15 citations · 28 across the 26 of their papers we have counts for
7 papers · 1 filter
Optimal Error Analysis of Channel Estimation for IRS-assisted MIMO Systems
Zhen Qin, Zhihui Zhu
As intelligent reflecting surface (IRS) has emerged as a new and promising technology capable of configuring the wireless environment favorably, channel estimation for IRS-assisted…
Optimal Allocation of Pauli Measurements for Low-rank Quantum State Tomography
Zhen Qin, Casey Jameson, Zhexuan Gong +2
The process of reconstructing quantum states from experimental measurements, accomplished through quantum state tomography (QST), plays a crucial role in verifying and benchmarking…
Robust Low-rank Tensor Train Recovery
Zhen Qin, Zhihui Zhu
Tensor train (TT) decomposition represents an -order tensor using matrices (i.e., factors) of small dimensions, achieved through products among these factors. Due to its…
Sample-Efficient Quantum State Tomography for Structured Quantum States in One Dimension
Zhen Qin, Casey Jameson, Alireza Goldar +3
While quantum state tomography (QST) remains the gold standard for benchmarking and verifying quantum devices, it requires an exponentially large number of measurements and classic…
Optimal quantum state tomography with local informationally complete measurements
Casey Jameson, Zhen Qin, Alireza Goldar +3
Quantum state tomography (QST) remains the gold standard for benchmarking and verification of near-term quantum devices. While QST for a generic quantum many-body state requires an…
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition
Zhen Qin, Zhihui Zhu
Recently, a tensor-on-tensor (ToT) regression model has been proposed to generalize tensor recovery, encompassing scenarios like scalar-on-tensor regression and tensor-on-vector re…
Guaranteed Nonconvex Factorization Approach for Tensor Train Recovery
Zhen Qin, Michael B. Wakin, Zhihui Zhu
In this paper, we provide the first convergence guarantee for the factorization approach. Specifically, to avoid the scaling ambiguity and to facilitate theoretical analysis, we op…