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Bernstein's theorem (also called Hausdorff--Bernstein--Widder theorem) enables the integral representation of a completely monotonic function. We introduce a finite completely monotonic function, which is a completely monotonic function…

Numerical Analysis · Mathematics 2023-07-25 Yohei M. Koyama

It is shown that if a function defined on the segment [-1,1] has sufficiently good approximation by partial sums of the Legendre polynomial expansion, then, given the function's Fourier coefficients $c_n$ for some subset of $n\in[n_1,n_2]$,…

Number Theory · Mathematics 2010-08-31 Sergei N. Preobrazhenskii

The Brent-McMillan algorithm is the fastest known procedure for the high-precision computation of Euler's constant $\gamma$ and is based on the modified Bessel functions $I_0(2x)$ and $K_0(2x)$. An error estimate for this algorithm relies…

Classical Analysis and ODEs · Mathematics 2019-02-19 R B Paris

Expectation Propagation is a very popular algorithm for variational inference, but comes with few theoretical guarantees. In this article, we prove that the approximation errors made by EP can be bounded. Our bounds have an asymptotic…

Computation · Statistics 2016-01-12 Guillaume P Dehaene , Simon Barthelmé

Solutions to a wide variety of transcendental equations can be expressed in terms of the Lambert $\mathrm{W}$ function. The $\mathrm{W}$ function, occurring frequently in applications, is a non-elementary, but now standard mathematical…

Numerical Analysis · Mathematics 2021-05-21 Lajos Lóczi

We improve the error term in the van der Corput transform for exponential sums \sum_{a \le n \le b} g(n) exp(2\pi i f(n)). For many functions g and f, we can extract the next term in the asymptotic, showing that previous results, such as…

Number Theory · Mathematics 2012-05-02 Joseph Vandehey

A deep approximation is an approximating function defined by composing more than one layer of simple functions. We study deep approximations of functions of one variable using layers consisting of low-degree polynomials or simple conformal…

Numerical Analysis · Mathematics 2025-04-25 Kingsley Yeon

Two approximations of the integral of a class of sinusoidal composite functions, for which an explicit form does not exist, are derived. Numerical experiments show that the proposed approximations yield an error that does not depend on the…

Numerical Analysis · Mathematics 2024-01-17 Alberto Costa

A new method is presented for Fourier decomposition of the Helmholtz Green Function in cylindrical coordinates, which is equivalent to obtaining the solution of the Helmholtz equation for a general ring source. The Fourier coefficients of…

Mathematical Physics · Physics 2015-05-14 John T. Conway , Howard S. Cohl

We develop approximations for the Riemann zeta function that enable high-precision computation within the critical strip and other vertical strips. These approximations combine the main sum of the Riemann-Siegel formula with a simple…

Number Theory · Mathematics 2026-05-22 Alexey Kuznetsov

In this paper, we have proved four theorems on the degree of approximation of continuous functions by matrix means of their Fourier series which is expressed in terms of the modulus of continuity and a non-negative mediate function.

Classical Analysis and ODEs · Mathematics 2023-06-22 Xhevat Z. Krasniqi

We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functionals. We prove that the new algorithm is convergent if the functions considered are smooth enough, under a general assumption on the spectral…

Numerical Analysis · Mathematics 2012-07-17 Erwan Faou , Fabio Nobile , Christophe Vuillot

We improve the unconditional explicit bounds for the error term in the prime counting function $\psi(x)$. In particular, we prove that, for all $x>2$, we have \[ \left| \psi(x)-x \right| < 9.22106 \, x \, (\log x)^{3/2}…

Number Theory · Mathematics 2023-05-18 Andrew Fiori , Habiba Kadiri , Joshua Swidinsky

In this paper we present an algorithm to fit data via exponentials when the error is measured using the max-norm. We prove the necesssary results to show that the algorithm will converge to the best approximation no matter the dataset.

Exponential integrability properties of numerical approximations are a key tool for establishing positive rates of strong and numerically weak convergence for a large class of nonlinear stochastic differential equations. It turns out that…

Numerical Analysis · Mathematics 2020-08-10 Martin Hutzenthaler , Arnulf Jentzen , Xiaojie Wang

In the empirical study of evolutionary algorithms, the solution quality is evaluated by either the fitness value or approximation error. The latter measures the fitness difference between an approximation solution and the optimal solution.…

Neural and Evolutionary Computing · Computer Science 2018-10-30 Jun He , Yu Chen , Yuren Zhou

By combining and improving recent techniques and results, we provide explicit estimates for the error terms $|\pi(x)-\text{li}(x)|$, $|\theta(x)-x|$ and $|\psi(x)-x|$ appearing in the prime number theorem. For example, we show for all…

Number Theory · Mathematics 2022-04-21 Daniel R. Johnston , Andrew Yang

Recently, the present authors derived new asymptotic expansions for linear differential equations having a simple turning point. These involve Airy functions and slowly varying coefficient functions, and were simpler than previous…

Classical Analysis and ODEs · Mathematics 2020-04-28 T. M. Dunster , A. Gil , J. Segura

In the present paper we use the expansion formula of the polylogarithm function to construct approximations of the Caputo derivative which are related to the midpoint approximation of the integral in the definition of the Caputo derivative.…

Numerical Analysis · Mathematics 2018-08-28 Yuri Dimitrov , Venelin Todorov , Radan Miryanov

We solve the problem of finding optimal entire approximations of prescribed exponential type (unrestricted, majorant and minorant) for a class of truncated and odd functions with a shifted exponential subordination, minimizing the…

Classical Analysis and ODEs · Mathematics 2021-09-30 Emanuel Carneiro , Friedrich Littmann