ArticleNature communications2022
Local bifurcation with spin-transfer torque in superparamagnetic tunnel junctions.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- 250 magnetic tunnel junctions-based probabilistic Ising machine.Nature communications · 2026Article
- Superior probabilistic computing using operationally stable probabilistic-bit constructed by a manganite nanowire.National science review · 2025Article
- CMOS plus stochastic nanomagnets enabling heterogeneous computers for probabilistic inference and learning.Nature communications · 2024Article
- Local bifurcation with spin-transfer torque in superparamagnetic tunnel junctions.Nature communications · 2022Article
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Authors and funding
5 authors.
Funding
Abstract
Modulation of the energy landscape by external perturbations governs various thermally-activated phenomena, described by the Arrhenius law. Thermal fluctuation of nanoscale magnetic tunnel junctions with spin-transfer torque (STT) shows promise for unconventional computing, whereas its rigorous representation, based on the Néel-Arrhenius law, has been controversial. In particular, the exponents for thermally-activated switching rate therein, have been inaccessible with conventional thermally-stable nanomagnets with decade-long retention time. Here we approach the Néel-Arrhenius law with STT utilising superparamagnetic tunnel junctions that have high sensitivity to external perturbations and determine the exponents through several independent measurements including homodyne-detected ferromagnetic resonance, nanosecond STT switching, and random telegraph noise. Furthermore, we show that the results are comprehensively described by a concept of local bifurcation observed in various physical systems. The findings demonstrate the capability of superparamagnetic tunnel junction as a useful tester for statistical physics as well as sophisticated engineering of probabilistic computing hardware with a rigorous mathematical foundation.
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