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arXiv 2609.11369math.NAcs.NA

张量函数逼近的管状Arnoldi方法

The tubal Arnoldi method for tensor function approximation

  • École nationale de l’aviation civile(法国国立民用航空学院)
  • Mohammed V University(穆罕默德五世大学)
  • Université du Littoral Côte d’Opale(加来海峡海岸大学)

机构由 AI 辅助整理,请以论文原文为准。

Fatima Bouyghf, Mohamed El Ghomari, Alaa El Ichi

AI总结:

本文提出基于张量t-积的管状Arnoldi方法,将高维张量问题投影到低维Krylov子空间,用于高效逼近张量函数并求解多维常微分方程,实验验证了其有效性和准确性。

AI中文摘要:

本文描述了基于张量t-积的Krylov子空间方法,用于逼近与三阶张量函数相关的量。具体而言,它引入了张量-管状Arnoldi方法,该方法将高维张量问题投影到低维张量Krylov子空间上。所推导的方法利用t-积的新代数性质,高效地处理大规模张量计算。应用包括参数依赖张量函数的评估以及多维常微分方程的求解。数值实验表明了所提方法相对于其他方法的有效性和准确性。

英文摘要:

This paper describes Krylov subspace methods based on the tensor t-product for approximating quantities associated with third-order tensor functions. Specifically, it introduces the tensor-tubal Arnoldi method, which projects highdimensional tensor problems onto lower-dimensional tensor Krylov subspaces. The derived method exploits novel algebraic properties of the t-product to address large-scale tensor computations efficiently. Applications include the evaluation of parameter-dependent tensor functions and the solution of multidimensional ordinary differential equations. Numerical experiments illustrate the effectiveness and accuracy of the proposed methods compared with other approaches.

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