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QuEst: Graph Transformer for Quantum Circuit Reliability Estimation


Oct 30, 2022
Hanrui Wang, Pengyu Liu, Jinglei Cheng, Zhiding Liang, Jiaqi Gu, Zirui Li, Yongshan Ding, Weiwen Jiang, Yiyu Shi, Xuehai Qian, David Z. Pan, Frederic T. Chong, Song Han

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* ICCAD 2022; 10 pages, 10 figures; code at https://github.com/mit-han-lab/torchquantum 

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PAN: Pulse Ansatz on NISQ Machines


Aug 02, 2022
Zhiding Liang, Jinglei Cheng, Hang Ren, Hanrui Wang, Fei Hua, Yongshan Ding, Fred Chong, Song Han, Yiyu Shi, Xuehai Qian

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* 13 pages, 13 figures 

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On-chip QNN: Towards Efficient On-Chip Training of Quantum Neural Networks


Feb 26, 2022
Hanrui Wang, Zirui Li, Jiaqi Gu, Yongshan Ding, David Z. Pan, Song Han

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* Published as a conference paper in DAC 2022; 7 pages, 8 figures; open-source at https://github.com/mit-han-lab/torchquantum 

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RoQNN: Noise-Aware Training for Robust Quantum Neural Networks


Oct 21, 2021
Hanrui Wang, Jiaqi Gu, Yongshan Ding, Zirui Li, Frederic T. Chong, David Z. Pan, Song Han

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* 19 pages, 10 figures, open-source at https://github.com/mit-han-lab/pytorch-quantum 

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QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits


Aug 02, 2021
Hanrui Wang, Yongshan Ding, Jiaqi Gu, Yujun Lin, David Z. Pan, Frederic T. Chong, Song Han

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* 14 pages, 22 figures. Code available at https://github.com/mit-han-lab/pytorch-quantum 

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