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Abstract
Real partially symmetric tensors arise from the strong ellipticity condition problem in solid mechanics and the entanglement problem in quantum physics. In this paper, we try to compute the smallest V-singular value of partially symmetric tensors with orders (p, q). This is a unified notion in a broad sense that, when (p,q)=(2,2), the V-singular value coincides with the notion of M-eigenvalue. To do that, we propose a generalized inverse power method with a shift variable to compute the smallest V-singular value and eigenvectors. Global convergence of the algorithm is established. Furthermore, it is proven that the proposed algorithm always converges to the smallest V-singular value and the associated eigenvectors. Several numerical experiments show the efficiency of the proposed algorithm. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
| Original language | English |
|---|---|
| Pages (from-to) | 1151-1167 |
| Number of pages | 17 |
| Journal | Journal of Optimization Theory and Applications |
| Volume | 201 |
| Issue number | 3 |
| Online published | 26 Apr 2024 |
| DOIs | |
| Publication status | Published - Jun 2024 |
Funding
This work was supported by the Natural Science Foundation of China (Grant No. 12071249), Shandong Provincial Natural Science Foundation of Distinguished Young Scholars (Grant No. ZR2021JQ01), Hong Kong Innovation and Technology Commision (InnoHK Project CIMDA) and Hong Kong Research Grants Council (Project CityU 11204821).
Research Keywords
- 15A18
- 65H17
- 90C30
- Eigenvector
- Inverse power method
- Partially symmetric tensors
- V-singular value
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GRF: Matching Large Feature Sets based on Hypergraph Models and Structurally Adaptive CUR Decompositions of Compatibility Tensors
YAN, H. (Principal Investigator / Project Coordinator)
1/01/22 → …
Project: Research