${\mathrm{Hf}\mathrm{O}}_2$-based ferroelectrics ($\mathrm{FE}\text{−}{\mathrm{Hf}\mathrm{O}}_2$) have triggered extensive research interest because they are promising materials for beyond-Moore electronic device applications. However, the origin of ferroelectricity in ${\mathrm{Hf}\mathrm{O}}_2$-based ferroelectrics remains elusive. Here, we demonstrate that the ordered oxygen vacancies (${\mathrm{V}}_{\mathrm{O}}$) in $\mathrm{FE}$-${\mathrm{Hf}\mathrm{O}}_2$ thin films contribute to ferroelectricity through the formation of a stable-polar phase. In $\mathrm{FE}$-${\mathrm{Hf}\mathrm{O}}_2$ thin films, oxygen vacancy (${\mathrm{V}}_{\mathrm{O}}$) defects induce local electric dipoles and the ordered ${\mathrm{V}}_{\mathrm{O}}$ distribution results in the stable-polar phases. Using first-principles calculations, a thermodynamically stable-polar phase $M_1$ with the spontaneous polarization of 27 µC/${\mathrm{cm}}^2$ is predicted in monocliniclike ${\mathrm{Hf}}_4{\mathrm{Zr}}_4{\mathrm{O}}_{15}$ structures. Moreover, the predicted $M_1$ structures are directly visualized in ${\mathrm{Hf}}_{0.5}{\mathrm{Zr}}_{0.5}{\mathrm{O}}_{2-\delta }$ (HZO) ferroelectric thin films using spherical aberration (Cs)-corrected scanning transmission electron microscopy. The proposed mechanism for ${\mathrm{V}}_{\mathrm{O}}$-induced order-disorder ferroelectricity in $\mathrm{FE}$-${\mathrm{Hf}\mathrm{O}}_2$ opens a new pathway to explore the underlying physics of the ferroelectric characteristics in $\mathrm{FE}$-${\mathrm{Hf}\mathrm{O}}_2$.

Efficient optical quantum memories are a milestone required for several quantum technologies, including repeater-based quantum key distribution and on-demand multiphoton generation. We present an efficiency optimization of an optical electromagnetically induced transparency (EIT) memory experiment in a warm cesium vapor using a genetic algorithm and analyze the resulting wave forms. The control pulse is represented either as a Gaussian or free-form pulse and the results from the optimization are compared. We see an improvement factor of 3(7)% when using optimized free-form pulses. By limiting the allowed pulse energy in a solution, we show an energy-based optimization giving a 30% reduction in energy, with minimal efficiency loss.

Parametric converters are parametric amplifiers that mix two spatially separate nondegenerate modes and are commonly used for amplifying and squeezing microwave signals in quantum computing and sensing. In Josephson parametric converters, the strong localized nonlinearity of the Josephson junction limits the amplification and squeezing, as well as the dynamic range, in current devices. In contrast, a weak distributed nonlinearity can provide higher gain and dynamic range, when implemented as a kinetic inductance (KI) nanowire of a dirty superconductor, and has additional benefits such as resilience to magnetic field, higher-temperature operation, and simplified fabrication. Here, we propose, demonstrate, and analyze the performance of a KI parametric converter that relies on the weak distributed nonlinearity of a Nb-Ti-N KI nanowire. The device utilizes three-wave mixing induced by a dc current bias. We demonstrate its operation as a nondegenerate parametric amplifier with high phase-sensitive gain, reaching two-mode amplification and deamplification of approximately 30 dB for two resonances separated by 0.8 GHz, in excellent agreement with our theory of the device. We observe a dynamic range of $-108$ dBm at 30 dB gain. Our device can significantly broaden applications of quantum-limited signal processing devices including phase-preserving amplification and two-mode squeezing.

Pancreatic ductal adenocarcinoma is a devastating disease with very low survival rates 5 years after diagnosis. The main reason for this dismal prognosis is the thick stroma which both protects tumor cells from drug penetration and supports tumor development. Ultrasound inertial cavitation is a promising treatment with potential for stromal disruption, enhancing tumor cells’ sensitivity to chemical agents and biomodulators. Our goal was to develop a dedicated microelastography setup allowing us to measure the elasticity of in vitro tumor models called spheroids. In a second step, the impact of cavitation treatment on their mechanical properties was assessed. A transcranial magnetic stimulation clinical device was used to induce shear waves in the spheroids containing magnetic nanoparticles. Using an inverted optical microscope, particle imaging velocimetry, and noise correlation algorithms, the shear wave velocity, indicative of the medium’s elasticity, could be measured. Shear waves generated by the magnetic pulse inside the spheroids were detected and their velocity was measured using noise correlation elastography. This allowed the estimation of the spheroids’ elasticity. Cavitation treatment softened them significantly, and the impact of the exposure conditions and the spheroids’ composition have been studied. In the future, such a method could be used to monitor cavitation treatments. In addition, since it is now well established that mechanical constraints and elasticity play an important role in tumor growth, it is of great interest to measure the elasticity of tumor models to better understand the mechanisms of tumor growth.

Extremely large acoustic impedance mismatching generates a natural acoustic barrier at the air-water interface, resulting in significantly impeding bidirectional acoustic wave propagation across the heterogeneous interface. Here, an air-water metasurface with dual coupling resonators is proposed to enhance the acoustic transmission at the air-water interface, which facilitates the implementation of wireless harvesting for acoustic energy across the heterogeneous interface. A theoretical model is established and derived to obtain the analytical expressions between acoustic energy transmission and microstructural geometric parameters. The theoretical analysis reveals that the highly efficient energy transmission mechanism depends on the impedance coupling effect of the resonant cavities for nonresonance modes. The enhanced bidirectional acoustic energy transmission at the air-water interface is investigated and verified numerically and experimentally, and the maximum enhancement of energy transmission is measured to be approximately 19 dB at the peak frequency. Finally, wireless acoustic energy harvesting across the air-water interface is implemented experimentally by integrating the designed metasurface with a contact-separation-mode triboelectric nanogenerator, and the captured energy from the waves effectively operates six LED lamps. The proposed “bottom-up” design methodology of air-water wave energy harvesting based on an acoustic-metasurface-embedded system opens promising routes for underwater wireless energy-supplying platforms and medical ultrasound therapy.

Field emission (FE), the process of emitting electrons from the surface of a metal under large perpendicular electric fields, has a long history and plays a crucial role in numerous applications ranging from electron microscopes to detectors. A key determining factor for FE is the work function of the material. Graphene is semimetallic and has a work function that can be tuned by the position of the Fermi level, lending it a distinct advantage in FE applications. However, the exceptional thinness of graphene means its properties are highly dependent on the environment and the substrate that it is supported on. The impact of environmental factors, particularly the atomic-scale roughness of the substrate to which graphene typically conforms, on FE has not been explored. Here, we demonstrate that atomic-scale roughness dictates FE currents by controlling the local slope of the graphene sheet relative to the electric field. Our study combines measurements of FE current from graphene supported over trenches and supported on silicon nitride substrates, while our calculations capture the full electronic structure from first principles and model the adhesion of graphene to a rough substrate via van der Waals forces. Our results show that the FE current scales with the average slope of the substrate’s surface, which, in turn, depends on the ratio of roughness and correlation length of the atomic-scale roughness. This novel relationship explains our observation that FE currents are larger from supported graphene samples compared with those suspended over micron-scale trenches. Our work impacts future applications of graphene in FE by allowing researchers to maximize the FE current through surface engineering.

Zero-mode waveguide (ZMW) nanowells confine light efficiently down to the nanometer scale and overcome the diffraction limit of single-molecule fluorescence analysis. However, the sticking of fluorescent molecules on ZMW surface can substantially hinder the interpretation of experiments. A regular quantitative method for the description of the fluorescence of molecules randomly moving in a ZMW with a functionalized surface is proposed. The autocorrelation functions of the single-molecule fluorescence fluctuations in a closed ZMW with different properties of its bottom and walls are found. It is shown that in the ZMW, where the diffusion coefficient at the bottom and/or walls is significantly smaller than the diffusion coefficient in the main volume, mode decoupling arises. A significant increase in the fluorescence correlation time appears, and quantitative estimates of this increase are found. The obtained results pave the way for the quantitative analysis of the properties of a ZMW with functionalized surfaces and expand the use of the ZMW to single-molecule fluorescence applications.

Understanding the high-frequency transport characteristics of magnetic tunnel junctions (MTJs) is crucial for the development of fast-operating spintronics memories and radio frequency devices. Here, we present the study of a frequency-dependent capacitive current effect in $\mathrm{Co}\mathrm{Fe}\mathrm{B}/\mathrm{Mg}\mathrm{O}$-based MTJs and its influence on magnetization dynamics using a time-resolved magneto-optical Kerr effect technique. In our device, operating at gigahertz frequencies, we find a large displacement current of the order of mA, which does not break the tunnel barrier of the MTJ. Importantly, this current generates an Oersted field and spin-orbit torque, inducing magnetization dynamics. Our discovery holds promise for building robust MTJ devices operating under high current conditions, also highlighting the significance of capacitive impedance in high-frequency magnetotransport techniques.

Spatial gaps between sub-beams in high-peak-power lasers with tiled-aperture-based coherent beam combining (TACBC) give rise to relatively strong sidelobes and impair the power in bucket (PIB) at far field. To address the aforementioned issue, spatial chirp is employed in this paper to fill the gaps and further enhance PIB. With two sub-beams, both simulations and experiments indicate that spatial chirp can boost PIB by 1.8 times at a gap-beam width ratio of 0.2. The same enhancement is observed in simulations even when four sub-beams are considered. To put it briefly, the spatial-chirp-assisted TACBC approach holds the potential in boosting focal intensity during constructing tens to hundreds of petawatt (PW) lasers.

Large-area carbon-nanotube (CNT) cathodes made from yarns, films, or fibers have long been promising as next-generation electron sources for high-power rf and microwave-vacuum-electronic devices. However, experimental evidence has highlighted that spatial incoherence of the electron beam produced by such cathodes impeded the progress toward high brightness CNT electron sources and their practical applications. Indeed, typically large-area CNT fibers, films, or textiles emit stochastically across their physical surface at large emission angles and with large transverse spread, meaning large emittance and hence low brightness. In this work, using high-resolution field-emission microscopy, we demonstrate that conventional electroplating of hair-thick CNT fibers followed by a femtosecond laser cutting, producing an emitter surface, solves the described incoherent emission issues extremely well. Strikingly, it was observed that the entire (within the error margin) cathode surface of a radius of approximately $75\text{μ}\text{m}$ emitted uniformly (with no hot spots) in the direction of the applied electric field. The normalized cathode emittance, i.e., on the fiber surface, was estimated as 26-$\text{nm}\text{rad}$ with brightness of $>{10}^{16}\text{A}/{\text{m}}^2{\text{rad}}^2$ (or $>{10}^7\mathrm{A}{\mathrm{m}}^{-2}{\mathrm{sr}}^{-1}{\mathrm{V}}^{-1}$) estimated for pulsed-mode operation.

Current-biased Josephson junctions can act as detectors of electromagnetic radiation. At optimal conditions, their sensitivity is limited by fluctuations causing stochastic switching from the superconducting to the resistive state. This work provides a quantitative description of a stochastic switching current detector, based on an underdamped Josephson junction. It is shown that activation of a Josephson plasma resonance can greatly enhance the detector responsivity in proportion to the quality factor of the junction. The ways of tuning the detector for achieving optimal operation are discussed. For realistic parameters of $\mathrm{Nb}$/${\mathrm{Al}\mathrm{O}}_x$/$\mathrm{Nb}$ tunnel junctions, the sensitivity and noise-equivalent power (NEP) can reach values of $S\simeq 5\times {10}^{12}$ (V/W) and $\mathrm{NEP}\simeq 2\times {10}^{-23}$ (${\mathrm{WHz}}^{-1/2}$), respectively. These outstanding characteristics facilitate both bolometric and single-photon detection in microwave and terahertz ranges.

Acousto-optics consists of launching acoustic waves in a medium (usually a crystal) in order to modulate its refractive index and create a tunable optical grating. In this article, we present the theoretical basis of an alternative scheme to generate acousto-optics in a gas, where the acoustic waves are initiated by the localized absorption (and thus gas heating) of spatially modulated UV light, as was demonstrated by Michine and Yoneda [Commun. Phys. 3, 24 (2020)]. We identify the chemical reactions initiated by the absorption of UV light via the photodissociation of ozone molecules present in the gas, and calculate the resulting temperature increase in the gas as a function of space and time. Solving the Euler fluid equations shows that the modulated, isochoric heating initiates a mixed acoustic-entropy wave in the gas, whose high-amplitude density (and thus refractive index) modulation can be used to manipulate a high-power laser. We calculate that diffraction efficiencies near 100% can be obtained using only a few millimeters of gas containing a few percent ozone fraction at room temperature, with UV fluences of less than 100 ${\mathrm{mJ}/\mathrm{cm}}^2$—consistent with the experimental measurements. Our analysis suggests possible ways to optimize the diffraction efficiency by changing the buffer gas composition. Gases have optics damage thresholds 2–3 orders of magnitude beyond those of solids; these optical elements should therefore be able to manipulate kilojoule-class lasers.

High-precision remote clock synchronization is crucial for many classical and quantum network applications. Evaluating options for space-Earth links, we find that traditional solutions may not produce the desired synchronization for low Earth orbits and unnecessarily complicate quantum networking architectures. Demonstrating an alternative, we use commercial off-the-shelf quantum photon sources and detection equipment to synchronize two remote clocks across our free-space testbed utilizing a method called two-way quantum time transfer (QTT). We reach picosecond-scale timing precision under very lossy and noisy channel conditions representative of daytime space-Earth links and software-emulated satellite motion. This work demonstrates how QTT is potentially relevant for daytime space-Earth quantum networking and/or providing high-precision timing in GPS-denied environments.

We demonstrate qubit-state measurements assisted by a supervised convolutional neural network (CNN) in a neutral-atom quantum processor. We present two CNN architectures for analyzing neutral-atom qubit readout data: a compact five-layer single-qubit CNN architecture and a six-layer multiqubit CNN architecture. We benchmark both architectures against a conventional Gaussian-threshold analysis method. In a sparse array (9-$\text{μ}\mathrm{m}$ atom separation) which experiences negligible crosstalk, we have observed up to 32% and 56% error reduction for the multiqubit and single-qubit architectures, respectively, as compared to the benchmark. In a tightly spaced array (5-$\text{μ}\mathrm{m}$ atom separation), which suffers from readout crosstalk, we have observed up to 43% and 32% error reduction in the multiqubit and single-qubit CNN architectures, respectively, as compared to the benchmark. By examining the correlation between the predicted states of neighboring qubits, we have found that the multiqubit CNN architecture reduces the crosstalk correlation by up to 78.5%. This work demonstrates a proof of concept for a CNN network to be implemented as a real-time readout-processing method on a neutral-atom quantum computer, enabling faster readout time and improved fidelity.

Solving optimization problems using variational algorithms stands out as a crucial application for noisy intermediate-scale devices. Instead of constructing gate-based quantum computers, our focus centers on designing variational quantum algorithms within the analog paradigm. This involves optimizing parameters that directly control pulses, driving quantum states toward target states without the necessity to compile a quantum circuit. In this work, we introduce pulse-based variational quantum optimization (PBVQO) as a hardware-level framework. We illustrate the framework by optimizing external fluxes on superconducting quantum interference devices, effectively driving the wave function of this specific quantum architecture to the ground state of an encoded problem Hamiltonian. Given that the performance of variational algorithms relies heavily on appropriate initial parameters, we introduce a global optimizer as a metalearning technique to tackle a simple problem. The synergy between PBVQO and metalearning provides an advantage over conventional gate-based variational algorithms.