Quantum Compiling with Reinforcement Learning on a Superconducting Processor

no code implementations • 18 Jun 2024 • Z. T. Wang, Qiuhao Chen, Yuxuan Du, Z. H. Yang, Xiaoxia Cai, Kaixuan Huang, Jingning Zhang, Kai Xu, Jun Du, Yinan Li, Yuling Jiao, Xingyao Wu, Wu Liu, Xiliang Lu, Huikai Xu, Yirong Jin, Ruixia Wang, Haifeng Yu, S. P. Zhao

To effectively implement quantum algorithms on noisy intermediate-scale quantum (NISQ) processors is a central task in modern quantum technology.

reinforcement-learning Reinforcement Learning (RL) +1

Provable Advantage of Parameterized Quantum Circuit in Function Approximation

no code implementations • 11 Oct 2023 • Zhan Yu, Qiuhao Chen, Yuling Jiao, Yinan Li, Xiliang Lu, Xin Wang, Jerry Zhijian Yang

To achieve this, we utilize techniques from quantum signal processing and linear combinations of unitaries to construct PQCs that implement multivariate polynomials.

Quantum Machine Learning

Efficient and practical quantum compiler towards multi-qubit systems with deep reinforcement learning

no code implementations • 14 Apr 2022 • Qiuhao Chen, Yuxuan Du, Qi Zhao, Yuling Jiao, Xiliang Lu, Xingyao Wu

We systematically evaluate the performance of our proposal in compiling quantum operators with both inverse-closed and inverse-free universal basis sets.

Q-Learning reinforcement-learning +1