Research and Publications

My research aims to reduce the noise and compliation overhead problem in NISQ era quantum computer and can be divided to two aspects: Pulse based approach and Gate based approach. And I am also working on extend quantum machine learning into applications in different areas.

I’m grateful for having collaborated with these inspiring people, who guide and help me alot in my research path: Yongshan Ding (Assistant Professor at Yale), Hanrui Wang (PhD Candidate at MIT), Jinglei Cheng (PhD student at Purdue), Zhongrui Wang (Assistant Professor at HKU).

Publication

2022

• Hybrid gate-pulse model for variational quantum algorithms.
  Zhiding Liang, Zhixin Song, Jinglei Cheng, Zichang He, Ji Liu, Hanrui Wang, Ruiyang Qin, Yiru Wang, Song Han, Xuehai Qian, Yiyu Shi. in submission.
  [arXiv]

• PAN: Pulse Ansatz on NISQ Machines.
  Zhiding Liang^, Jinglei Cheng^, Hang Ren, Hanrui Wang, Yongshan Ding, Fred Chong, Song Han, Yiyu Shi, Xuehai Qian. in submission.
  [arXiv]

• Variational Quantum Pulse Learning.
  Zhiding Liang^, Hanrui Wang^, Jinglei Cheng, Yongshan Ding, Hang Ren, Zhengqi Gao, Duane Boning, Xuehai Qian, Song Han, Weiwen Jiang, Yiyu Shi. Accepted to IEEE International Conference on Quantum Computing and Engineering (QCE 2022).
  [arXiv]

• Improving Quantum Classifier Performance in NISQ Computers by Voting Strategy from Ensemble Learning .
  Ruiyang Qin, Zhiding Liang, Jinglei Cheng, Peter Kogge, Yiyu Shi. in submission.
  [arXiv]

• TopGen: Topology-Aware Bottom-Up Generator for Variational Quantum Circuits.
  Jinglei Cheng, Hanrui Wang, Zhiding Liang, Yiyu Shi, Song Han, Xuehai Qian. Under Review in IEEE Transcation on Quantum Engineering.
  [arXiv]

• QuEst: Graph Transformer for Quantum Circuit Reliability Estimation.
  Hanrui Wang, Pengyu Liu, Jinglei Cheng, Zhiding Liang, Jinglei Cheng, Jiaqi Gu, Zirui Li, Yongshan Ding, Weiwen Jiang, Yiyu Shi, Xuehai Qian, David Z. Pan, Frederic T. Chong, Song Han. Accepted to IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2022).
  [arXiv]

2021

• Can Noise on Qubits Be Learned in Quantum Neural Network? A Case Study on QuantumFlow.
  Zhiding Liang, Zhepeng Wang, Junhuan Yang, Lei Yang, Yiyu Shi, Weiwen Jiang. in Proc. of IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2021).
  [arXiv]

• Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs.
  Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Yiyu Shi, Weiwen Jiang. in Proc. of IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2021).
  [arXiv]

2020

• A comprehensive understanding of conductive mechanism of RRAM: from electron conduction to ionic dynamics.
  Zhiding Liang. 2020 International Conference on Electrical Engineering and Control Technologies (CEECT 2020).