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Sharp Convergence Rates and Optimal Weights for Cimmino's Reflection Algorithm

数值分析 2026-05-26 v1 数值分析

摘要

In this paper, Cimmino's classical reflection algorithm for solving the n×nn\times n nonsingular linear system A\bx=\bbA\bx=\bb is analysed through the lens of spectral theory. Reformulating the weighted iteration as \e(ν+1)=Mw\e(ν)\e^{(\nu+1)}=M_w\,\e^{(\nu)}, where Mw=IADwAM_w = I - A^\top D_w A, the error is shown to contract by the spectral radius \sprad(Mw)\sprad(M_w) at every step, with a sharp, asymptotically tight bound. For n=2n=2, a closed-form expression for the contraction factor is derived, \sprad(Mw)  =  1μ+12(w1w2)2+4w1w2cos2 ⁣θ, \sprad(M_w) \;=\; |1-\mu| + \tfrac{1}{2}\sqrt{(w_1-w_2)^2 + 4w_1w_2\cos^2\!\theta}, where μ=(w1+w2)/2\mu=(w_1+w_2)/2 and θ\theta denotes the angle between the hyperplane normals. A central result of this paper is that the standard unit weights w1=w2=1w_1^*=w_2^*=1 are \emph{globally optimal} over all positive weight pairs, uniquely achieving the minimum contraction factor \sprad=cosθ\sprad^*=|\cos\theta| -- a quantity determined solely by the geometry of the hyperplane normals. The inter-normal angle θ\theta thus emerges as the single diagnostic parameter governing both convergence speed and weight selection. Extensions to a single-step convergence criterion at θ=π/2\theta=\pi/2 and to an exact spectral rate for general~nn are also established.

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引用

@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}
}