Van der Waals magnets are uniquely positioned at the intersection between two-dimensional materials, antiferromagnetic spintronics, and magnonics. The interlayer exchange interaction in these materials enables antiferromagnetic resonances to be accessed at gigahertz frequencies. Consequently, these layered antiferromagnets are intriguing materials out of which quantum hybrid magnonic devices can be fashioned. Here, we use both a modified macrospin model and micromagnetic simulations to demonstrate a comprehensive antiferromagnetic resonance spectra in van der Waals magnets near the ultrathin (monolayer) limit. The number of optical and acoustic magnon modes, as well as the mode frequencies, are found to be exquisitely sensitive to the number of layers. We discover a self-hybridization effect where pairs of either optical or acoustic magnons are found to interact and self-hybridize through the dynamic exchange interaction. This leads to characteristic avoided energy level crossings in the energy spectra. Through simulations, we show that, by electrically controlling the damping of surface layers within heterostructures, both the strength and number of avoided energy level crossings in the magnon spectra can be controlled.

In-plane uniformity of narrow-gap semiconductor $\mathrm{In}\mathrm{As}$/$\mathrm{Ga}\mathrm{Sb}$ type-II superlattice (T2SL) wafer is a crucial yet hard-to-evaluate prerequisite for high-performance long-wavelength infrared optoelectronic device applications of, e.g., focal-plane-array (FPA) photodetectors. In this work, we report a modulated photoluminescence-mapping (PL-mapping) study of $\mathrm{In}\mathrm{As}$/$\mathrm{Ga}\mathrm{Sb}$ T2SL in long-wavelength infrared range with a spatial resolution of a typical FPA-pixel scale. Spatial distributions are analyzed of PL-peak energy, linewidth, and integral intensity, which indicate a high in-plane uniformity of effective band gap but a considerable fluctuation of radiative recombination. The in-plane distributions of effective carrier lifetime and Shockley-Read-Hall defect concentration are evaluated, with the aid of a model that takes into account the pumping power dependence of the PL integral intensity. The results reveal a considerable in-plane nonuniformity of the optoelectronic response that may restrict the performance of the derivative FPA photodetector, and indicate the modulated PL mapping of a good pathway particularly for uniformity analysis of long-wavelength infrared FPA semiconductors.

Feedback amplification is a key technique for synthesizing various functionalities, especially in electronic circuits involving op amps. This paper presents a quantum version of this methodology, where the general phase-preserving quantum amplifier and coherent (i.e., measurement-free) feedback are employed to construct various types of systems having useful functionalities: quantum versions of differentiator, integrator, self-oscillator, and active filters. The class of active filters includes the Butterworth filter, which can be used to enhance the capacity of an optical quantum communication channel, and the nonreciprocal amplifier, which enables measurement of a superconducting qubits system as well as protection of it by separating input from output fields. A particularly detailed investigation is performed on the active phase-canceling filter for realizing a broadband gravitational-wave detector; that is, the feedback-amplification method is used to construct an active filter that compensates the phase delay of the signal and eventually recovers the sensitivity in the high-frequency regime.

Efforts by numerous research groups have provided a deeper insight into the physical mechanisms behind the power absorption of single-domain magnetic nanoparticles in magnetic-fluid-hyperthermia applications and theoretical models now account for the main experimental observations. However, the role of all parameters relevant to the magnetic relaxation remains a matter of debate. Here, we employ a nonlinear model for the magnetic relaxation of single-domain magnetic nanoparticles with uniaxial effective anisotropy and evaluate the influence of particle-intrinsic parameters as well as experimental conditions on the power absorption of both noninteracting and interacting systems (linear arrangements). These effects are assessed through the enclosed hysteresis area of the magnetization loops as a function of relative anisotropy $h_K$ (the anisotropy field with respect to the amplitude of the ac field), i.e., the “area curve” of the system. These curves can be divided into four regions with distinct magnetic responses and boundaries that depend on the particle size, frequency of the applied field and interactions. Interactions change the effective anisotropy of the system and shift the area curve towards lower $h_K$ values. For the low relative anisotropy range, dipolar interactions increase the area of the hysteresis loops [thus, the specific power absorption (SPA)], while they are detrimental or produce nonsignificant effects for the range of high relative anisotropy. Our study resolves seemingly contradictory results of interaction effects in linear arrangements recently reported in the literature. Simulations of randomly oriented particles and chains were contrasted with the oriented cases. An analytical approach and the thermal interpretation of its validity range are discussed, both aimed at the design of nanoparticles and the choice of the experimental conditions for optimal heating. We find that systems with low-thermal-fluctuation influence are better candidates for the application due to their high SPA values.

We present a surface-passivation method that reduces surface-related losses by almost 2 orders of magnitude in a highly miniaturized $\mathrm{Ga}\mathrm{As}$ open microcavity. The microcavity consists of a curved dielectric distributed Bragg reflector with radius of approximately $10\mu \mathrm{m}$ paired with a $\mathrm{Ga}\mathrm{As}$-based heterostructure. The heterostructure consists of a semiconductor distributed Bragg reflector followed by an $n$-$i$-$p$ diode with a layer of quantum dots in the intrinsic region. Free-carrier absorption in the highly-$n$-doped and highly-$p$-doped layers is minimized by our positioning them close to a node of the vacuum electromagnetic field. The surface, however, resides at an antinode of the vacuum field and results in significant loss. These losses are much reduced by surface passivation. The strong dependence on wavelength implies that the main effect of the surface passivation is to eliminate the surface electric field, thereby quenching below-band-gap absorption via a Franz-Keldysh-like effect. An additional benefit is that the surface passivation reduces scattering at the $\mathrm{Ga}\mathrm{As}$ surface. These results are important in other nanophotonic devices that rely on a $\mathrm{Ga}\mathrm{As}$-vacuum interface to confine the electromagnetic field.

Calibration of sensors is a fundamental step in validating their operation. This can be a demanding task, as it relies on acquiring detailed modeling of the device, which can be aggravated by its possible dependence upon multiple parameters. Machine learning provides a handy solution to this issue, operating a mapping between the parameters and the device response, without needing additional specific information on its functioning. Here, we demonstrate the application of a neural-network-based algorithm for the calibration of integrated photonic devices depending on two parameters. We show that a reliable characterization is achievable by carefully selecting an appropriate network training strategy. These results show the viability of this approach as an effective tool for the multiparameter calibration of sensors characterized by complex transduction functions. Furthermore, the approach is proven to be versatile and promising for mass production, as the same neural network is able to calibrate different devices that have the same structure.

We have fabricated an array of subgap kinetic inductance detectors (SKIDs) made of granular aluminum ($T_c\sim 2$ K) sensitive in the 80–90 GHz frequency band and operating at 300 mK. We measure a noise equivalent power of $1.3\times {10}^{-16}{\mathrm{W}/\mathrm{Hz}}^{0.5}$ on average and $2.6\times {10}^{-17}{\mathrm{W}/\mathrm{Hz}}^{0.5}$ at best, for an illuminating power of 50 fW per pixel. Even though the circuit design of SKIDs is identical to that of the kinetic inductance detectors, the SKIDs operating principle is based on their sensitivity to subgap excitations. This detection scheme is advantageous because it avoids having to lower the operating temperature proportionally to the lowest detectable frequency. The SKIDs presented here are intrinsically selecting the 80–90 GHz frequency band, well below the superconducting spectral gap of the film, at approximately 180 GHz.

Deep learning is the backbone of artificial-intelligence technologies, and it can be regarded as a kind of multilayer feedforward neural network. An essence of deep learning is information propagation through layers. This suggests that there is a connection between deep neural networks and dynamical systems in the sense that information propagation is explicitly modeled by the time evolution of dynamical systems. In this study, we perform pattern recognition based on the optimal control of continuous-time dynamical systems, which is suitable for physical hardware implementation. The learning is based on the adjoint method to optimally control dynamical systems, and the deep (virtual) network structures based on the time evolution of the systems are used for processing input information. As a key example, we apply the dynamics-based recognition approach to an optoelectronic delay system and demonstrate that the use of the delay system allows for image recognition and nonlinear classifications using only a few control signals. This is in contrast to conventional multilayer neural networks, which require a large number of weight parameters to be trained. The proposed approach provides insight into the mechanisms of deep network processing in the framework of an optimal control problem and presents a pathway for realizing physical computing hardware.

Using a coupled parametric resonator array for generating and propagating a topological soliton in its rotating-frame phase space is theoretically and numerically investigated. In an analogy with the well-known ${\varphi }^4$ model, the existence of a soliton is topologically protected, as the boundary of two different phase domains of parametric oscillation. Numerical simulation indicates that propagation can be triggered by switching of the phase state of one specific resonator, and the effects of damping, collision, and symmetry lifting by the harmonic drive on the propagation dynamics are studied. The topological soliton can be implemented by using electromechanical resonators, which allow its propagation dynamics to be precisely electrically controlled and provide a fully controlled on-chip test bed for the study of a topological soliton.

In quantum optomechanics, finding materials and strategies to limit losses has been crucial to the progress of the field. Recently, superfluid ${}^4\mathrm{He}$ was proposed as a promising mechanical element for quantum optomechanics. This quantum fluid shows highly desirable properties (e.g., extremely low acoustic loss) for a quantum optomechanical system. In current implementations, superfluid optomechanical systems suffer from external sources of loss, which spoils the quality factor of resonators. In this work, we propose an alternate implementation, exploiting nanofluidic confinement. Our approach, based on acoustic resonators formed within phononic nanostructures, aims at limiting radiation losses to preserve the intrinsic properties of superfluid ${}^4\mathrm{He}$. In this work, we estimate the optomechanical system parameters. Using recent theory, we derive the expected quality factors for acoustic resonators in different thermodynamic conditions. We calculate the sources of loss induced by the phononic nanostructures with numerical simulations. Our results indicate the feasibility of the proposed approach in a broad range of parameters, which opens prospects for more complex geometries.

The recent experiment [Y. Wang et al., Science 366, 1125 (2019)] on magnon-mediated spin-transfer torque (MSTT) was interpreted in terms of a picture where magnons are excited within an antiferromagnetic insulator (AFI), by applying nonequilibrium electronic spin density at one of its surfaces, so that their propagation across AFI deprived of conduction electrons eventually leads to reversal of magnetization of a ferromagnetic metal (FM) attached to the opposite surface of an AFI. However, microscopic (i.e., Hamiltonian-based) understanding of how magnonic and electronic spin currents, both of which can exert torque on localized magnetic moments within FM, are generated and interconverted at multiple junction interfaces is lacking. We employ recently developed time-dependent nonequilibrium Green functions combined with the Landau-Lifshitz-Gilbert equation (TDNEGF+LLG) formalism to evolve conduction electrons quantum mechanically while they interact via self-consistent backaction with localized magnetic moments described classically by atomistic spin dynamics solving a system of LLG equations. Upon injection of square current pulse as the initial condition, TDNEGF+LLG simulations of FM-polarizer/AFI/FM-analyzer junctions show that reversal of localized magnetic moments within a FM analyzer is less efficient, in the sense of requiring larger pulse height and its longer duration, than conventional electron-mediated STT (ESTT) driving magnetization switching in a standard FM-polarizer/normal-metal/FM-analyzer spin valve. Since both electronic, generated by spin pumping from AFI, and magnonic, generated by direct transmission from AFI, spin currents are injected into the FM analyzer, its localized magnetic moments will experience combined MSTT and ESTT. Nevertheless, by artificially turning off ESTT we demonstrate that MSTT plays a dominant role whose understanding, therefore, paves the way for all-magnon-driven magnetization switching devices with no electronic parts.

Temperature plays an important role in spin-torque switching of magnetic tunnel junctions, causing magnetization fluctuations that decrease the switching voltage but also introduce switching errors. Here we present a systematic study of the temperature dependence of the spin-torque-switching probability of state-of-the-art perpendicular-magnetic-tunnel-junction nanopillars (40–60 nm in diameter) from room temperature down to 4 K, sampling up to a million switching events. The junction temperature at the switching voltage—obtained from the thermally assisted spin-torque-switching model—saturates at temperatures below about 75 K, showing that junction heating is significant below this temperature and that spin-torque switching remains highly stochastic down to 4 K. A model of heat flow in a nanopillar junction shows this effect is associated with the reduced thermal conductivity and heat capacity of the metals in the junction.

Many developments in science and engineering depend on tackling complex optimizations on large scales. The challenge motivates an intense search for specific computing hardware that takes advantage of quantum features, nonlinear dynamics, or photonics. A paradigmatic optimization problem is to find low-energy states in classical spin systems with fully random interactions. To date, no alternative computing platform can address such spin-glass problems on a large scale. Here, we propose and realize an optical scalable spin-glass simulator based on spatial light modulation and multiple light scattering. By tailoring optical transmission through a disordered medium, we optically accelerate the computation of the ground state of large spin networks with all-to-all random couplings. Scaling of the operation time with the problem size demonstrates an optical advantage over conventional computing. Our results highlight optical vector-matrix multiplication as a tool for spin-glass problems and provide a general route toward large-scale computing that exploits speed, parallelism, and coherence of light.

In this work, we fabricate a nitride-based photonic crystal (PhC) nanocavity with an embedded active layer for unexplored red regions using simplified selective wet etching of an ${\mathrm{Al}}_{0.82}{\mathrm{In}}_{0.18}\mathrm{N}$ sacrificial layer. Eu,O-codoped $\mathrm{Ga}\mathrm{N}$ ($\mathrm{Ga}\mathrm{N}$:$\mathrm{Eu}$,$\mathrm{O}$) is embedded in L7-type two-dimensional-PhC (2D-PhC) nanocavities with hexagonal holes. Room-temperature photoluminescence (PL) shows $\mathrm{Eu}$ emission coupled to the cavity modes at wavelengths around 620 nm. The quality factor of the fundamental mode in an L7 nanocavity is 5400, which is comparable to those of state-of-the-art 2D-PhC nanocavities with embedded nitride-based active layers for the blue and ultraviolet regions. We show that the Purcell effect due to the small mode volumes of the 2D-PhC nanocavities and enhanced light extraction lead to a 54-fold increase in the integrated PL intensity per unit area with respect to the typical $\mathrm{Ga}\mathrm{N}$:$\mathrm{Eu}$,$\mathrm{O}$ emission.

We propose an approach for wavelength-selective excitation of perpendicular standing spin waves by optical guided modes in a magnetic dielectric film. TM-polarized guided waves with elliptical polarization induce an effective magnetic field due to the inverse transverse magneto-optical Kerr effect (ITMOKE). The ITMOKE is similar to the inverse Faraday effect, except for the induced magnetic field direction that is oriented in the film plane perpendicular to guided-mode propagation. Switching between different guided modes by tuning the wavelength or angle of the laser pulse significantly modifies the spatial distribution of the induced ITMOKE field and, therefore, selectively launches the standing spin-wave modes of different orders. Consequently, one may perform a tunable optical excitation of a certain spin-wave mode via a femtosecond laser pulse of the corresponding wavelength. The proposed approach broadens the spin-wave manipulation capabilities via optical means.

Recently, nonreciprocal charge transport has emerged as an important experimental tool for detecting symmetry breaking in noncentrosymmetric crystals. Despite extensive studies on systems with intrinsic symmetry breaking from crystal structures or interfaces, nonreciprocal transport induced by extrinsic mechanisms, such as the asymmetric design of device geometry, remains largely unexplored. Here, we show that a giant nonreciprocal resistance arises extrinsically from the thermoelectric effect due to nonuniform current heating in mesoscopic devices. Taking $\mathrm{Nb}\mathrm{As}$ nanobelts as an example, we observe giant second-harmonic resistances induced by the Seebeck and Nernst effects, with a nonreciprocal coefficient value up to 5.4 × ${10}^{-6}{\mathrm{cm}}^2/\mathrm{A}$, which is higher than that of most noncentrosymmetric crystals. The symmetry of second-harmonic resistance in magnetic fields can be further controlled by designing the electrode geometry and is decoupled from that of the first-harmonic resistance or the crystal symmetry. We show that such thermoelectric related nonreciprocal resistances also exist in macroscopic samples up to hundreds of microns. Our results not only introduce a simple yet effective approach to probe the thermoelectric effect, but also reveal a previously underestimated mechanism that strongly modifies the second-order transport coefficients.

Slowing down, stopping, and reversing a signal is a core functionality for information processing. Here, we show that this functionality can be realized by tuning the dispersion of a periodic system through a dispersionless, or flat, band. Specifically, we propose a phononic metamaterial based on plate resonators, in which the phonon band dispersion can be modified from an acousticlike to an optical character by modulating a uniform prestress. The switch is enabled by the change in sign of an effective coupling between fundamental modes, which generically leads to a nearly dispersion-free band at the transition point. We demonstrate how adiabatic tuning of the band dispersion can immobilize and reverse the propagation of a sound pulse in simulations of a one-dimensional resonator chain. Our study relies on the basic principles of thin-plate elasticity independently of any specific material, making our results applicable across varied length scales and experimental platforms. More broadly, our approach could be replicated for signal manipulation in photonic metamaterials and electronic heterostructures.

Microwave resonators with a keyhole profile (KHRs) operating in the C band and the X band are designed and studied in numerical simulations and experiments. KHR structures concentrate a microwave magnetic field in a subwavelength volume, while suppressing microwave electric fields. This microwave magnetic field is focused at a finite working distance from KHR metal structures, allowing convenient optical excitation of the sample in both the Faraday geometry and the Voigt geometry. By means of room-temperature optically detected electron spin resonance on $\mathrm{Si}\mathrm{C}$ quantum defects, the conversion factor $B_1{P}_{\mathrm{MW}}^{-1/2}$ for conversion of microwave power into a microwave magnetic field is measured to be approximately $1.0\times {10}^{-3}\mathrm{T}{\mathrm{W}}^{-1/2}$ at a frequency of approximately 7 GHz and a working distance of approximately 0.5 mm from the KHR structure. Numerical simulations match the experimental observations, and an example model code for use with the finite-element-method program elmer is provided. The KHR structures are most promising for fast coherent electron-spin control in solid-state spin qubits, where a large microwave magnetic field needs to be achieved with simultaneous suppression of microwave heating and electric fields, while permitting efficient optical spin initialization and readout.

The fabrication of quantum key distribution (QKD) systems typically involves several parties, thus providing Eve with multiple opportunities to meddle with the devices. As a consequence, conventional hardware and/or software hacking attacks pose natural threats to the security of practical QKD. Fortunately, if the number of corrupted devices is limited, the security can be restored by using redundant apparatuses. Here, we report on the demonstration of a secure QKD setup with optical devices and classical postprocessing units possibly controlled by an eavesdropper. We implement a 1.25 GHz chip-based measurement-device-independent QKD system secure against malicious devices on both the measurement and the users’ sides. The secret key rate reaches 137 bps over a 24 dB channel loss. Our setup, benefiting from a high clock rate, miniaturized transmitters, and a cost-effective structure, provides a promising solution for widespread applications requiring uncompromising communication security.