15 papers
Structured Factorization Approaches for Quantum State Tomography
Zhen Qin, Joseph M. Lukens, Brian T. Kirby +1
Since the complexity of quantum state tomography (QST) scales exponentially with system size, exploiting priors such as low-rankness, tensor-network structures, and neural-network…
Statistical and Algorithmic Foundations of Probing Quantum Systems with Compressive Measurements: A Review
Zhen Qin, Michael B. Wakin, Zhihui Zhu
Quantum state tomography (QST) is a fundamental task in quantum information science that aims to reconstruct unknown quantum states from measurement data. However, the exponential…
An Exponential Advantage for Adaptive Tomography of Structured States under Pauli Basis Measurements
Alireza Goldar, Zhen Qin, Zhihui Zhu +2
Broad claims about whether adaptivity helps in quantum state tomography can be misleading unless the state family, measurement architecture, and error metric are specified carefull…
Learning to Adapt: In-Context Learning Beyond Stationarity
Zhen Qin, Jiachen Jiang, Zhihui Zhu
Transformer models have become foundational across a wide range of scientific and engineering domains due to their strong empirical performance. A key capability underlying their s…
In-Context Learning for Non-Stationary MIMO Equalization
Jiachen Jiang, Zhen Qin, Zhihui Zhu
Channel equalization is fundamental for mitigating distortions such as frequency-selective fading and inter-symbol interference. Unlike standard supervised learning approaches that…
Quantum State Tomography for Tensor Networks in Two Dimensions
Zhen Qin, Zhihui Zhu
Recent work has shown that for one-dimensional quantum states that can be effectively approximated by matrix product operators (MPOs), a polynomial number of copies of the state su…