7 papers · 1 filter
From Barren Plateaus to SPSA Optimization in Variational Quantum Eigensolvers
Zhen Qin
The barren plateau (BP) phenomenon poses a fundamental challenge to the trainability of variational quantum eigensolvers (VQEs) by causing exponentially vanishing gradients as the…
A Unified Framework for Sample Complexity of Structured Quantum State Tomography under Noisy Observations
Zhen Qin
Quantum state tomography (QST) has attracted considerable attention due to its fundamental role in quantum information processing. In this paper, we develop a unified theoretical f…
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…
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…
Enhancing Quantum State Reconstruction with Structured Classical Shadows
Zhen Qin, Joseph M. Lukens, Brian T. Kirby +1
Quantum state tomography (QST) remains the prevailing method for benchmarking and verifying quantum devices; however, its application to large quantum systems is rendered impractic…
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…