Heterogeneous III-V/Si micro-ring laser array with multi-state non-volatile memory for ternary content-addressable memories
In this work, we introduce programmable memory elements embedded within III-V/Si light sources which facilitate non-volatile wavelength tuning. These non-volatile III-V/Si micro-ring lasers (MRLs) exhibit non-volatile wavelength shifts of ~80 pm with ~40 dB signal extinction ratio while consuming 0 electrical static tuning power. An array of 5 cascaded MRLs is demonstrated with each laser capable of 4 programmable non-volatile states, thus yielding 1024 unique states altogether. Write/erase operations were performed up to 100 cycles with non-volatile time duration lasting up to 24 h. These non-volatile lasers are used to demonstrate optical ternary content-addressable memories (O-TCAM) which can find utility in fast memory search and in-memory computing functions necessary for various machine learning algorithms. The end-to-end energy consumption of the non-volatile MRL O-TCAM with 5 ternary symbols is 1156 fJ/sym. This work provides an opportunity for realizing photonic memory applications in next generation non-volatile photonic systems.
Authors
- Yanir London (ORCID: https://orcid.org/0000-0003-2902-6397)
- Stanley Cheung (ORCID: https://orcid.org/0000-0002-4886-0013)
- Thomas Van Vaerenbergh (ORCID: https://orcid.org/0000-0002-7301-8610)
- Di Liang (ORCID: https://orcid.org/0000-0003-1366-0115)
- Géza Kurczveil (ORCID: https://orcid.org/0000-0003-1373-6087)
- Yiwei Peng (ORCID: https://orcid.org/0000-0002-5014-8527)
- Raymond G. Beausoleil (ORCID: https://orcid.org/0000-0003-1139-1660)
- Bassem Tossoun (ORCID: https://orcid.org/0000-0003-3608-8369)
- Yuan Yuan (ORCID: https://orcid.org/0000-0003-0907-9934)
- Chong Zhang (ORCID: https://orcid.org/0000-0001-5161-4326)
- Yingtao Hu (ORCID: https://orcid.org/0009-0001-4702-2763)
Institutions
- Northeastern University (US)
- North Carolina State University (US)
- University of Michigan (US)
- Hewlett Packard Enterprise (United States) (US)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-05-30
- DOI
- https://doi.org/10.1038/s41467-025-59832-w
- Citations
- 3
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 7.44
Funders
- U.S. Department of Energy
- Advanced Research Projects Agency - Energy
- University of California, Santa Barbara
- Advanced Research Projects Agency
- California NanoSystems Institute