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We review some aspects of the use of a technique known as group averaging, which provides a tool for the study of constrained systems. We focus our attention on the case where the gauge group is non-compact, and a `renormalized' group…

High Energy Physics - Theory · Physics 2007-05-23 Andres Gomberoff

In this paper we present a new family of rules for numerical integration. This family has up to half the error of the widely used Newton-Cotes rules when a sufficient number of points is evaluated and also much better numerical stability…

Numerical Analysis · Mathematics 2018-12-04 Ricardo Luiz Utsch de Freitas Pinto , Bernardo Bahia Monteiro

In a posteriori error analysis, the relationship between error and estimator is usually spoiled by so-called oscillation terms, which cannot be bounded by the error. In order to remedy, we devise a new approach where the oscillation has the…

Numerical Analysis · Mathematics 2019-03-15 Christian Kreuzer , Andreas Veeser

This paper presents a unique approach to the problem of calculating revisit time metrics for different satellite orbits, sensor geometries, and constellation configurations with application to early lifecycle design and optimisation…

Computational Engineering, Finance, and Science · Computer Science 2018-07-06 Nicholas H. Crisp , Sabrina Livadiotti , Peter C. E. Roberts

This paper proposes a new estimation procedure for the ambiguity function of a non-stationary time series. The stochastic properties of the empirical ambiguity function calculated from a single sample in time are derived. Different…

Methodology · Statistics 2009-08-21 Heidi Hindberg , Sofia C. Olhede

The averaging method provides a powerful tool for studying evolution in near-integrable systems. Existence of separatrices in the phase space of the underlying integrable system is an obstacle for application of standard results that…

Dynamical Systems · Mathematics 2017-06-28 Anatoly Neishtadt

A notorious problem in mathematics and physics is to create a solvable model for random sequential adsorption of non-overlapping congruent spheres in the $d$-dimensional Euclidean space with $d\geq 2$. Spheres arrive sequentially at…

Probability · Mathematics 2019-01-25 Souvik Dhara , Johan S. H. van Leeuwaarden , Debankur Mukherjee

This paper is devoted to the error analysis of a time-spectral algorithm for fractional diffusion problems of order $\alpha$ ($0 < \alpha < 1$). The solution regularity in the Sobolev space is revisited, and new regularity results in the…

Numerical Analysis · Mathematics 2021-06-08 Hao Luo , Xiaoping Xie

The earlier work of the author on Frequency estimation in three-phase power systems ( that is included as the reference number 1) is expanded to the distributed setting in order present a framework for the implementation of such a frequency…

Applications · Statistics 2016-03-31 Sayed Pouria Talebi

In this paper, a practical estimation method for a regression model is proposed using semiparametric efficient score functions applicable to data with various shapes of errors. First, I derive semiparametric efficient score vectors for a…

Methodology · Statistics 2023-01-23 Mijeong Kim

We study the resonant dynamics in a simple one degree of freedom, time dependent Hamiltonian model describing spin-orbit interactions. The equations of motion admit periodic solutions associated with resonant motions, the most important…

Earth and Planetary Astrophysics · Physics 2016-07-29 Ioannis Gkolias , Alessandra Celletti , Christos Efthymiopoulos , Giuseppe Pucacco

Semi-algebraic priors are ubiquitous in signal processing and machine learning. Prevalent examples include a) linear models where the signal lies in a low-dimensional subspace; b) sparse models where the signal can be represented by only a…

Information Theory · Computer Science 2025-08-19 Tamir Bendory , Nadav Dym , Dan Edidin , Arun Suresh

A new method for the line-of-sight velocity estimation of a high-speed near-Earth object (asteroid, meteorite) is suggested. The method is based on use of fractional, one-half order derivative of a Doppler signal. The algorithm suggested is…

Earth and Planetary Astrophysics · Physics 2015-06-17 V. D. Zakharchenko , I. G. Kovalenko

In the last years several estimation strategies have been formulated to determine the value of an unknown parameter in the most precise way, taking into account the presence of noise. These strategies typically rely on the use of quantum…

Quantum Physics · Physics 2021-08-31 Andrea Smirne , Andreas Lemmer , Martin B. Plenio , Susana F. Huelga

In the second paper of this series we extend our Bayesian reanalysis of the evidence for a cosmic variation of the fine structure constant to the semi-parametric modelling regime. By adopting a mixture of Dirichlet processes prior for the…

Instrumentation and Methods for Astrophysics · Physics 2013-09-12 Ewan Cameron , Tony Pettitt

In many radar scenarios, the radar target or the medium is assumed to possess randomly varying parts. The properties of a target are described by a random process known as the spreading function. Its second order statistics under the WSSUS…

Information Theory · Computer Science 2015-06-19 Götz E. Pfander , Pavel Zheltov

We consider secular perturbations of nearly Keplerian two-body motion under a perturbing potential that can be approximated to sufficient accuracy by expanding it to second order in the coordinates. After averaging over time to obtain the…

Astrophysics · Physics 2015-06-24 S. Mikkola , P. Nurmi

We introduce kernel estimators for the semicircle law. In this first part of our general theory on the estimators, we prove the consistency and conduct simulation study to show the performance of the estimators. We also point out that…

Mathematical Physics · Physics 2011-07-15 Wang Zhou

We provide the detailed asymptotic behavior for first-order aggregation models of heterogeneous oscillators. Due to the dissimilarity of natural frequencies, one could expect that all relative distances converge to definite positive value…

Dynamical Systems · Mathematics 2022-06-03 Dohyun Kim , Hansol Park

Machine learning models have emerged as a very effective strategy to sidestep time-consuming electronic-structure calculations, enabling accurate simulations of greater size, time scale and complexity. Given the interpolative nature of…

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