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Temperature effect on a weighted vortex spin-torque nano-oscillator for neuromorphic computing

Scientific reports, 2024-05, Vol.14 (1), p.10043-10043 [Peer Reviewed Journal]

2024. The Author(s). ;The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-024-60929-3 ;PMID: 38698145

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  • Title:
    Temperature effect on a weighted vortex spin-torque nano-oscillator for neuromorphic computing
  • Author: Li, Ren ; Rezaeiyan, Yasser ; Böhnert, Tim ; Schulman, Alejandro ; Ferreira, Ricardo ; Farkhani, Hooman ; Moradi, Farshad
  • Subjects: Heating ; Neural networks ; Oscillators ; Synaptic strength ; Temperature effects ; Torque ; Vortices
  • Is Part Of: Scientific reports, 2024-05, Vol.14 (1), p.10043-10043
  • Description: In this work, we present fabricated magnetic tunnel junctions (MTJs) that can serve as magnetic memories (MMs) or vortex spin-torque nano-oscillators (STNOs) depending on the device geometry. We explore the heating effect on the devices to study how the performance of a neuromorphic computing system (NCS) consisting of MMs and STNOs can be enhanced by temperature. We further applied a neural network for waveform classification applications. The resistance of MMs represents the synaptic weights of the NCS, while temperature acts as an extra degree of freedom in changing the weights and TMR, as their anti-parallel resistance is temperature sensitive, and parallel resistance is temperature independent. Given the advantage of using heat for such a network, we envision using a vertical-cavity surface-emitting laser (VCSEL) to selectively heat MMs and/or STNO when needed. We found that when heating MMs only, STNO only, or both MMs and STNO, from 25 to 75 °C, the output power of the STNO increases by 24.7%, 72%, and 92.3%, respectively. Our study shows that temperature can be used to improve the output power of neural networks, and we intend to pave the way for future implementation of a low-area and high-speed VCSEL-assisted spintronic NCS.
  • Publisher: England: Nature Publishing Group
  • Language: English
  • Identifier: EISSN: 2045-2322
    DOI: 10.1038/s41598-024-60929-3
    PMID: 38698145
  • Source: PubMed Central
    ProQuest Central
    DOAJ Directory of Open Access Journals
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