3 papers
quant-ph2025
Realizing Universal Non-Markovian Noise Suppression
Hongfeng Liu, Zizhao Han, Xinfang Nie +2
Non-Markovian noise, arising from environmental memory effects, is the most general and challenging form of noise in quantum computing, and is typically difficult to characterize a…
quant-ph2025
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…
quant-ph2023
Expressibility-induced Concentration of Quantum Neural Tangent Kernels
Li-Wei Yu, Weikang Li, Qi Ye +3
Quantum tangent kernel methods provide an efficient approach to analyzing the performance of quantum machine learning models in the infinite-width limit, which is of crucial import…