approxima- tions by trigonometric polynomials of the classes of 2\pi - periodic functions presented in the form of convolutions to the case of set-valued…

Functional Analysis · Mathematics 2015-04-29 V. F. Babenko , V. V. Babenko , M. V. Polischuk

Recently, it has been presented some algorithms and physical models which give prospects for construction of quantum computers capable to solve systems of linear equations. The common feature which is shared in these works is the use of…

Quantum Physics · Physics 2013-09-04 Marek Sawerwain , Wiesław Leoński

The Operator axioms have produced new real numbers with new operators. New operators naturally produce new equations and thus extend the traditional mathematical models which are selected to describe various scientific rules. So new…

Numerical Analysis · Computer Science 2021-02-08 Pith Peishu Xie

Quantum Iterated Function System on a complex projective space is defined by a family of linear operators on a complex Hilbert space. The operators define both the maps and their probabilities by one algebraic formula. Examples with…

Chaotic Dynamics · Physics 2009-11-10 Arkadiusz Jadczyk

Quantum computers promise to revolutionise electronic simulations by overcoming the exponential scaling of many-electron problems. While electronic wave functions can be represented using a product of fermionic unitary operators, shallow…

Quantum Physics · Physics 2022-07-04 Hugh G. A. Burton , Daniel Marti-Dafcik , David P. Tew , David J. Wales

We study the question of the existence of a dual extremal function for a bounded matrix function on the unit circle in connection with the problem of approximation by analytic matrix functions. We characterize the class of matrix functions,…

Functional Analysis · Mathematics 2008-01-03 V. V. Peller

Functions with singularities are notoriously difficult to approximate with conventional approximation schemes. In computational applications, they are often resolved with low-order piecewise polynomials, multilevel schemes, or other types…

Numerical Analysis · Mathematics 2024-07-30 Nicolas Boullé , Astrid Herremans , Daan Huybrechs

We determine the Lagrange function in Taylor polynomial approximation by solving an appropriate initial-value problem. Hence, we determine the remainder term which we then approximate by means of a natural cubic spline. This results in a…

Numerical Analysis · Mathematics 2023-03-06 J. S. C. Prentice

Some mathematical models of applied problems lead to the need of solving boundary value problems with a fractional power of an elliptic operator. In a number of works, approximations of such a nonlocal operator are constructed on the basis…

Numerical Analysis · Computer Science 2019-05-28 Petr N. Vabishchevich

The analogue of Kontsevich's matrix Airy function, with the cubic potential $\operatorname{Tr}\big(\Phi^3\big)$ replaced by a quartic term $\operatorname{Tr}\big(\Phi^4\big)$ with the same covariance, provides a toy model for quantum field…

Mathematical Physics · Physics 2021-09-17 Johannes Branahl , Alexander Hock , Raimar Wulkenhaar

Tame functions are a class of nonsmooth, nonconvex functions, which feature in a wide range of applications: functions encountered in the training of deep neural networks with all common activations, value functions of mixed-integer…

Optimization and Control · Mathematics 2024-06-05 Gilles Bareilles , Johannes Aspman , Jiri Nemecek , Jakub Marecek
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