Temporal pattern recognition with delayed feedback spin-torque nano-oscillators.

The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this demonstration hinged on the intrinsic short-term memory of the oscillators. In this study, we extend the memory of the spin-torque nano-oscillators through time-delayed feedback. We leverage this extrinsic memory to increase the efficiency of solving pattern recognition tasks that require memory to discriminate different inputs. The large tunability of these non-linear oscillators allows us to control and optimize the delayed feedback memory using different operating conditions of applied current and magnetic field.

Vector network analyzer ferromagnetic resonance spectrometer with field differential detection.

This work presents a vector network analyzer ferromagnetic resonance (VNA-FMR) spectrometer with field differential detection. This technique differentiates the S-parameter by applying a small binary modulation field in addition to the DC bias field to the sample. By setting the modulation frequency sufficiently high, slow sensitivity fluctuations of the VNA, i.e., low-frequency components of the trace noise, which limit the signal-to-noise ratio of the conventional VNA-FMR spectrometer, can be effectively removed, resulting in a very clean FMR signal. This paper presents the details of the hardware implementation and measurement sequence as well as the data processing and analysis algorithms tailored for the FMR spectrum obtained with this technique. Because the VNA measures a complex S-parameter, it is possible to estimate the Gilbert damping parameter from the slope of the phase variation of the S-parameter with respect to the bias field. We show that this algorithm is more robust against noise than the conventional algorithm based on the linewidth.

Mutual synchronization of spin torque nano-oscillators through a long-range and tunable electrical coupling scheme.

The concept of spin-torque-driven high-frequency magnetization dynamics, allows the potential construction of complex networks of non-linear dynamical nanoscale systems, combining the field of spintronics and the study of non-linear systems. In the few previous demonstrations of synchronization of several spin-torque oscillators, the short-range nature of the magnetic coupling that was used has largely hampered a complete control of the synchronization process. Here we demonstrate the successful mutual synchronization of two spin-torque oscillators with a large separation distance through their long range self-emitted microwave currents. This leads to a strong improvement of both the emitted power and the linewidth. The full control of the synchronized state is achieved at the nanoscale through two active spin transfer torques, but also externally through an electrical delay line. These additional levels of control of the synchronization capability provide a new approach to develop spin-torque oscillator-based nanoscale microwave-devices going from microwave-sources to bio-inspired networks.

Neuromorphic Computing through Time-Multiplexing with a Spin-Torque Nano-Oscillator.

Fabricating powerful neuromorphic chips the size of a thumb requires miniaturizing their basic units: synapses and neurons. The challenge for neurons is to scale them down to submicrometer diameters while maintaining the properties that allow for reliable information processing: high signal to noise ratio, endurance, stability, reproducibility. In this work, we show that compact spin-torque nano-oscillators can naturally implement such neurons, and quantify their ability to realize an actual cognitive task. In particular, we show that they can naturally implement reservoir computing with high performance and detail the recipes for this capability.

Spin-torque resonant expulsion of the vortex core for an efficient radiofrequency detection scheme.

It has been proposed that high-frequency detectors based on the so-called spin-torque diode effect in spin transfer oscillators could eventually replace conventional Schottky diodes due to their nanoscale size, frequency tunability and large output sensitivity. Although a promising candidate for information and communications technology applications, the output voltage generated from this effect has still to be improved and, more pertinently, reduces drastically with decreasing radiofrequency (RF) current. Here we present a scheme for a new type of spintronics-based high-frequency detector based on the expulsion of the vortex core in a magnetic tunnel junction (MTJ). The resonant expulsion of the core leads to a large and sharp change in resistance associated with the difference in magnetoresistance between the vortex ground state and the final C-state configuration. Interestingly, this reversible effect is independent of the incoming RF current amplitude, offering a fast real-time RF threshold detector.

Understanding of Phase Noise Squeezing Under Fractional Synchronization of a Nonlinear Spin Transfer Vortex Oscillator.

We investigate experimentally the synchronization of vortex based spin transfer nano-oscillators to an external rf current whose frequency is at multiple integers, as well as at an integer fraction, of the oscillator frequency. Through a theoretical study of the locking mechanism, we highlight the crucial role of both the symmetries of the spin torques and the nonlinear properties of the oscillator in understanding the phase locking mechanism. In the locking regime, we report a phase noise reduction down to -90 dBc/Hz at 1 kHz offset frequency. Our demonstration that the phase noise of these nanoscale nonlinear oscillators can be tuned and eventually lessened, represents a key achievement for targeted radio frequency applications using spin torque devices.