Ultrathin oxide semiconductors with sub-1-nm thickness are promising building blocks for ultrascaled field-effect transistor (FET) applications due to their resilience against short-channel effects, high air stability, and potential for low-energy device operation. However, the n-type dominance of ultrathin oxide FET has hindered their integration into complementary metal-oxide-semiconductor (CMOS) technology, which requires both n- and p-type devices. Here, we develop an ab initio device-driven computational screening workflow to identify sub-1-nm-thickness oxide semiconductors for sub-5-nm FET applications. We demonstrate that ultrathin ${\mathrm{Ca}\mathrm{O}}_2$, $\mathrm{Ca}\mathrm{O}$, and $\mathrm{Sr}\mathrm{O}$ are compatible with p-type device operations under both high-performance (HP) and low-power (LP) requirements specified by the International Technology Roadmap of Semiconductors (ITRS), thereby expanding the limited family of p-type oxide semiconductors. Notably, $\mathrm{Ca}\mathrm{O}$ and $\mathrm{Sr}\mathrm{O}$ emerge as the first-of-the-kind sub-1-nm-thickness oxide semiconductors capable of simultaneously meeting the HP and LP criteria of the ITRS for both n- and p-type devices. $\mathrm{Ca}\mathrm{O}$ and $\mathrm{Sr}\mathrm{O}$ FETs outperform many existing low-dimensional semiconductors, exhibiting scalability below a 5-nm gate length. Our findings offer a pioneering effort in the ab initio, device-driven screening of sub-1-nm-thickness oxide semiconductors, significantly broadening the material candidate pool for future CMOS technology nodes.

In the noisy intermediate-scale quantum era, quantum devices can only execute shallow-depth circuits to maintain acceptable fidelity. This poses a significant challenge in implementing quantum algorithms that require interactions between nonadjacent qubits, especially on superconducting platforms with limited qubit connectivity. In conventional methods, swap gates are often employed to bridge distant qubits, at the cost of increased circuit depth and reduced overall fidelity. In this paper, we propose a scheme for implementing a controlled-$Z$ gate between next-nearest-neighbor qubits ($N^3\text{−}\mathrm{C}Z$), which enables direct high-fidelity entanglement between nonadjacent qubits without disturbing the intermediate qubit. Implemented on fixed-frequency and fixed-coupler superconducting qubits via simultaneous cross-resonance drives, the $N^3\text{−}\mathrm{C}Z$ gate achieves an average gate fidelity of 99.0% under realistic decoherence conditions, which is further confirmed by quantum process tomography with a fidelity of 98.9%. Moreover, we demonstrate that the $N^3\text{−}\mathrm{C}Z$ gate significantly reduces circuit depth and gate count in key quantum applications and circuit components, including quantum error correction, the quantum fan-out gate, the Toffoli gate, quantum ripple-carry adder, and graph state preparation. These results highlight the potential of the $N^3\text{−}\mathrm{C}Z$ gate as an efficient and hardware-friendly primitive for scalable quantum computation.

Rydberg atoms have emerged as a promising platform for physical implementation of quantum computation. Nonadiabatic holonomic quantum computation (NHQC) provides a powerful route toward high-fidelity and intrinsically robust quantum control. Here we propose a universal framework for robust quantum control based on geometric-optimized NHQC, enabling ultrafast and error-resilient quantum gates on Rydberg atoms. By optimizing geometric phases, we realize gate operations that effectively suppress Rabi-frequency errors while maximizing gate speed, thereby resolving the long-standing trade-off between robustness and evolution time encountered in previous optimized gate schemes. Numerical simulations on a Rydberg-atom platform show that our scheme achieves fidelities exceeding $99.999\mathrm{\%}$ for single-qubit gates and $99.94\mathrm{\%}$ for two-qubit entangling gates, even in the presence of decoherence and Rabi-frequency errors of up to $20\mathrm{\%}$. Therefore, our protocol offers a powerful path toward high-fidelity, error-resistant NHQC on the neutral-atom platform, with broad potential applications in scalable quantum information processing.

Imaging of spatial mode profiles is crucial for understanding the behavior of mechanical resonators. The recent development of phononic circuits has increased the demand for a fast imaging method based on principles of coherent detection. However, it becomes complicated to perform measurements on a large surface area. Here, we present a frequency-detuned collimated-beam interferometry measurement scheme with an in-plane spatial resolution of approximately $6\text{μ}\mathrm{m}$, which can provide information about the phase dynamics of the entire mechanical oscillation cycle on a timescale of a few seconds. We employ a stroboscopic pulse-probing method to resolve high-frequency vibrational motion with a standard CMOS camera. We use this setup to image megahertz frequency resonant mode profiles present in a valley-Hall topological triangular cavity, over an area of more than $20{\mathrm{mm}}^2$. We relate the obtained data to numerical simulations of the topological edge modes to reveal the relation between backscattering and the mode profile distribution. The presented protocol can become a staple for characterizing mesoscopic mechanical resonators.

The integration of photonic components into surface ion traps provides a scalable approach for trapped-ion quantum computing, sensing, and metrology, enabling compact systems with enhanced stability and precision. However, the introduction of optical apertures in the trap electrodes can distort the trapping electric field. This can lead to excess micromotion and ion displacement, which degrade the performance of quantum logic operations and optical clocks. In this work, we systematically investigate the electric field distortion in a surface ion trap with integrated waveguides and grating couplers that require apertures in the surface electrode using finite element method simulations. We analyze methods to reduce these distortions by exploiting symmetries and transparent conductive oxide materials.

A quantum network utilizes quantum entanglement and quantum error correction to effectively transmit quantum information. The development of such networks is a crucial step toward achieving secure and efficient quantum communication. This paper introduces a Bell inequality to verify nonlocality in continuous-variable (CV) multipartite chained entanglement-swapping networks, and proposes a CV-quantum key distribution (QKD) protocol for such networks with Bell-test gating, in which key generation proceeds only when the Bell test is passed. We analyze the achievable key rates under collective and coherent attacks. Numerical simulations show a clear scalability advantage, with the maximum secure distance increasing with the number of nodes. These results support the proposed CV-QKD protocol as a practical route to long-distance secure communication in CV quantum networks.

An emerging device architecture for infrared imaging is the curved focal-plane array, which benefits from several optical advantages over the traditional flat design. However, the curving process introduces additional strain in the active region, which must be taken into account. Type-II superlattices, a promising alternative to traditional bulk materials for use in infrared photodetectors, are candidate materials for use in these devices, but the transport properties of these highly heterogeneous materials are not straightforward and can be affected by different material conditions, such as superlattice (SL) disorder and external strain. We present a comprehensive study of the internal quantum efficiency (QE) calculated for a curved device that incorporates finite-element-analysis (FEA) modeling, nonequilibirium Green’s function (NEGF) calculations, and Gaussian process (GP) regression. FEA is used for predicting the strain configuration throughout the active region induced by the curving procedure of the device. NEGF is used to calculate the vertical hole mobility for a select set of strain configurations, from which the internal quantum efficiency of the device is approximated to predict performance under strained conditions. This data set is then used to train a GP model that maps the QE predictions onto the spatial coordinates of the curved device, based on the strain configuration predicted using FEA. This analysis is performed for ideal and disordered SLs to understand both the fundamental and practical limitations of the performance of these materials in curved devices.

We generalize the van der Pol oscillator model to account for a realistic nonlinearity of the resonant-tunneling-diode (RTD) $I$-$V$ curve. In the case of weak nonlinearity, perturbation theory is applied, and analytical expressions are derived for first-order corrections to the oscillation frequency, quadrature component (phase shift), and higher harmonics. Applicability requirements for perturbation theory are discussed. These requirements are always satisfied at sufficiently high frequencies, but they can fail already at frequencies as low as a few hundred GHz for RTDs with thicker barriers and at slightly above 500 GHz for thin-barrier RTDs, where oscillators transition to a strongly nonlinear regime. Calculation results for the above corrections for several RTD wafers, with typical parameters for sub-THz and THz oscillators, are presented. In particular, our calculations indicate that first-order correction terms play an essential role in the mechanism of variation of the RTD-oscillator frequency with bias. Taking into account the realistic nonlinearity of the RTD $I$-$V$ curve leads to significant quantitative and even qualitative differences in the behavior of RTD oscillators, compared to the conventional van der Pol oscillator model. The presented generalized model lays the groundwork for a more accurate analysis of nonlinear phenomena in RTD oscillators, it can serve as a reference for numerical simulations, it is also essential for qualitative and semiquantitative analysis of RTD oscillators.

We design a superconducting thermoelectric bolometer made of a graphene-insulator-superconductor tunnel junction. Our detector has the advantage of being passive, as it directly transduces input power to a voltage without the need to modulate an external bias. We characterize the device via numerical simulation of the full nonlinear thermal dynamical model of the junction, considering heating of both sides of the junction. While estimating noise contributions, we found expressions due to the temperatures of both sides being different from the bath temperature. Numerical simulations show a noise equivalent power of approximately $4\times {10}^{-17}\mathrm{W}/\sqrt{\mathrm{Hz}}$ for an input power of approximately ${10}^{-16}\mathrm{W}$, a response time of approximately $200\mathrm{ns}$, and an integration time to obtain a signal-to-noise ratio of 1 of approximately $100\text{μ}\mathrm{s}$ for an input power of approximately ${10}^{-13}\mathrm{W}$. Therefore, the device shows promise for large-array cosmological experiment applications, also considering its advantages for fabrication and heat budget.

Spin waves are attractive information carriers, owing to their gigahertz-to-terahertz frequencies, nanometric wavelengths, and negligible Joule heating. However, efficiently and locally exciting short-wavelength high-frequency propagating spin waves and exploiting nonlinear effects remain challenging. We propose a hybrid ferromagnetic structure consisting of an in-plane-magnetized nanosized area (a magnonic nanocavity) that is exchange-coupled to an out-of-plane-magnetized film or stripe. Micromagnetic simulations show that a spatially uniform out-of-plane microwave magnetic field excites only the fundamental mode of the nanocavity. Its second harmonic is then coherently and efficiently launched into the extended part of the ferromagnet, yielding propagating spin waves. This process can be achieved with stripe or extended film geometries, which excite plane waves or radial spin waves, respectively. Given the simple fabrication process of degrading the anisotropy of a ferromagnetic layer with perpendicular magnetic anisotropy, the spin-wave wave front can be shaped extensively by adjusting the nanocavity geometry. Conversion efficiency can be enhanced when the frequency of the second harmonic matches a higher-order standing spin-wave frequency of the nanocavity. Furthermore, the emission frequency is tunable via the bias magnetic field or the width of the nanocavity. These findings suggest a compact route toward on-chip, short-wavelength, high-frequency nonlinear spin-wave sources for artificial neural networks.

Weak measurement (WM) offers the advantage of amplifying small signals at the cost of postselecting a small portion of the probes. This so-called weak-value amplification effect makes it compare favorably with conventional techniques (without postselection) to overcome various technical noises. However, certain types of technical noise, such as jitter and pixelation, present insurmountable limitations for both WM and conventional techniques. In this work, we propose an advanced variant of WM that incorporates time-momentum correlation (TMC) into biased weak measurement (BWM). By employing the Fisher information metric, we theoretically show that TMC-BWM can overcome jitter and pixelation, and meanwhile extract significantly higher Fisher information. This dual advantage was experimentally validated in a magnetic-sensing application when applying severe jitter and pixelation, and it remains robust under natural conditions, achieving a 24.8-dB improvement in precision over the standard WM scheme. Moreover, merely classical resources are required to achieve this dual metrological advantage.

Inkjet printing is a highly reproducible and reliable droplet deposition technique. However, its stability can be compromised by the stochastic entrainment of an air bubble inside the ink channel, causing acute nozzle failure. Prior studies have linked bubble entrainment to the trapping of dirt particles, which are typically denser than the ink, inside the pulsating toroidal vortex formed above the jetting nozzle. While this seemingly counterintuitive trapping has been numerically studied in idealized unbound vortices, its behavior in realistic flows remains mostly unexplored. Here, we investigate particle trapping within a piezoacoustic inkjet channel by using two-phase flow simulations and by modeling particle translation using the Maxey-Riley equation. We compare two nozzle geometries, i.e., a straight nozzle and one tapered at ${10}^{\circ }$, and find that introducing this small taper significantly alters the oscillatory flow near the nozzle. For both nozzle types, particles in the relevant size range (4–8 $\text{μ}\mathrm{m}$) and particle-to-fluid density ratios (0.5–3) exhibit consistent trends: particles heavier than the fluid follow centripetal trajectories, spiraling inward within the vortex ring, while lighter particles follow centrifugal paths. Particles denser than the fluid can become trapped when the particles can no longer follow the high-frequency flow oscillations thereby limiting their kinetic energy, allowing the strong centripetal force from the pressure gradient in the vortex ring to pull them inward. The particle-trapping rate increases with both particle size and density ratio, and is similar for straight and tapered nozzles. However, in tapered nozzles, the vortex ring is smaller, resulting in fewer particles interacting with it, thereby reducing the number of particles trapped, and potentially mitigating dirt-induced bubble entrainment.

Droplet microfluidics combined with optical detection has emerged as a transformative avenue for high-throughput single-cell assays. However, these platforms often suffer from limited sensitivity and signal heterogeneity due to intrinsic optical and geometric constraints. We investigate how key operating parameters influence the performance of a droplet-based optomicrofluidic system. Our experiments probe optical interactions between guided light and aqueous droplets encapsulating fluorescent particles flowing in an oil medium. Geometric optics simulations model light-droplet interaction, while florescence simulations quantify signal variation due to particle size and position. Experimentally, we observe two refracted optical signals: a droplet-refracted signal that scales with droplet diameter, and a particle-refracted signal arising from light interaction with encapsulated particles. Both experiments and simulations reveal that the particle-refracted signal is prominent when the particle-to-droplet size ratio $D_{\mathrm{p}}^{\ast }$ is between 0.23 and 0.33, enabling label-free detection. Experiments also show that particles located near the droplet center ($r_{\mathrm{p}}^{\ast }<0.4$) exhibit a reduced angular dependence, producing more uniform fluorescence signals. Simulations indicate that the fluorescence intensity increases with $D_{\mathrm{p}}^{\ast }$, with a strong rise from 0.33 to 0.5 and a more gradual increase up to 0.66. Further, simulations show that reducing the thickness of the oil layer consistently increases fluorescence by minimizing optical losses at the droplet/channel interface. Our results demonstrate that controlling $D_{\mathrm{p}}^{\ast }$, particle position, and oil-layer thickness significantly increases fluorescence intensity and uniformity. These findings establish a quantitative and experimentally validated framework for optimizing droplet-based fluorescence detection, with potential applications in microflow cytometry and single-cell assays.

Elongate animals and robots use undulatory body waves to locomote through diverse environments. Geometric mechanics provides a framework to model and optimize such systems in highly damped environments, connecting a prescribed shape change pattern (gait) with locomotion displacement. However, the practical applicability of controlling compliant physical robots remains to be demonstrated. In this work, we develop a framework based on geometric mechanics to predict locomotor performance and search for optimal swimming strategies of compliant swimmers. We introduce a compliant extension of Purcell’s three-link swimmer by incorporating series-connected springs at the joints. Body dynamics are derived with the use of resistive force theory. Geometric mechanics is incorporated into movement prediction and into an optimization framework that identifies strategies for controlling compliant swimmers to achieve maximal displacement. We validate our framework on a physical cable-driven, three-link limbless robot and demonstrate accurate prediction and optimization of locomotor performance under varied programmed, state-dependent compliance in a granular medium. Our results establish a systematic, physics-based approach for modeling and controlling compliant swimming locomotion, highlighting compliance as a design feature that can be exploited for robust movement in both homogeneous and heterogeneous environments.

Guiding spin wave (SW) signals around turns in integrated magnonic circuits remains a challenge. Here, we calculated efficient SW transmission through Z-shaped turns of 120° using low-loss magnonic crystal (MC) waveguides comprising yttrium iron garnet (YIG) and a $\mathrm{Cu}$ hole array. The MCs were optimized using a finite integration technique, showing a complete magnonic band gap with a width of 15.1 MHz at a center frequency of 1.811 GHz. The MC waveguide showed 5.7 × ${10}^3$ times stronger SW propagation than ridge-type waveguides by avoiding SW depression caused by inhomogeneous internal magnetic field distributions in the YIG film. The effect of the bending radius on the SW propagation was evaluated through simulations. The proposed MC waveguide plays a vital role in SW waveguide integration by maintaining homogeneous magnetic field distributions throughout the unprocessed YIG film.