2023-12-18 カリフォルニア大学サンディエゴ校(UCSD)
◆これにより、真の乱数発生器の実装など、サイバーセキュリティの応用が可能となる可能性があります。この予想外の結果は、量子物質ベースのスパイキング振動子がニューロンを模倣する方法を示すため、人工知能とニューロモーフィックコンピューティングにも重要な意味を持っています。
＜関連情報＞
- https://today.ucsd.edu/story/spiking-nano-oscillators
- https://www.pnas.org/doi/10.1073/pnas.2303765120
同期したスパイキング・ナノシレーターにおける確率的遷移 Stochastic transition in synchronized spiking nanooscillators
Erbin Qiu , Pavel Salev, Felipe Torres , Henry Navarro , Robert C. Dynes , and Ivan K. Schuller
Proceedings of the National Academy of Sciences published:September 11, 2023
DOI:https://doi.org/10.1073/pnas.2303765120
Significance
Synchronization is a universal phenomenon commonly observed in nature, and it has been extensively studied in harmonic oscillators. Synchronization of spiking oscillators remains less explored despite the increasing interest in using spiking networks in novel computational approaches, such as neuromorphic computing. Here, we use Mott-material-based spiking nanooscillators as a case study to experimentally investigate the synchronization properties arising from the physical interactions between the devices. We found that the transition between different synchronization modes occurs via a stochastic regime in which the spiking pattern unpredictably alternates between the two integer modes instead of desynchronizing or entering a chaotic oscillation regime. This work highlights the unusual dynamic synchronization properties of spiking oscillators in contrast to conventional harmonic oscillators.
Abstract
This work reports that synchronization of Mott material-based nanoscale coupled spiking oscillators can be drastically different from that in conventional harmonic oscillators. We investigated the synchronization of spiking nanooscillators mediated by thermal interactions due to the close physical proximity of the devices. Controlling the driving voltage enables in-phase 1:1 and 2:1 integer synchronization modes between neighboring oscillators. Transition between these two integer modes occurs through an unusual stochastic synchronization regime instead of the loss of spiking coherence. In the stochastic synchronization regime, random length spiking sequences belonging to the 1:1 and 2:1 integer modes are intermixed. The occurrence of this stochasticity is an important factor that must be taken into account in the design of large-scale spiking networks for hardware-level implementation of novel computational paradigms such as neuromorphic and stochastic computing.
