Publications

You can also check out my Google Scholar page.

2023

  1. long_range_order.gif
    Collective dynamics and long-range order in thermal neuristor networks
    Yuan-Hang Zhang, Chesson Sipling, Erbin Qiu, Ivan K Schuller, and 1 more author
    arXiv preprint arXiv:2312.12899, 2023
  2. VO2.png
    Reconfigurable cascaded thermal neuristors for neuromorphic computing
    Erbin Qiu, Yuan-Hang Zhang, Massimiliano Di Ventra, and Ivan K Schuller
    Advanced Materials, 2023
  3. circuit.png
    Implementation of digital MemComputing using standard electronic components
    Yuan-Hang Zhang, and Massimiliano Di Ventra
    arXiv preprint arXiv:2309.12437, 2023
  4. self_averaging.png
    Self-averaging of digital memcomputing machines
    Daniel Primosch, Yuan-Hang Zhang, and Massimiliano Di Ventra
    Phys. Rev. E, 2023
  5. FPGA.png
    Hardware implementation of digital memcomputing on small-size FPGAs
    Dyk Chung Nguyen, Yuan-Hang Zhang, Massimiliano Di Ventra, and Yuriy V Pershin
    arXiv preprint arXiv:2305.01061, 2023
  6. transformer.png
    Transformer quantum state: A multipurpose model for quantum many-body problems
    Yuan-Hang Zhang, and Massimiliano Di Ventra
    Physical Review B, 2023

2022

  1. mode_demo.gif
    Efficient quantum state tomography with mode-assisted training
    Yuan-Hang Zhang, and Massimiliano Di Ventra
    Physical Review A, 2022

2021

  1. directed_percolation.png
    Directed percolation and numerical stability of simulations of digital memcomputing machines
    Yuan-Hang Zhang, and Massimiliano Di Ventra
    Chaos: An Interdisciplinary Journal of Nonlinear Science, 2021

2020

  1. topoQCRL.png
    Topological quantum compiling with reinforcement learning
    Yuan-Hang Zhang, Pei-Lin Zheng, Yi Zhang, and Dong-Ling Deng
    Physical Review Letters, 2020

2019

  1. QNN.png
    Building quantum neural networks based on a swap test
    Jian Zhao, Yuan-Hang Zhang, Chang-Peng Shao, Yu-Chun Wu, and 2 more authors
    Physical Review A, 2019
  2. domain_wall.png
    Efficient machine-learning representations of a surface code with boundaries, defects, domain walls, and twists
    Zhih-Ahn Jia, Yuan-Hang Zhang, Yu-Chun Wu, Liang Kong, and 2 more authors
    Physical Review A, 2019

2018

  1. RBM.png
    An efficient algorithmic way to construct Boltzmann machine representations for arbitrary stabilizer code
    Yuan-Hang Zhang, Zhian Jia, Yu-Chun Wu, and Guang-Can Guo
    arXiv preprint arXiv:1809.08631, 2018