Sharp Convergence Rates and Optimal Weights for Cimmino's Reflection Algorithm
Abstract
In this paper, Cimmino's classical reflection algorithm for solving the nonsingular linear system is analysed through the lens of spectral theory. Reformulating the weighted iteration as , where , the error is shown to contract by the spectral radius at every step, with a sharp, asymptotically tight bound. For , a closed-form expression for the contraction factor is derived, where and denotes the angle between the hyperplane normals. A central result of this paper is that the standard unit weights are \emph{globally optimal} over all positive weight pairs, uniquely achieving the minimum contraction factor -- a quantity determined solely by the geometry of the hyperplane normals. The inter-normal angle thus emerges as the single diagnostic parameter governing both convergence speed and weight selection. Extensions to a single-step convergence criterion at and to an exact spectral rate for general~ are also established.
Cite
@article{arxiv.2605.24692,
title = {Sharp Convergence Rates and Optimal Weights for Cimmino's Reflection Algorithm},
author = {Hemant Sharma},
journal= {arXiv preprint arXiv:2605.24692},
year = {2026}
}