Non-hermiticity in spintronics: oscillation death in coupled spintronic nano-oscillators through emerging exceptional points.

The emergence of exceptional points (EPs) in the parameter space of a non-hermitian (2D) eigenvalue problem has long been interest in mathematical physics, however, only in the last decade entered the scope of experiments. In coupled systems, EPs give rise to unique physical phenomena, and enable the development of highly sensitive sensors. Here, we demonstrate at room temperature the emergence of EPs in coupled spintronic nanoscale oscillators and exploit the system's non-hermiticity. We observe amplitude death of self-oscillations and other complex dynamics, and develop a linearized non-hermitian model of the coupled spintronic system, which describes the main experimental features. The room temperature operation, and CMOS compatibility of our spintronic nanoscale oscillators means that they are ready to be employed in a variety of applications, such as field, current or rotation sensors, radiofrequeny and wireless devices, and in dedicated neuromorphic computing hardware. Furthermore, their unique and versatile properties, notably their large nonlinear behavior, open up unprecedented perspectives in experiments as well as in theory on the physics of exceptional points expanding to strongly nonlinear systems.

Antiferromagnetic magnon spintronic based on nonreciprocal and nondegenerated ultra-fast spin-waves in the canted antiferromagnet α-Fe2O3.

Spin-waves in antiferromagnets hold the prospects for the development of faster, less power-hungry electronics and promising physics based on spin superfluids and coherent magnon condensates. For both these perspectives, addressing electrically coherent antiferromagnetic spin-waves is of importance, a prerequisite that has been so far elusive, because, unlike ferromagnets, antiferromagnets couple weakly to radiofrequency fields. Here, we demonstrate the detection of ultra-fast nonreciprocal spin-waves in the dipolar exchange regime of a canted antiferromagnet using both inductive and spintronic transducers. Using time-of-flight spin-wave spectroscopy on hematite (α-Fe2O3), we find that the magnon wave packets can propagate as fast as 20 kilometers/second for reciprocal bulk spin-wave modes and up to 6 kilometers/second for surface spin-waves propagating parallel to the antiferromagnetic Néel vector. We lastly achieve efficient electrical detection of nonreciprocal spin-wave transport using nonlocal inverse spin-Hall effects. The electrical detection of coherent nonreciprocal antiferromagnetic spin-waves paves the way for the development of antiferromagnetic and altermagnet-based magnonic devices.

Multilayer spintronic neural networks with radiofrequency connections.

Spintronic nano-synapses and nano-neurons perform neural network operations with high accuracy thanks to their rich, reproducible and controllable magnetization dynamics. These dynamical nanodevices could transform artificial intelligence hardware, provided they implement state-of-the-art deep neural networks. However, there is today no scalable way to connect them in multilayers. Here we show that the flagship nano-components of spintronics, magnetic tunnel junctions, can be connected into multilayer neural networks where they implement both synapses and neurons thanks to their magnetization dynamics, and communicate by processing, transmitting and receiving radiofrequency signals. We build a hardware spintronic neural network composed of nine magnetic tunnel junctions connected in two layers, and show that it natively classifies nonlinearly separable radiofrequency inputs with an accuracy of 97.7%. Using physical simulations, we demonstrate that a large network of nanoscale junctions can achieve state-of-the-art identification of drones from their radiofrequency transmissions, without digitization and consuming only a few milliwatts, which constitutes a gain of several orders of magnitude in power consumption compared to currently used techniques. This study lays the foundation for deep, dynamical, spintronic neural networks.

Parsonage-Turner Syndrome mimicking musculoskeletal shoulder pain: A case report during the SARS-CoV-2 pandemic era.

Parsonage-Turner Syndrome or neuralgic amyotrophy is a peripheral neuropathy typically characterized by an abrupt onset of pain, followed by progressive neurological deficits (e.g. weakness, atrophy, occasionally sensory abnormalities) that involve the upper limb, mainly the shoulder, encompassing an extensive spectrum of clinical manifestations, somehow difficult to recognize. This case report describes the proper management of a 35-year-old, bank employee and sports amateur who reported subtle and progressive upper limb disorder with previous history of neck pain. SARS-CoV-2 pandemic era made patient's access to the healthcare system more complicated. Nevertheless, proper management of knowledge, relevant aspects of telerehabilitation-based consultation for musculoskeletal pain, advanced skills, tools and technologies led the physiotherapist to suspect an atypical presentation of Parsonage-Turner Syndrome. Further, neurologist consultation and electromyography suggested signs of denervation in the serratus anterior and supraspinatus muscle. Therefore, an appropriate physiotherapist's screening for referral is conducted to correct diagnosis and thorough treatment.

Binding events through the mutual synchronization of spintronic nano-neurons.

The brain naturally binds events from different sources in unique concepts. It is hypothesized that this process occurs through the transient mutual synchronization of neurons located in different regions of the brain when the stimulus is presented. This mechanism of 'binding through synchronization' can be directly implemented in neural networks composed of coupled oscillators. To do so, the oscillators must be able to mutually synchronize for the range of inputs corresponding to a single class, and otherwise remain desynchronized. Here we show that the outstanding ability of spintronic nano-oscillators to mutually synchronize and the possibility to precisely control the occurrence of mutual synchronization by tuning the oscillator frequencies over wide ranges allows pattern recognition. We demonstrate experimentally on a simple task that three spintronic nano-oscillators can bind consecutive events and thus recognize and distinguish temporal sequences. This work is a step forward in the construction of neural networks that exploit the non-linear dynamic properties of their components to perform brain-inspired computations.

Effectiveness of Blue light photobiomodulation therapy in the treatment of chronic wounds. Results of the Blue Light for Ulcer Reduction (B.L.U.R.) Study.

BACKGROUND: Lower limb ulcers not responding to standard treatments after 8 weeks are defined as chronic wounds, and they are a significant medical problem. Blue light (410-430 nm) proved to be effective in treating wounds, but there is a lack of data on chronic wounds in clinical practice. The aim of the study was to determine if blue light photobiomodulation with EmoLED (Emoled Srl, Sesto Fiorentino, Florence, Italy) medical device in addition to standard of care is more effective compared to standard of care alone in promoting re-epithelialization of chronic wounds of lower limbs in 10 weeks. METHODS: Ninety patients affected by multiple or large area ulcers were enrolled. To minimize all variabilities, each patient has been used as control of himself. Primary endpoint was the comparison of the re-epithelialization rate expressed as a percentage of the difference between the initial and final area. Secondary endpoints were: treatment safety, pain reduction, wound area reduction trend over time, healing rate. RESULTS: At week 10, the wounds treated with EmoLED in addition to standard care showed a smaller residual wound area compared to the wounds treated with standard of care alone: 42.1% vs. 63.4% (P=0.029). The difference is particularly evident in venous leg ulcers, 33.3% vs. 60.1% (P=0.007). 17 treated wounds and 12 controls showed complete healing at week 10. Patients showed a significant reduction in pain (P=2×10-7). CONCLUSIONS: Blue light treatment in addition to standard of care accelerates consistently the re-epithelialization rate of chronic wounds, especially venous leg ulcers and increases the chances of total wound healing in 10 weeks.

Voltage-Controlled Reconfigurable Magnonic Crystal at the Sub-micrometer Scale.

Multiferroics offer an elegant means to implement voltage control and on the fly reconfigurability in microscopic, nanoscaled systems based on ferromagnetic materials. These properties are particularly interesting for the field of magnonics, where spin waves are used to perform advanced logical or analogue functions. Recently, the emergence of nanomagnonics is expected to eventually lead to the large-scale integration of magnonic devices. However, a compact voltage-controlled, on demand reconfigurable magnonic system has yet to be shown. Here, we introduce the combination of multiferroics with ferromagnets in a fully epitaxial heterostructure to achieve such voltage-controlled and reconfigurable magnonic systems. Imprinting a remnant electrical polarization in thin multiferroic BiFeO3 with a periodicity of 500 nm yields a modulation of the effective magnetic field in the micrometer-scale, ferromagnetic La2/3Sr1/3MnO3 magnonic waveguide. We evidence the magnetoelectric coupling by characterizing the spin wave propagation spectrum in this artificial, voltage induced, magnonic crystal and demonstrate the occurrence of a robust magnonic band gap with >20 dB rejection.

On the importance of primary and community healthcare in relation to global health and environmental threats: lessons from the COVID-19 crisis.

In the course of the COVID-19 pandemic, it has become clear that primary healthcare systems play a critical role in clinical care, such as patient screening, triage, physical and psychological support and also in promoting good community advice and awareness in coordination with secondary healthcare and preventive care. Because of the role of social and environmental factors in COVID-19 transmission and burden of disease, it is essential to ensure that there is adequate coordination of population-based health services and public health interventions. The COVID-19 pandemic has shown the primary and community healthcare (P&CHC) system's weaknesses worldwide. In many instances, P&CHC played only a minor role, the emphasis being on hospital and intensive care beds. This was compounded by political failures, in supporting local community resilience. Placing community building, social cohesion and resilience at the forefront of dealing with the COVID-19 crisis can help align solutions that provide a vision of 'planetary health'. This can be achieved by involving local well-being and participation in the face of any pervasive health and environmental crisis, including other epidemics and large-scale ecological crises. This paper proposes that P&CHC should take on two critical roles: first, to support local problem-solving efforts and to serve as a partner in innovative approaches to safeguarding community well-being; and second, to understand the local environment and health risks in the context of the global health perspective. We see this as an opportunity of immediate value and broad consequence beyond the control of the COVID-19 pandemic.

Influence of flicker noise and nonlinearity on the frequency spectrum of spin torque nano-oscillators.

The correlation of phase fluctuations in any type of oscillator fundamentally defines its spectral shape. However, in nonlinear oscillators, such as spin torque nano-oscillators, the frequency spectrum can become particularly complex. This is specifically true when not only considering thermal but also colored 1/f flicker noise processes, which are crucial in the context of the oscillator's long term stability. In this study, we address the frequency spectrum of spin torque oscillators in the regime of large-amplitude steady oscillations experimentally and as well theoretically. We particularly take both thermal and flicker noise into account. We perform a series of measurements of the phase noise and the spectrum on spin torque vortex oscillators, notably varying the measurement time duration. Furthermore, we develop the modelling of thermal and flicker noise in Thiele equation based simulations. We also derive the complete phase variance in the framework of the nonlinear auto-oscillator theory and deduce the actual frequency spectrum. We investigate its dependence on the measurement time duration and compare with the experimental results. Long term stability is important in several of the recent applicative developments of spin torque oscillators. This study brings some insights on how to better address this issue.

AbobotulinumtoxinA: A New Therapy for Hip Osteoarthritis. A Prospective Randomized Double-Blind Multicenter Study.

Background: Hip Osteoarthritis (OA) causes pain and disability. Here we evaluate abobotulinumtoxinA (Dysport®) (AboBoNT-A) injections versus placebo as a novel treatment option to improve hip range of motion, pain and quality of life. Methods: This prospective randomized double-blind multicenter study (EudraCT # 2012-004890-25) recruited 46 outpatients with hip OA who were randomized 2:1 to the Treatment Group (TG; 31 subjects), or the Placebo Group (PG; 15 subjects). The TG received 400 U of AboBoNT-A injected into the adductor muscles, and the PG received placebo solution. The primary endpoints were the difference in Harris Hip Score (HHS) and Visual Analogic Scale for pain (VAS) at Week 4 between groups (TG vs. PG). Secondary endpoints were the change from baseline in HHS, VAS pain, Medical Research Council scale for muscle strength (MRC) and Short Form scale (SF-36) scores. Results: In TG at Week 4, the HHS and VAS score were significantly improved compared to PG, and pairwise assessments showed significant improvements in HSS and VAS pain at each time point compared to baseline for TG. No significant changes were observed in MRC and SF-36 over time, though SF-36 showed a positive trend. There were no significant differences from baseline in the PG. No adverse events were detected in either treatment group. Conclusions: AboBoNT-A injections in hip OA improve range of motion and pain without any significant side effects.

Vowel recognition with four coupled spin-torque nano-oscillators.

In recent years, artificial neural networks have become the flagship algorithm of artificial intelligence1. In these systems, neuron activation functions are static, and computing is achieved through standard arithmetic operations. By contrast, a prominent branch of neuroinspired computing embraces the dynamical nature of the brain and proposes to endow each component of a neural network with dynamical functionality, such as oscillations, and to rely on emergent physical phenomena, such as synchronization2-6, for solving complex problems with small networks7-11. This approach is especially interesting for hardware implementations, because emerging nanoelectronic devices can provide compact and energy-efficient nonlinear auto-oscillators that mimic the periodic spiking activity of biological neurons12-16. The dynamical couplings between oscillators can then be used to mediate the synaptic communication between the artificial neurons. One challenge for using nanodevices in this way is to achieve learning, which requires fine control and tuning of their coupled oscillations17; the dynamical features of nanodevices can be difficult to control and prone to noise and variability18. Here we show that the outstanding tunability of spintronic nano-oscillators-that is, the possibility of accurately controlling their frequency across a wide range, through electrical current and magnetic field-can be used to address this challenge. We successfully train a hardware network of four spin-torque nano-oscillators to recognize spoken vowels by tuning their frequencies according to an automatic real-time learning rule. We show that the high experimental recognition rates stem from the ability of these oscillators to synchronize. Our results demonstrate that non-trivial pattern classification tasks can be achieved with small hardware neural networks by endowing them with nonlinear dynamical features such as oscillations and synchronization.

Ultra-low damping insulating magnetic thin films get perpendicular.

A magnetic material combining low losses and large perpendicular magnetic anisotropy (PMA) is still a missing brick in the magnonic and spintronic fields. We report here on the growth of ultrathin Bismuth doped Y3Fe5O12 (BiYIG) films on Gd3Ga5O12 (GGG) and substituted GGG (sGGG) (111) oriented substrates. A fine tuning of the PMA is obtained using both epitaxial strain and growth-induced anisotropies. Both spontaneously in-plane and out-of-plane magnetized thin films can be elaborated. Ferromagnetic Resonance (FMR) measurements demonstrate the high-dynamic quality of these BiYIG ultrathin films; PMA films with Gilbert damping values as low as 3 × 10-4 and FMR linewidth of 0.3 mT at 8 GHz are achieved even for films that do not exceed 30 nm in thickness. Moreover, we measure inverse spin hall effect (ISHE) on Pt/BiYIG stacks showing that the magnetic insulator's surface is transparent to spin current, making it appealing for spintronic applications.

Neuromorphic computing with nanoscale spintronic oscillators.

Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit 108 oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nanoscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way. For this reason, despite multiple theoretical proposals and several candidates, including memristive and superconducting oscillators, a proof of concept of neuromorphic computing using nanoscale oscillators has yet to be demonstrated. Here we show experimentally that a nanoscale spintronic oscillator (a magnetic tunnel junction) can be used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks. We also determine the regime of magnetization dynamics that leads to the greatest performance. These results, combined with the ability of the spintronic oscillators to interact with each other, and their long lifetime and low energy consumption, open up a path to fast, parallel, on-chip computation based on networks of oscillators.

Self-Injection Locking of a Vortex Spin Torque Oscillator by Delayed Feedback.

The self-synchronization of spin torque oscillators is investigated experimentally by re-injecting its radiofrequency (rf) current after a certain delay time. We demonstrate that the integrated power and spectral linewidth are improved for optimal delays. Moreover by varying the phase difference between the emitted power and the re-injected one, we find a clear oscillatory dependence on the phase difference with a 2π periodicity of the frequency of the oscillator as well as its power and linewidth. Such periodical behavior within the self-injection regime is well described by the general model of nonlinear auto-oscillators including not only a delayed rf current but also all spin torque forces responsible for the self-synchronization. Our results reveal new approaches for controlling the non-autonomous dynamics of spin torque oscillators, a key issue for rf spintronics applications as well as for the development of neuro-inspired spin-torque oscillators based devices.