The rich physics of spin transfer nano-oscillators (STNO) has provoked a huge interest to create a new generation of multi-functional microwave spintronic devices . It has been often emphasized that their nonlinear behavior gives a unique opportunity to tune their radiofrequency (rf) properties but at the cost of large phase noise, not compatible with practical applications. To tackle this issue as well as to open the opportunities to new developments for non-boolean computations , one strategy is to use electrical synchronization of STOs through the rf current. Thereby, it is crucial to understand how the synchronization forces transmitted through the electric current. In this talk, we will first present the results of an experimental study showing the self-synchronization of STNO by re-injecting its rf current after a certain delay time . In the second part, we demonstrate that the synchronization of two vortex-STNOs connected in parallel can be tuned either by an artificial delay or by the spin transfer torques . The synchronization of spin-torque oscillators, combined with the drastic improvement of the rf-features (linewidth decreases by a factor of 2 and power increases by a factor of 4) in the synchronized state, marks an important milestone towards a new generation of rf-devices based on STNO.
The authors acknowledge the financial support from ANR agency (SPINNOVA: ANR-11-NANO-0016) and EU grant (MOSAIC: ICT-FP7-317950).
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 R. Lebrun et al., arXiv:1601.01247 (2016)
The brain displays many features typical of non-linear dynamical networks, such as synchronization or chaotic behaviour. These observations have inspired a whole class of models that harness the power of complex non-linear dynamical networks for computing. In this framework, neurons are modeled as non-linear oscillators, and synapses as the coupling between oscillators. These abstract models are very good at processing waveforms for pattern recognition or at generating precise time sequences useful for robotic motion. However there are very few hardware implementations of these systems, because large numbers of interacting non-linear oscillators are indeed. In this talk, I will show that coupled spin-torque nano-oscillators are very promising for realizing cognitive computing at the nanometer and nanosecond scale, and will present our first results in this direction.