599 citations · 1.9k across the 42 of their papers we have counts for
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Fermionic Simulators for Enhanced Scalability of Variational Quantum Simulation
Qingyu Li, Chiranjib Mukhopadhyay, Abolfazl Bayat
Near-term quantum simulators are mostly based on qubit-based architectures. However, their imperfect nature significantly limits their practical application. The situation is even…
A sequentially generated variational quantum circuit with polynomial complexity
Xiaokai Hou, Qingyu Li, Man-Hong Yung +4
Variational quantum algorithms have been a promising candidate to utilize near-term quantum devices to solve real-world problems. The powerfulness of variational quantum algorithms…
Ensemble-learning error mitigation for variational quantum shallow-circuit classifiers
Qingyu Li, Yuhan Huang, Xiaokai Hou +3
Classification is one of the main applications of supervised learning. Recent advancement in developing quantum computers has opened a new possibility for machine learning on such…
A duplication-free quantum neural network for universal approximation
Xiaokai Hou, Guanyu Zhou, Qingyu Li +2
The universality of a quantum neural network refers to its ability to approximate arbitrary functions and is a theoretical guarantee for its effectiveness. A non-universal neural n…
Quantum spectral clustering algorithm for unsupervised learning
Qingyu Li, Yuhan Huang, Shan Jin +2
Clustering is one of the most crucial problems in unsupervised learning, and the well-known -means clustering algorithm has been shown to be implementable on a quantum computer…
Robust resource-efficient quantum variational ansatz through evolutionary algorithm
Yuhan Huang, Qingyu Li, Xiaokai Hou +4
Variational quantum algorithms (VQAs) are promising methods to demonstrate quantum advantage on near-term devices as the required resources are divided between a quantum simulator…