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A mathematical framework is constructed for the sum of the lowest N eigenvalues of a potential. Exactness is illustrated on several model systems (harmonic oscillator, particle in a box, and Poschl-Teller well). Its order-by-order…

Materials Science · Physics 2020-06-04 Kieron Burke

In a previous paper, I demonstrated the accuracy of simple, precessing, power ellipse (p-ellipse) approximations to orbits of low-to-moderate eccentricity in power-law potentials. Here I explore several extensions of these approximations to…

Astrophysics of Galaxies · Physics 2015-06-23 Curtis Struck

For a regression model, we consider the risk of the maximum likelihood estimator with respect to $\alpha$-divergence, which includes the special cases of Kullback-Leibler divergence, Hellinger distance and $\chi^2$ divergence. The…

Statistics Theory · Mathematics 2017-09-12 Yo Sheena

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

In this work we discuss the problem of selecting suitable approximators from families of parameterized elementary functions that are known to be dense in a Hilbert space of functions. We consider and analyze published procedures, both…

Numerical Analysis · Computer Science 2016-09-01 Alexander N. Gorban , Ivan Yu. Tyukin , Danil V. Prokhorov , Konstantin I. Sofeikov

Cosmological parameter estimation from forthcoming experiments promise to reach much greater precision than current constraints. As statistical errors shrink, the required control over systematic errors increases. Therefore, models or…

Cosmology and Nongalactic Astrophysics · Physics 2020-10-07 José Luis Bernal , Nicola Bellomo , Alvise Raccanelli , Licia Verde

Stellar limb darkening affects a wide range of astronomical measurements and is frequently modelled with a parametric model using polynomials in the cosine of the angle between the line of sight and the emergent intensity. Two-parameter…

Solar and Stellar Astrophysics · Physics 2015-06-16 David M. Kipping

An important question in evolutionary computation is how good solutions evolutionary algorithms can produce. This paper aims to provide an analytic analysis of solution quality in terms of the relative approximation error, which is defined…

Neural and Evolutionary Computing · Computer Science 2016-11-28 Jun He

Forthcoming photometric redshift surveys should provide an accurate probe of the acoustic peak in the two-point galaxy correlation function, in the form of angular clustering of galaxies within a given shell in redshift space. We…

Cosmology and Nongalactic Astrophysics · Physics 2009-03-24 Fergus Simpson , John A. Peacock , Patrick Simon

We introduce a recursive algorithm of conveniently general form for estimating the coefficient of a moving average model of order one and obtain convergence results for both correct and misspecified MA(1) models. The algorithm encompasses…

Statistics Theory · Mathematics 2007-06-13 James L. Cantor , David F. Findley

Here we introduce a generalization of the exponential sampling series of optical physics and establish pointwise and uniform convergence theorem, also in a quantitative form. Moreover we compare the error of approximation for Mellin…

Functional Analysis · Mathematics 2016-10-03 Carlo Bardaro , Loris Faina , Ilaria Mantellini

We develop likelihood-based bias reduction for nonlinear panel models with additive individual and time effects. In two-way panels, integrated-likelihood corrections are attractive but challenging because the required integration is high…

Econometrics · Economics 2026-04-07 Zizhong Yan , Zhengyu Zhang , Mingli Chen , Jingrong Li , Iván Fernández-Val

We study approximation of the embedding $\ell_p^m \rightarrow \ell_{\infty}^m$, $1 \leq p \leq 2$, based on randomized adaptive algorithms that use arbitrary linear functionals as information on a problem instance. We show upper bounds for…

Numerical Analysis · Mathematics 2024-08-05 Robert J. Kunsch , Marcin Wnuk

In a previous paper an asymptotic expansion for lambda_d in powers of 1/d was developed. The results of computer computations for some terms in the expansion, as well as various quantities associated to the expansion, are herein presented.…

Mathematical Physics · Physics 2008-05-30 Paul Federbush

A new sampling methodology based on incomplete cosine expansion series is presented as an alternative to the traditional sinc function approach. Numerical integration shows that this methodology is efficient and practical. Applying the…

Numerical Analysis · Mathematics 2015-03-24 S. M. Abrarov , B. M. Quine

Fourier extension is an approximation method that alleviates the periodicity requirements of Fourier series and avoids the Gibbs phenomenon when approximating functions. We describe a similar extension approach using regular wavelet bases…

Numerical Analysis · Mathematics 2020-04-08 Vincent Coppé , Daan Huybrechs

This paper considers decentralized consensus optimization problems where different summands of a global objective function are available at nodes of a network that can communicate with neighbors only. The proximal method of multipliers is…

Optimization and Control · Mathematics 2016-02-02 Aryan Mokhtari , Wei Shi , Qing Ling , Alejandro Ribeiro

An eikonal expansion is developed in order to provide systematic corrections to the eikonal approximation through order 1/k^2, where k is the wave number. The expansion is applied to wave functions for the Klein-Gordon equation and for the…

Nuclear Theory · Physics 2011-07-19 J. A. Tjon , S. J. Wallace

In this paper a new technique aimed to obtain accurate estimates of the error in energy norm using a moving least squares (MLS) recovery-based procedure is presented. We explore the capabilities of a recovery technique based on an enhanced…

Numerical Analysis · Mathematics 2012-09-03 J. J. Ródenas , Octavio Andrés González Estrada , F. J. Fuenmayor , F. Chinesta

The quest for an algorithm that solves an $n\times n$ linear system in $O(n^2)$ time complexity, or $O(n^2 \text{poly}(1/\epsilon))$ when solving up to $\epsilon$ relative error, is a long-standing open problem in numerical linear algebra…

Numerical Analysis · Mathematics 2026-05-26 Michał Dereziński , Yuji Nakatsukasa , Elizaveta Rebrova