Near-Term Quantum Computing Techniques: Variational Quantum Algorithms, Error Mitigation, Circuit Compilation, Benchmarking and Classical Simulation

no code implementations • 16 Nov 2022 • He-Liang Huang, Xiao-Yue Xu, Chu Guo, Guojing Tian, Shi-Jie Wei, Xiaoming Sun, Wan-su Bao, Gui-Lu Long

To address this challenge, several near-term quantum computing techniques, including variational quantum algorithms, error mitigation, quantum circuit compilation and benchmarking protocols, have been proposed to characterize and mitigate errors, and to implement algorithms with a certain resistance to noise, so as to enhance the capabilities of near-term quantum devices and explore the boundaries of their ability to realize useful applications.

Benchmarking

Active Learning on a Programmable Photonic Quantum Processor

no code implementations • 3 Aug 2022 • Chen Ding, Xiao-Yue Xu, Yun-Fei Niu, Shuo Zhang, Wan-su Bao, He-Liang Huang

Here, we design and implement two AL-enpowered variational quantum classifiers, to investigate the potential applications and effectiveness of AL in quantum machine learning.

Active Learning BIG-bench Machine Learning +1