2024/04/05 by Sourabh Manna, Manna, Sourabh, Rohit Medwal +7 · 1 citation
Computer Science · Engineering · #Advanced Memory and Neural Computing #Applied Physics (physics.app-ph) #FOS: Physical sciences #Mesoscale and Nanoscale Physics (cond-mat.mes-hall) #Neural Networks and Applications #Neural Networks and Reservoir Computing #Other Condensed Matter (cond-mat.other)
paper · pdf · doi:10.48550/arxiv.2404.04023
openalex publication_date 2024/04/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Mutually coupled spin Hall nano-oscillators (SHNO) can exhibit binarized phase state, offering pathways to realize Ising machines and efficient neuromorphic hardware. Conventionally, phase binarization is achieved in coupled SHNOs via injecting an external microwave at twice of the oscillator frequency in presence of a biasing magnetic field. However, this technology poses potential challenges of higher energy consumption and complex circuit design. Moreover, fabrication-induced mismatch in SHNO dimensions may hinder mutual synchronization. Addressing these challenges, we demonstrate purely DC current-driven mutual synchronization and phase binarization of two non-identical nanoconstriction SHNOs without biasing magnetic field and microwave injection. We thoroughly investigate these phenomena and underlying mechanisms using micromagnetic simulation. We further demonstrate the bias field-free synchronized SHNO pair efficiently performing a reservoir computing benchmark learning task: sin and square wave classification, utilizing current tunable phase binarization. Our results showcase promising magnetization dynamics of coupled bias field-free SHNOs for future computing applications.