10 papers
Anticoncentrated -bit distribution from qubits
Bingzhi Zhang, Quntao Zhuang
Random circuit sampling (RCS) is a leading approach to demonstrate quantum advantage, with its believed classical hardness rooted in anticoncentration of output distributions and a…
An Analytic Theory of Quantum Imaginary Time Evolution
Min Chen, Bingzhi Zhang, Quntao Zhuang +1
Quantum imaginary time evolution (QITE) algorithm is one of the most promising variational quantum algorithms (VQAs), bridging the current era of Noisy Intermediate-Scale Quantum d…
Mixed-State Quantum Denoising Diffusion Probabilistic Model
Gino Kwun, Bingzhi Zhang, Quntao Zhuang
Generative quantum machine learning has gained significant attention for its ability to produce quantum states with desired distributions. Among various quantum generative models,…
Holographic deep thermalization for secure and efficient quantum random state generation
Bingzhi Zhang, Peng Xu, Xiaohui Chen +1
Randomness is a cornerstone of science, underpinning fields such as statistics, information theory, dynamical systems, and thermodynamics. In quantum science, quantum randomness, e…
Quantum-data-driven dynamical transition in quantum learning
Bingzhi Zhang, Junyu Liu, Liang Jiang +1
Quantum neural networks, parameterized quantum circuits optimized under a specific cost function, provide a paradigm for achieving near-term quantum advantage in quantum informatio…
Uncovering Quantum Many-body Scars with Quantum Machine Learning
Jiajin Feng, Bingzhi Zhang, Zhi-Cheng Yang +1
Quantum many-body scars are rare eigenstates hidden within the chaotic spectra of many-body systems, representing a weak violation of the eigenstate thermalization hypothesis (ETH)…