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Phase locking of ultra-low power consumption stochastic magnetic bits induced by colored noise

Author

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  • Liao, Zhiqiang
  • Ma, Kaijie
  • Tang, Siyi
  • Sarker, Md Shamim
  • Yamahara, Hiroyasu
  • Tabata, Hitoshi

Abstract

Superparamagnetic tunnel junctions (STJs) are nanostructures with very low turnover barriers. The barrier height of an STJ is generally equal to the heat energy at room temperature; thus, it can oscillate automatically without external driving. Previous studies have shown that the randomness of an STJ can be driven by a subthreshold voltage. This synchronization can be adjusted using electrical noise, which is often considered as zero-field Gaussian white noise. However, the actual circuit and environment are inevitably associated with colored noise, which has not been considered previously. In this work, numerical simulations were performed to study the phase-locking characteristics of a single STJ with the aid of several typical types of colored noise. The results show that the phase-locked behavior of an STJ can be effectively enhanced by colored noise whose power spectral density per unit of bandwidth is proportional to its frequency. Meanwhile, colored noise whose power spectral density per unit of bandwidth and frequency are inversely proportional can suppress the synchronization of STJs by suppressing the increase in junction frequency.

Suggested Citation

  • Liao, Zhiqiang & Ma, Kaijie & Tang, Siyi & Sarker, Md Shamim & Yamahara, Hiroyasu & Tabata, Hitoshi, 2021. "Phase locking of ultra-low power consumption stochastic magnetic bits induced by colored noise," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    • Handle: RePEc:eee:chsofr:v:151:y:2021:i:c:s0960077921006160
    DOI: 10.1016/j.chaos.2021.111262
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    References listed on IDEAS

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    1. Alice Mizrahi & Tifenn Hirtzlin & Akio Fukushima & Hitoshi Kubota & Shinji Yuasa & Julie Grollier & Damien Querlioz, 2018. "Neural-like computing with populations of superparamagnetic basis functions," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
    2. Liu, Jian & Qiao, Zijian & Ding, Xiaojian & Hu, Bing & Zang, Chuanlai, 2021. "Stochastic resonance induced weak signal enhancement over controllable potential-well asymmetry," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    3. Jacob Torrejon & Mathieu Riou & Flavio Abreu Araujo & Sumito Tsunegi & Guru Khalsa & Damien Querlioz & Paolo Bortolotti & Vincent Cros & Kay Yakushiji & Akio Fukushima & Hitoshi Kubota & Shinji Yuasa , 2017. "Neuromorphic computing with nanoscale spintronic oscillators," Nature, Nature, vol. 547(7664), pages 428-431, July.
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    Cited by:

    1. Shi, Zhuozheng & Liao, Zhiqiang & Tabata, Hitoshi, 2022. "Boosting learning ability of overdamped bistable stochastic resonance system based physical reservoir computing model by time-delayed feedback," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    2. Liao, Zhiqiang & Wang, Zeyu & Yamahara, Hiroyasu & Tabata, Hitoshi, 2021. "Echo state network activation function based on bistable stochastic resonance," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).

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