2 papers
quant-ph2026
Online Riemannian Gradient Descent for Quantum State Tomography with Matrix Product Operators
Jian-Feng Cai, Jingyang Li, Xiaoqun Zhang +1
Matrix product operators (MPOs) provide a scalable approach for quantum state tomography (QST) by offering a compact representation of many-body mixed states with limited entanglem…
cs.LG2025
Fast and Provable Tensor-Train Format Tensor Completion via Precondtioned Riemannian Gradient Descent
Fengmiao Bian, Jian-Feng Cai, Xiaoqun Zhang +1
Low-rank tensor completion aims to recover a tensor from partially observed entries, and it is widely applicable in fields such as quantum computing and image processing. Due to th…