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A Gaussian elimination form of inverse iteration within the complex coordinate approach is shown to produce a simple uniform method of finding both real bound state energies and complex resonant state energies for several problems which…

Quantum Physics · Physics 2009-06-25 John P. Killingbeck , Alain Grosjean

We present a fast Gauss transform in one dimension using nearly optimal sum-of-exponentials approximations of the Gaussian kernel. For up to about ten-digit accuracy, the approximations are obtained via best rational approximations of the…

Numerical Analysis · Mathematics 2019-09-24 Shidong Jiang

In this paper we present two different variants of method for symmetric matrix inversion, based on modified Gaussian elimination. Both methods avoid computation of square roots and have a reduced machine time's spending. Further, both of…

Mathematical Software · Computer Science 2015-04-28 Anton Kochnev , Nicolai Savelov

It may be possible to extend the Grover search algorithm by taking a divide and conquer approach using auxiliary solutions to achieve an exponential speed-up.

General Physics · Physics 2009-07-13 A. Y. Shiekh

Gaussian Boson Sampling (GBS) have shown advantages over classical methods for performing some specific sampling tasks. To fully harness the computational power of GBS, there has been great interest in identifying their practical…

Quantum Physics · Physics 2025-02-28 Jørgen Ellegaard Andersen , Shan Shan

We provide faster algorithms for the problem of Gaussian summation, which occurs in many machine learning methods. We develop two new extensions - an O(Dp) Taylor expansion for the Gaussian kernel with rigorous error bounds and a new error…

Machine Learning · Computer Science 2012-07-02 Dongryeol Lee , Alexander G. Gray

The Gaussian Elimination with Partial Pivoting (GEPP) is a classical algorithm for solving systems of linear equations. Although in specific cases the loss of precision in GEPP due to roundoff errors can be very significant, empirical…

Numerical Analysis · Mathematics 2024-03-07 Han Huang , Konstantin Tikhomirov

In this paper, we propose a simple strategy for estimating the convergence point approximately by averaging the elite sub-population. Based on this idea, we derive two methods, which are ordinary averaging strategy, and weighted averaging…

Neural and Evolutionary Computing · Computer Science 2022-09-01 Rui Zhong , Masaharu Munetomo

We discuss the generalization to global gauge anomalies of the familiar procedure for the cancellation of local gauge anomalies in effective theories of spontaneously broken symmetries. We illustrate this mechanism in a recently proposed…

High Energy Physics - Theory · Physics 2009-11-07 M. Fabbrichesi , R. Percacci , M. Piai , M. Serone

Gauge mediation of supersymmetry breaking is drastically simplified using generic superpotentials without U(1)_R symmetry by allowing metastable vacua.

High Energy Physics - Phenomenology · Physics 2008-11-26 Hitoshi Murayama , Yasunori Nomura

We study a generalization of deduplication, which enables lossless deduplication of highly similar data and show that standard deduplication with fixed chunk length is a special case. We provide bounds on the expected length of coded…

Information Theory · Computer Science 2020-03-04 Rasmus Vestergaard , Qi Zhang , Daniel E. Lucani

Gaussian elimination (GE) is the archetypal direct algorithm for solving linear systems of equations and this has been its primary application for thousands of years. In the last decade, GE has found another major use as an iterative…

Numerical Analysis · Mathematics 2016-02-23 Alex Townsend

Gaussian Boson Sampling (GBS), which can be realized with a photonic quantum computing model, perform some special kind of sampling tasks. In [4], we introduced algorithms that use GBS samples to approximate Gaussian expectation problems.…

Quantum Physics · Physics 2025-02-28 Jørgen Ellegaard Andersen , Shan Shan

An asymptotic expansion for the generalised quadratic Gauss sum $$S_N(x,\theta)=\sum_{j=1}^{N} \exp (\pi ixj^2+2\pi ij\theta),$$ where $x$, $\theta$ are real and $N$ is a positive integer, is obtained as $x\rightarrow 0$ and…

Classical Analysis and ODEs · Mathematics 2014-04-01 R B Paris

Statistical analyses of observed galaxy distortions are often used to reconstruct the mass distribution of an intervening cluster responsible for gravitational lensing. In current projects, distortions of thousands of source galaxies have…

Astrophysics · Physics 2007-05-23 Marco Lombardi , Giuseppe Bertin

A method is presented which allows for a tremendous speed-up of computer simulations of statistical systems by orders of magnitude. This speed-up is achieved by means of a new observable, while the algorithm of the simulation remains…

Statistical Mechanics · Physics 2013-05-29 M. Kastner , J. D. Munoz , M. Promberger

The leading asymptotics of the truncation error for Gauss's continued fraction is determined exactly. Not only for this purpose but also for wider applicability elsewhere the discrete analogue of Laplace's method for hypergeometric series…

Classical Analysis and ODEs · Mathematics 2019-04-09 Katsunori Iwasaki

We propose a novel accelerated exact k-means algorithm, which performs better than the current state-of-the-art low-dimensional algorithm in 18 of 22 experiments, running up to 3 times faster. We also propose a general improvement of…

Machine Learning · Statistics 2016-09-13 James Newling , François Fleuret

We consider the uniform asymptotic expansion for the Gauss hypergeometric function \[F(a+\epsilon\lambda,m;c+\lambda;x),\qquad \lambda\to+\infty\] for $x<1$ and positive integer $m$ when the parameter $\epsilon>1$ and the constants $a$ and…

Classical Analysis and ODEs · Mathematics 2018-10-16 R B Paris

Recent advances in 3D Gaussian Splatting (3DGS) have focused on accelerating optimization while preserving reconstruction quality. However, many proposed methods entangle implementation-level improvements with fundamental algorithmic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Florian Hahlbohm , Linus Franke , Martin Eisemann , Marcus Magnor
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