8 citations · 16 across the 4 of their papers we have counts for
5 papers
Shuffle-QUDIO: accelerate distributed VQE with trainability enhancement and measurement reduction
Yang Qian, Yuxuan Du, Dacheng Tao
The variational quantum eigensolver (VQE) is a leading strategy that exploits noisy intermediate-scale quantum (NISQ) machines to tackle chemical problems outperforming classical a…
Quantum circuit architecture search on a superconducting processor
Kehuan Linghu, Yang Qian, Ruixia Wang +14
Variational quantum algorithms (VQAs) have shown strong evidences to gain provable computational advantages for diverse fields such as finance, machine learning, and chemistry. How…
Accelerating variational quantum algorithms with multiple quantum processors
Yuxuan Du, Yang Qian, Dacheng Tao
Variational quantum algorithms (VQAs) have the potential of utilizing near-term quantum machines to gain certain computational advantages over classical methods. Nevertheless, mode…
The dilemma of quantum neural networks
Yang Qian, Xinbiao Wang, Yuxuan Du +2
The core of quantum machine learning is to devise quantum models with good trainability and low generalization error bound than their classical counterparts to ensure better reliab…
Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC
Sau Lan Wu, Shaojun Sun, Wen Guan +20
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In…