Ultrafast stochastic spiking neurons based on field-free magnetic tunnel junction
In this study, we showcase the hardware implementation of stochastic spiking neurons (SSNs) utilizing the back hopping phenomenon in a field-free magnetic tunnel junction with a well-established fabrication process and excellent scalability. The neural network constructed using this SSN array demonstrates an ultrafast response speed on the order of tens of nanoseconds, a high accuracy of 97.6% in handwritten digit classification, and superior adaptability across various tasks, surpassing the performance of the majority of reported SSNs. This research carries significant implications, positioning our SSNs as promising candidates in the realm of efficient and robust neuromorphic computing applications.
Authors
- Wenjie Duan (ORCID: https://orcid.org/0000-0002-1251-3685)
- Tiaoyang Li (ORCID: https://orcid.org/0009-0002-2705-2751)
- Haizhong Zhang (ORCID: https://orcid.org/0000-0002-6696-7463)
- Li Wu (ORCID: https://orcid.org/0000-0002-1853-1286)
- Yapeng Zhao
- Wen‐Jie Chen (ORCID: https://orcid.org/0000-0002-9428-7828)
- Miao Pan (ORCID: https://orcid.org/0000-0002-2756-5859)
- Musheng Chen (ORCID: https://orcid.org/0000-0001-6960-5567)
- Changjin Wan
- Huiwu Mao
Institutions
- Quanzhou Normal University (CN)
- Nanjing University of Information Science and Technology (CN)
- Nanjing University of Science and Technology (CN)
- Fuzhou University (CN)
Publication Details
- Journal
- Applied Physics Letters
- Published
- 2025-08-04
- DOI
- https://doi.org/10.1063/5.0273136
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China