In dark-matter searches using axion haloscopes, the search sensitivity depends on the quality factors ($Q_0$) of radio-frequency cavities immersed in multitesla magnetic fields. Increasing $Q_0$ would increase the scan rate through the parameter space of interest. Researchers developing superconducting radio-frequency cavities for particle accelerators have developed methods for obtaining extremely high $Q_0$ of approximately ${10}^{11}$ in microteslascale magnetic fields. In this paper, we describe efforts to develop high-$Q$ cavities made from ${\mathrm{Nb}}_3\mathrm{Sn}$ films using a technique developed for particle-accelerator cavities. Geometry optimization for this application is explored, and two cavities are tested: an existing particle-accelerator-style cavity and a geometry developed and fabricated for use in high fields. A quality factor of $(5.3\pm 0.3)\times {10}^5$ is obtained at 3.9 GHz and 6 T at 4.2 K.

Accelerometers have widespread applications and are an essential component in many areas, such as automotive, consumer electronics, and industrial applications. Most commercial accelerometers are based on a microelectromechanical system (MEMS) that is limited in downscaling and power consumption. Spintronics-based accelerometers are proposed as alternatives; however, current proposals suffer from design limitations that result in reliability issues and high cost. Here, we propose spintronic accelerometers with magnetic tunnel junctions (MTJs) as building blocks, which map accelerations into a measurable voltage across the MTJ terminals. The device exploits elastic and dipolar coupling as a sensing mechanism and the spintronic diode effect for the direct readout of acceleration. The proposed technology represents a potentially competitive and scalable solution to current capacitive MEMS-based approaches that could lead to a step forward in many of the commercial applications.

Channel materials with symmetrical performances for n- and p-type transistors and shrinking transistors to the ultrascale limit are essential for CMOS integrated circuits (ICs) in the coming post-$\mathrm{Si}$ era. Monolayer (ML) boron pnictides (i.e., $\mathrm{BP}$ and $\mathrm{B}\mathrm{As}$) possess both high electron and hole mobilities and flat atomic thick configurations, which are beneficial for symmetrical performance and short natural lengths, respectively. Herein, we provide a theoretical study on the device performances of sub-5-nm ML boron pnictide MOSFETs using the ab initio quantum transport method. Symmetrical n- and p-type performances are achieved for the ML boron pnictide MOSFETs. The optimal n- and p-type ML $\mathrm{BP}$ and $\mathrm{B}\mathrm{As}$ MOSFETs can reach the International Roadmap for Devices and Systems goals for the 2028 horizon for high-performance devices at gate lengths ($L_{\mathrm{g}}$) of 3 and 5 nm, respectively. In particular, the optimal n-type (p-type) ML $\mathrm{BP}$ MOSFETs possess superhigh on-state currents ($I_{\mathrm{ON}}$) of 2974 (2937) µA/µm at $L_{\mathrm{g}}$= 5 nm, exceeding most reported ML MOSFETs. Our study suggests that ML boron pnictides are prospective channel materials in the post-$\mathrm{Si}$ era for CMOS ICs.

The stability of lithium-ion batteries is of paramount importance for their commercialization. However, strategies for improving electrode stability are still quite unsatisfactory due to the unclear mechanism of diffusion-induced stress and especially the regulation methods based on it. Herein, based on a columnar lithium-ion diffusion electrode model, a double high-elastic-modulus modification (DHEMM) method is proposed to inhibit deformation and relieve the generated stress during cycling. In this light, ${\mathrm{Ti}\mathrm{O}}_2/{\mathrm{V}}_2{\mathrm{O}}_5/$polypyrrole (PPy) nanofibers are accordingly synthesized with a significantly enhanced rate capacity (198.2 mAh ${\mathrm{g}}^{-1}$ at 1600 mA ${\mathrm{g}}^{-1}$) and electrochemical stability (91.9% capacity retention for 100 cycles at 100 mA ${\mathrm{g}}^{-1}$), offering an alternative way to fabricate stable lithium-ion batteries.

Imaging systems measuring intensity in the far field succumb to Rayleigh’s curse, a resolution limitation dictated by the finite aperture of the optical system. Many proof-of-principle and some two-dimensional imaging experiments have shown that, by using spatial mode demultiplexing (SPADE), the field information collected is maximal, and, thus, the resolution increases beyond the Rayleigh criterion. Hitherto, the SPADE approaches are based on resolving the lateral splitting of a Gaussian wave function. Here, we consider the case in which the light field originates from a biphoton source, i.e., spontaneous parametric down-conversion, and a horizontal separation is introduced in one of the two photons. We show that a separation induced in the signal photon arm can be superresolved using coincidence measurements after projecting both photons on Hermite-Gauss modes. Remarkably, the Fisher information associated with the measurement is enhanced compared to the ordinary SPADE techniques by $\sqrt{K}$, where $K$ is the Schmidt number of the two-photon state that quantifies the amount of spatial entanglement between the two photons.

Topological edge states in electromagnetic systems feature fascinating fundamental properties and unveil future applications based on disorder robustness and tailored localization. Despite active efforts in implementing topologically protected waveguides in two-dimensional photonic systems, applications of one-dimensional topological systems remain almost uncharted. In this Paper, we demonstrate that topological edge modes can be implemented in metamaterial-inspired volumetric resonators for clinical magnetic resonance imaging (MRI) by dimerizing a metasolenoid composed of coupled split-ring resonators to implement a one-dimensional Su-Schrieffer-Heeger model. Performing numerical simulations and experiments with a $1.5$ T MRI scanner, we study the associated resonance spectra of metasolenoids, their bulk and topological edge mode profiles, and signal-to-noise ratio curves. Finally, we consider the potential applications based on increased magnetic field localization at the topological edge mode compared with conventional surface coils based on single split-ring resonators and bulk modes of metasolenoids.

In addition to spin and valley degrees of freedom, a bilayer of transition-metal dichalcogenides (TMDs) exhibits a further degree of freedom, the layer pseudospin, which is associated with the interlayer dynamics. Here, we study, over a wide range of energies, the conditions for the generation and control of the perfect-spin-, valley-, and layer-polarized transport in a nonmagnetic/ferromagnetic/nonmagnetic junction fabricated in AB-stacked bilayer TMDs. We find that, via breaking the inversion and time-reversal symmetries through application of external electric and exchange fields, layer-, perfect-spin-, and valley-polarized transport can be achieved and controlled electrically and magnetically. Analyzing effects related to the band structure and the local density of states, the predictions are rationalized, and in particular we expose the role of tuning the band gap and adjusting the charge localization in one specific layer. Within an appropriate parameter regime, an energy interval with contributions from both layers is identified, leading to enhancement of the transmission and conductance. Our results can be useful for pseudospintronic applications in bilayer TMD-based devices.

Pump-induced magnon modes (PIMs) are recently discovered elementary excitations in ferrimagnets that offer significant tunability to spin dynamics. Here, we investigate the coupling between a PIM and cavity magnon-polaritons (CMPs) by driving a cavity magnonic system away from equilibrium with a microwave pump. In our experiment, the Walker mode simultaneously couples with the PIM and cavity photons and thus combines two strongly coherent coupling processes in a single cavity structure. Such a PIM-CMP hybridization system acquires complementary properties from both the PIM and CMPs, allowing it to be freely manipulated by the magnetic field, the pump power, and the pump frequency. These coherent manipulations exhibit unique behaviors beyond the intrinsic properties limited by the material nature and electromagnetic boundary conditions, thereby creating opportunities for extending the control of hybrid devices.

Entanglement plays a crucial role in quantum physics and is the key resource in quantum information processing. However, entanglement detection and quantification are believed to be hard due to the operational impracticality of existing methods. This work proposes three near-term efficient algorithms that exploit the hybrid quantum-classical technique to address this difficulty. The first algorithm finds the Schmidt decomposition—a powerful tool to analyze the properties and structure of entanglement—for bipartite pure states. While the logarithm negativity can be calculated from the Schmidt decomposition, we propose the second algorithm to estimate the logarithm negativity for bipartite pure states, where the width of the parameterized quantum circuits is further reduced. Finally, we generalize our framework for mixed states, leading to our third algorithm that detects entanglement on specific families of states, and determines distillability in general. All three algorithms share a similar framework where the optimizations are accomplished by maximizing a cost function utilizing local parameterized quantum circuits, with better hardware efficiency and practicality compared to existing methods. The experimental implementation on Quantum Leaf using the Institute of Physics, Chinese Academy of Sciences superconducting quantum processor exhibits the validity and practicality of our methods for analyzing and quantifying entanglement on near-term quantum devices.

Superconducting quantum processors comprising flux-tunable data and coupler qubits are a promising platform for quantum computation. However, magnetic flux crosstalk between the flux-control lines and the constituent qubits impedes precision control of qubit frequencies, presenting a challenge to scaling this platform. In order to implement high-fidelity digital and analog quantum operations, one must characterize the flux crosstalk and compensate for it. In this work, we introduce a learning-based calibration protocol and demonstrate its experimental performance by calibrating an array of 16 flux-tunable transmon qubits. To demonstrate the extensibility of our protocol, we simulate the crosstalk matrix learning procedure for larger arrays of transmon qubits. We observe an empirically linear scaling in calibration time with system size while maintaining a median qubit frequency error below 300 kHz.

Neurons in the brain show nonlinear oscillatorlike behaviors, inspiring the development of neuromorphic computing with spin-torque oscillators for their low power consumption and high integration density. The time-multiplexing technique enables utilizing only one device to achieve neuromorphic computing, further reducing power consumption and simplifying device fabrication. However, optimizing such systems remains a challenge and needs further development. A controversial hypothesis claims that dynamic systems possess the optimal computational capacity to address the information at the dynamical phase transition. Here, we apply this hypothesis to improve a reservoir computing system based on an alternating input-driven spin-torque oscillator. The input-driven property of reservoir computing allows us to exploit the dynamics of a spin-torque oscillator by manipulating the input stream. By tuning the ac amplitude in inputs, the system can exhibit diversified dynamic regimes indicated by the largest Lyapunov exponent and echo-state property spectra. Our findings demonstrate that the proper configuration of ac inputs for reservoir computing based on a single spin-torque oscillator can adjust its information-processing capacity profile and enhance its computational performance for specific tasks.

Rydberg-atom-based sensors are a type of radio-frequency sensor that is inherently quantum mechanical. Several configurations of the sensor use a local oscillator to determine the properties of the target radio-frequency field. We explain how the physics of Rydberg-atom-based sensors in two or more radio-frequency fields can be precisely described by a multiply dressed Jaynes-Cummings model. Studying Rydberg-atom-based sensors in two or more near-resonant radio-frequency fields is important for understanding how interfering signals as well as the local oscillator can affect measurements. Studies, so far, focus on a simplified approximation for the local oscillator-target field interaction that uses an analogy to radio-frequency heterodyning. The atom acts as a medium for exchanging electromagnetic field excitations of the field modes whose spectrum is a ladder. The Jaynes-Cummings states and their avoided crossings can be used to determine the properties of the radio-frequency fields. Radio-frequency field sensitivity enhancement for nonresonant radio frequencies is achieved and self-calibrated measurements are recovered under specific conditions described by the theory.

Droplet-based microfluidic has emerged as a versatile tool for widespread applications, such as biochemical analysis and synthesis, for which the generation and manipulation of the microdroplets are fundamental. Acoustic based droplet control has shown advantages of good biocompatibility and widescale tunability. Here, we demonstrate an acoustic controlled nozzle that is integrated with both generation and directed dispensing of microdroplets. The system can generate monodisperse microdroplets with tunable sizes (50–641 µm) at a highest throughput of 2000 droplets per second. Besides, by tuning the acoustic frequency, the droplets can be steered to different directions after their formation, realizing on-demand dispensing of the microdroplets. The controlled microdroplet generation and dispensing are both attributed to the acoustic streaming effect induced by the nozzle vibration. Two basic mechanisms for the droplet control were studied: (1) the correlation between the droplet size and the acoustic actuation time, (2) the dependence of the droplet dispensing direction on the acoustic frequency. This work paves the way towards programmable control over acoustic generation and dispensing of microdroplets, which has great potential in the applications of bio-chemical analysis and synthesis.

Single-cell phenotyping based on biophysical properties is a promising tool to distinguish cell types and their response to a given condition, and charting such properties also enables optimization of cell separations. Isoacoustic focusing, where cells migrate to their points of zero acoustic contrast in an acoustic impedance gradient, added the effective acoustic impedance of cells to the directory of biophysical properties that can be utilized to categorize or separate cells. This study investigates isoacoustic focusing in a stop-flow regime and shows how cells migrate towards their isoacoustic point. We introduce a numerical model that we use to estimate the acoustic energy density in acoustic impedance gradient media by tracking particles of known properties, and we investigate the effect of acoustic streaming. From the measured trajectories of cells combined with fluorescence intensity images of the slowly diffusing gradient, we read out the effective acoustic impedance of neutrophils and K562 cancer cells. Finally, we propose suitable acoustic impedance gradients that lead to a high degree separation of neutrophils and K562 cells in a continuous-flow configuration.