5 papers
Exponential speedup in measurement property learning with post-measurement states
Zhenhuan Liu, Qi Ye, Zhenyu Cai +1
Learning properties of quantum states and channels is known to benefit from resources such as entangled operations, auxiliary qubits, and adaptivity, whereas the resource structure…
Quantum automated theorem proving
Zheng-Zhi Sun, Qi Ye, Dong-Ling Deng
Automated theorem proving, or more broadly automated reasoning, aims at using computer programs to automatically prove or disprove mathematical theorems and logical statements. It…
Exponential Advantage from One More Replica in Estimating Nonlinear Properties of Quantum States
Qi Ye, Zhenhuan Liu, Dong-Ling Deng
Inferring nonlinear features of quantum states is fundamentally important across quantum information science, but remains challenging due to the intrinsic linearity of quantum mech…
Quantum automated learning with provable and explainable trainability
Qi Ye, Shuangyue Geng, Zizhao Han +3
Machine learning is widely believed to be one of the most promising practical applications of quantum computing. Existing quantum machine learning schemes typically employ a quantu…
No-Free-Lunch Theories for Tensor-Network Machine Learning Models
Jing-Chuan Wu, Qi Ye, Dong-Ling Deng +1
Tensor network machine learning models have shown remarkable versatility in tackling complex data-driven tasks, ranging from quantum many-body problems to classical pattern recogni…