2022
DOI: 10.1007/s11075-022-01351-6
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A Lanczos-type procedure for tensors

Abstract: The solution of linear non-autonomous ordinary differential equation systems (also known as the time-ordered exponential) is a computationally challenging problem arising in a variety of applications. In this work, we present and study a new framework for the computation of bilinear forms involving the time-ordered exponential. Such a framework is based on an extension of the non-Hermitian Lanczos algorithm to 4-mode tensors. Detailed results concerning its theoretical properties are presented. Moreover, compu… Show more

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Cited by 3 publications
(6 citation statements)
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“…This may be exploited using projection methods with low-rank techniques (see, e.g., [11,12]). In [10], we also show that matrix A M in (8) can be compressed by the Tensor Train decomposition (note that [10] uses a different family of orthogonal functions instead of the Legendre polynomials). A Tensor Train approach may further reduce the memory and computational cost of the method.…”
Section: Discussionmentioning
confidence: 82%
See 2 more Smart Citations
“…This may be exploited using projection methods with low-rank techniques (see, e.g., [11,12]). In [10], we also show that matrix A M in (8) can be compressed by the Tensor Train decomposition (note that [10] uses a different family of orthogonal functions instead of the Legendre polynomials). A Tensor Train approach may further reduce the memory and computational cost of the method.…”
Section: Discussionmentioning
confidence: 82%
“…with D, B sparse matrices described in [10]. In our experiments, we set T = 10 −3 , ν = 10 4 , k = 4, 7, 10, so obtaining three systems with exponentially increasing sizes.…”
Section: Numerical Examplesmentioning
confidence: 99%
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“…The key to going from the ⋆-algebra to the matrix algebra is discretizing the ⋆-product. One way to discretize the ⋆-product is by the use of quadrature rules [1]. Another way is by expansion in a basis of orthonormal polynomials (ONPs), which is the topic of this paper.…”
Section: ⋆-Productmentioning
confidence: 99%
“…Therefore, a numerical procedure is proposed that computes a discretization of this solution in the matrix algebra, equipped with the usual matrix-matrix product. The key to going from the ⋆-algebra to the matrix algebra is finding a suitable discretization of the ⋆-product, which can be based on a quadrature rule [1] or on the expansion of the bivariate distributions in a basis of orthonormal polynomials. The latter approach is followed in this paper, a basis of orthonormal Legendre polynomials is chosen and the resulting discretization is discussed in Section 3.…”
Section: Introductionmentioning
confidence: 99%