20 papers
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…
Structured Adaptive Tensor Prediction for Streaming Data
Zhen Qin, Yang Chen
Matrix-valued time series arise in a wide range of applications, such as spatio-temporal data from medical imaging and geophysics. Existing methods are mainly designed for static s…
Geometric Analysis of Variational Quantum Eigensolver
Zhen Qin
The Variational Quantum Eigensolver (VQE) is a fundamental algorithm in quantum computing, yet a coherent geometric characterization of VQE remains missing due to fragmented analys…
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…