Advancing convergence analysis: extending the scope of a sixth order method

Jinny Ann John, Jayakumar Jayaraman
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Abstract

In this article, we aim to emphasize the critical role of extended convergence analysis in advancing research and understanding in the interdisciplinary fields of Applied and Computational Mathematics, Physics, Engineering, and Chemistry. By gaining a comprehensive understanding of the convergence behavior of numerical methods, one can make informed decisions regarding algorithm selection, optimization, and convergence domains, leading to more accurate and reliable scientific results in diverse applications. The conventional approach to assessing the convergence order of higher order methods for solving systems of non-linear equations relied on the Taylor series expansion, necessitating the computation of higher order derivatives that were typically absent in the method. This limitation not only constrained the method’s applicability but also increased the computational cost of solving the problem. In contrast, our study introduces a unique and innovative approach, where we demonstrate the improvised convergence of the method using only first order derivatives. Our new method offers several advantages over the traditional approach, providing valuable information regarding the radii of the convergence region and precise estimates of error boundaries. Furthermore, we establish the notion of semi-local convergence, which proves to be particularly significant as it allows for the identification of the specific domain in which the iterates converge. We have validated the convergence requirements through carefully selected numerical examples.

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推进收敛分析:扩展六阶方法的范围
本文旨在强调扩展收敛分析在推动应用数学与计算数学、物理学、工程学和化学等跨学科领域的研究和理解方面的关键作用。通过全面了解数值方法的收敛行为,人们可以在算法选择、优化和收敛域方面做出明智的决策,从而在各种应用中获得更准确、更可靠的科学结果。评估用于求解非线性方程系统的高阶方法的收敛阶数的传统方法依赖于泰勒级数展开,因此必须计算该方法中通常不存在的高阶导数。这种限制不仅制约了方法的适用性,而且增加了解决问题的计算成本。相比之下,我们的研究引入了一种独特的创新方法,我们仅使用一阶导数就证明了该方法的改进收敛性。与传统方法相比,我们的新方法具有多项优势,提供了关于收敛区域半径的宝贵信息和误差边界的精确估计。此外,我们还建立了半局部收敛的概念,这被证明是特别重要的,因为它允许识别迭代收敛的特定域。我们通过精心挑选的数值示例验证了收敛要求。
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