We investigate the impact of localized laser heating on the auto-oscillation properties of a 170 nm wide nano-constriction spin Hall nano-oscillators (SHNO) fabricated from a NiFe/Pt bilayer on a sapphire substrate. A 532 nm continuous wave laser is focused down to a spot size of about 500 nm at a power ranging from 0 to 12 mW. Through a comparison with resistive heating, we estimate a local temperature rise of about 8 K/mW. We demonstrate reversible laser tuning of the threshold current, the frequency, and the peak power, and find that the SHNO frequency can be tuned by up to 350 MHz, which is over three times more than the current tuning alone. Increasing the temperature also results in increased signal jitter, an increased threshold current, and a reduced maximum current for auto-oscillations. Our results open up for optical control of single SHNOs in larger SHNO networks without the need for additional voltage gates.
Artificial Neural Network (ANN) -- Oscillatory Neural Network (ONN) Hybrid System Using Domain-Wall Synapse Devices and Nano-Constriction Spin Hall Nano Oscillators
Indian Institute of Technology Bombay（印度理工学院孟买分校）；Centre for Semiconductor Technologies (SemiX), Indian Institute of Technology Bombay（印度理工学院半导体技术中心 (SemiX)）
Spin Hall nano-oscillators (SHNOs) utilize pure spin currents to drive local regions of magnetic films and nanostructures into auto-oscillating precession. If such regions are placed in close proximity to each other they can interact and sometimes mutually synchronize, in pairs or in short linear chains. Here we demonstrate robust mutual synchronization of two-dimensional SHNO arrays ranging from 2 x 2 to 8 x 8 nano-constrictions, observed both electrically and using micro-Brillouin Light Scattering microscopy. The signal quality factor, $Q=f/Δf$, increases linearly with number of mutually syn…
We study the current tunable microwave signal properties of nano-constriction based spin Hall nano-oscillators (SHNOs) in oblique magnetic fields as a function of the nano-constriction width, $w=$~50--140 nm. The threshold current is found to scale linearly with $w$, defining a constant threshold current density of $J_{th}=$ 1.7 $\times$ 10$^{8}$ A/cm$^2$. While the current dependence of the microwave frequency shows the same generic non-monotonic behavior for all $w\geqslant$ 80 nm, the quality of the generated microwave signal improves strongly with $w$, showing a linear $w$ dependence for b…
Reconfigurable field-free spin Hall nano-oscillators enabled by crystallographic anisotropy in epitaxial Co/Pt
University of Gothenburg（哥德堡大学）；Indian Institute of Science Education and Research Bhopal（印度科学教育研究所博帕尔分校）；Northwestern University（西北大学）；Tohoku University（东北大学）
Arrays of spin-torque nano-oscillators are promising for broadband microwave signal detection and processing, as well as for neuromorphic computing. In many of these applications, the oscillators should be engineered to have equally-spaced frequencies and equal sensitivity to microwave inputs. Here we design spin-torque nano-oscillator arrays with these rules and estimate their optimum size for a given sensitivity, as well as the frequency range that they cover. For this purpose, we explore analytically and numerically conditions to obtain vortex spin-torque nano-oscillators with equally-space…
We investigate a W-Ta alloying route to reduce the auto-oscillation current densities and the power consumption of nano-constriction based spin Hall nano oscillators. Using spin-torque ferromagnetic resonance (ST-FMR) measurements on microbars of W$_{\text{100-x}}$Ta$_{\text{x}}$(5 nm)/CoFeB(t)/MgO stacks with t = 1.4, 1.8, and 2.0 nm, we measure a substantial improvement in both the spin-orbit torque efficiency and the spin Hall conductivity. We demonstrate a 34\% reduction in threshold auto-oscillation current density, which translates into a 64\% reduction in power consumption as compared t…
Magnetic skyrmions are particle-like topological spin configurations, which can carry binary information and thus are promising building blocks for future spintronic devices. In this work, we investigate the relationship between the skyrmion dynamics and the characteristics of injected current in a skyrmion-based spin torque nano-oscillator, where the excitation source is introduced from a point nano-contact at the center of the nanodisk. It is found that the skyrmion will move away from the center of the nanodisk if it is driven by a spin-polarized current; however, it will return to the init…
A theoretical study of delayed feedback in a spin-torque nano-oscillator model is presented. The feedback acts as a modulation of the supercriticality, which results in changes in the oscillator frequency through a strong nonlinearity, amplitude modulations, and a rich modulation sideband structure in the power spectrum at long delays. Modulation sidebands persist at finite temperatures but some of the complex structure is lost through the finite coherence time of the oscillations.
We study mutual synchronization in double nanoconstriction-based spin Hall nano-oscillators (SHNOs) under weak in-plane fields ($μ_0H_\mathrm{IP}$ = 30-40 mT) and also investigate its angular dependence. We compare SHNOs with different nano-constriction spacings of 300 and 900 nm. In all devices, mutual synchronization occurs below a certain critical angle, which is higher for the 300 nm spacing than for the 900 nm spacing, reflecting the stronger coupling at shorter distances. Alongside the synchronization, we observe a strong second harmonic consistent with predictions that the synchronizati…
Pattern classification architectures leveraging the physics of coupled nano-oscillators have been demonstrated as promising alternative computing approaches, but lack effective learning algorithms. In this work, we propose a nano-oscillator based classification architecture where the natural frequencies of the oscillators are learned linear combinations of the inputs, and define an offline learning algorithm based on gradient back-propagation. Our results show significant classification improvements over a related approach with online learning. We also compare our architecture with a standard …
Spin-torque nano-oscillators can emulate neurons at the nanoscale. Recent works show that the non-linearity of their oscillation amplitude can be leveraged to achieve waveform classification for an input signal encoded in the amplitude of the input voltage. Here we show that the frequency and the phase of the oscillator can also be used to recognize waveforms. For this purpose, we phase-lock the oscillator to the input waveform, which carries information in its modulated frequency. In this way we considerably decrease amplitude, phase and frequency noise. We show that this method allows classi…
Nanomagnetic oscillator is a key component for radio-frequency (RF) signal generation in many nano-scale spintronic devices. However, the actuation mechanisms of nanomagnetic oscillators are mostly current-based, which is energy inefficient at nanoscale due to Joule heating. In this study, we present a new actuation mechanism for nanomagnetic oscillator with pure voltage input using a multiferroic structure. An AC voltage with a DC bias is applied to the piezoelectric substrate, and steady perpendicular magnetic oscillation is achieved in the attached Ni disk when the frequency of the voltage …
We study the agility of current-tunable oscillators based on a magnetic vortex orbiting around a point contact in spin-valves. Theory predicts frequency-tuning by currents occurs at constant orbital radius, so an exceptional agility is anticipated. To test this, we have inserted an oscillator in a microwave interferometer to apply abrupt current variations while time resolving its emission. Using frequency shift keying, we show that the oscillator can switch between two stabilized frequencies differing by 25% in less than ten periods. With a wide frequency tunability and a good agility, such o…
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 m…
We describe the construction and characterisation of a nano-oscillator formed by a Paul trap. The frequency and temperature stability of the nano-oscillator was measured over several days allowing us to identify the major sources of trap and environmental fluctuations. We measure an overall frequency stability of 2 ppm/hr and a temperature stability of more than 5 hours via the Allan deviation. Importantly, we find that the charge on the nanoscillator is stable over a timescale of at least two weeks and that the mass of the oscillator, can be measured with a 3 % uncertainty. This allows us to …
Spin Hall nano-oscillators (SHNOs) are emerging spintronic devices for microwave signal generation and oscillator based neuromorphic computing combining nano-scale footprint, fast and ultra-wide microwave frequency tunability, CMOS compatibility, and strong non-linear properties providing robust large-scale mutual synchronization in chains and two-dimensional arrays. While SHNOs can be tuned via magnetic fields and the drive current, neither approach is conducive for individual SHNO control in large arrays. Here, we demonstrate electrically gated W/CoFeB/MgO nano-constrictions in which the vol…
We demonstrate field and current controlled magnetodynamics in nanocontact spin-torque nano-oscillators (STNOs) based on orthogonal magnetic tunnel junctions (MTJs). We systematically analyze the microwave properties (frequency $f$, linewidth $Δf$, power $P$, and frequency tunability $df/dI$) with their physical origins---perpendicular magnetic anisotropy (PMA), damping-like and field-like spin transfer torque (STT), and voltage-controlled magnetic anisotropy (VCMA). These devices present several advantageous characteristics: high emission frequencies ($f> 20$ GHz), high frequency tunability (…
Can we build small neuromorphic chips capable of training deep networks with billions of parameters? This challenge requires hardware neurons and synapses with nanometric dimensions, which can be individually tuned, and densely connected. While nanosynaptic devices have been pursued actively in recent years, much less has been done on nanoscale artificial neurons. In this paper, we show that spintronic nano-oscillators are promising to implement analog hardware neurons that can be densely interconnected through electromagnetic signals. We show how spintronic oscillators maps the requirements o…
The advantage of an ultra-fast frequency-tunability of spin-torque nano-oscillators (STNOs) that have large (> 100MHz) relaxation frequency of amplitude fluctuations is exploited to realize ultra-fast wide-band time-resolved spectral analysis at nanosecond time scale with the frequency resolution limited only by the 'bandwidth' theorem. The demonstration is performed with an STNO generating in the 9 GHz frequency range, and comprised of a perpendicular polarizer and a perpendicularly and uniformly magnetized 'free' layer. It is shown that such a uniform-state STNO-based spectrum analyzer can e…
Spin-torque nano-oscillators (STNOs) are a type of nanoscale microwave auto-oscillators utilizing spin-torque to generate magnetodynamics with great promise for applications in microwaves, magnetic memory, and neuromorphic computing. Here, we report the first demonstration of exchange-spring STNOs, with an exchange-spring ([Co/Pd]-Co) reference layer and a perpendicular ([Co/Ni]) free layer. This magnetic configuration results in high-frequency (>10 GHz) microwave emission at a zero magnetic field and exchange-spring dynamics in the reference layer and the observation of magnetic droplet solit…
This Letter is a micromagnetic simulation-based study on the GHz-frequency ferromagnetic resonances for the detection of magnetic nanoparticles (MNPs) using spin current nano-oscillator (SCNO) operating in precession mode as a spintronic biosensor. The magnetic stray fields from the MNPs in an antibody-antigen-MNP complex on the SCNO surface modify the ferromagnetic resonance peaks and generate measurable resonance peak shifts. Moreover, our results strongly indicate the position-sensitive behavior of the SCNO biosensor and ways to eradicate this effect to facilitate better bio-sensing perform…
We demonstrate low-operational-current W/Co$_{20}$Fe$_{60}$B$_{20}$/MgO spin Hall nano-oscillators (SHNOs) on highly resistive silicon (HiR-Si) substrates. Thanks to a record high spin Hall angle of the $β$-phase W ($θ_{SH}$ = -0.53), a very low threshold current density of 3.3 $\times$ 10$^{7}$ A/cm$^2$ can be achieved. Together with their very wide frequency tunability (7-28 GHz), promoted by a moderate perpendicular magnetic anisotropy, this makes HiR-Si/W/CoFeB based SHNOs potential candidates for wide-band microwave signal generation. Their CMOS compatibility offers a promising route towa…
We demonstrate the compositional effect on the magnetodynamic and auto-oscillations properties of Ni100-xFex/Pt (x= 10 to 40) nanoconstriction based spin Hall nano-oscillators. Using spin-torque ferromagnetic resonance (ST-FMR) performed on microstrips, we measure a significant reduction in both damping and spin Hall efficiency with increasing Fe content, which lowers the spin pumping contribution. The strong compositional effect on spin Hall efficiency is primarily attributed to the increased saturation magnetization in Fe-rich devices. As a direct consequence, higher current densities are re…
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 …
