How to Cite

The following references are required to be cited when using DPNEGF.

• For DPNEGF:

  Zou J, Zhouyin Z, Lin D, et al. Deep learning accelerated quantum transport simulations in nanoelectronics: From break junctions to field-effect transistors[J]. arXiv preprint arXiv:2411.08800, 2024.

  @article{zou2025deep,
    title={Deep Learning Accelerated Quantum Transport Simulations in Nanoelectronics: From Break Junctions to Field-Effect Transistors}, 
    author={Jijie Zou and Zhanghao Zhouyin and Dongying Lin and Yike Huang and Linfeng Zhang and Shimin Hou and Qiangqiang Gu},
    year={2025},
    eprint={2411.08800},
    archivePrefix={arXiv},
    primaryClass={cond-mat.mes-hall},
    url={https://arxiv.org/abs/2411.08800}}     
  

DPNEGF is compatible with both modeling strategies available in DeePTB: DeePTB-SK and DeePTB-E3. Specifically:

• For DeePTB-SK:

  Q. Gu, Z. Zhouyin, S. K. Pandey, P. Zhang, L. Zhang, and W. E, Deep Learning Tight-Binding Approach for Large-Scale Electronic Simulations at Finite Temperatures with Ab Initio Accuracy, Nat Commun 15, 6772 (2024).

  @article{guDeep2024,
    title = {Deep Learning Tight-Binding Approach for Large-Scale Electronic Simulations at Finite Temperatures with  Ab Initio Accuracy},
    author = {Gu, Qiangqiang and Zhouyin, Zhanghao and Pandey, Shishir Kumar and Zhang, Peng and Zhang, Linfeng and E,    Weinan},
    year = {2024},
    month = aug,
    journal = {Nature Communications},
    volume = {15},
    number = {1},
    pages = {6772},
    publisher = {Nature Publishing Group},
    issn = {2041-1723},
    doi = {10.1038/s41467-024-51006-4},
    copyright = {2024 The Author(s)},
    keywords = {Computational methods,Electronic properties and materials,Electronic structure}
  }
  

• For DeePTB-E3:

  Z. Zhouyin, Z. Gan, S. K. Pandey, L. Zhang, and Q. Gu, Learning Local Equivariant Representations for Quantum Operators, arXiv:2407.06053.

  @misc{zhouyinLearning2024,
    title = {Learning Local Equivariant Representations for Quantum Operators},
    author = {Zhouyin, Zhanghao and Gan, Zixi and Pandey, Shishir Kumar and Zhang, Linfeng and Gu, Qiangqiang},
    year = {2024},
    month = jul,
    number = {arXiv:2407.06053},
    eprint = {2407.06053},
    primaryclass = {cond-mat, physics:quant-ph},
    publisher = {arXiv},
    doi = {10.48550/arXiv.2407.06053},
    archiveprefix = {arXiv},
    keywords = {Computer Science - Machine Learning,Condensed Matter - Materials Science,Quantum Physics},
  }