You're viewing papers too quickly. Please wait a moment.<br>This helps keep the archive available for everyone.
Quick Navigation
Topics
Quantum State Preparation Representation
Quotient geometry of tensor ring decomposition
arXiv
Authors: Bin Gao, Renfeng Peng, Ya-xiang Yuan
Year
2026
Paper ID
3125
Status
Preprint
Abstract Read
~2 min
Abstract Words
103
Citations
N/A
Abstract
Differential geometries derived from tensor decompositions have been extensively studied and provided the foundations for a variety of efficient numerical methods. Despite the practical success of the tensor ring (TR) decomposition, its intrinsic geometry remains less understood, primarily due to the underlying ring structure and the resulting nontrivial gauge invariance. We establish the quotient geometry of TR decomposition by imposing full-rank conditions on all unfolding matrices of the core tensors and capturing the gauge invariance. Additionally, the results can be extended to the uniform TR decomposition, where all core tensors are identical. Numerical experiments validate the developed geometries via tensor ring completion tasks.
Why This Paper Matters
- This paper contributes to the Quantum State Preparation & Representation research area in the Quantum Articles archive.
- It adds a 2026 reference point for readers tracking recent quantum research.
- Differential geometries derived from tensor decompositions have been extensively studied and provided the foundations for a variety of efficient numerical methods.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.