Atom spin sensors occupy a prominent position in the landscape of quantum technology, as they can combine precise measurements with appealing miniature packages that are crucial for many applications. In this work, we report on the design and realization of miniature silicon-wafer cells, with a double-chamber configuration and integrated heaters. The cells are tested by our systematically studying the dependence of the spin dynamics on the main pump parameters, temperature, and bias magnetic field. The results are benchmarked against centimeter-sized paraffin-coated cells, which allows optimization of the operating conditions of a radio frequency–driven atomic magnetometer. In particular, we observe that, when indirect optical pumping is performed on the two cells, an analogous line-narrowing mechanism appears in otherwise-very-different cell conditions. Competitive results are obtained, with magnetic resonance linewidths of roughly 300 Hz at the maximum signal-to-noise ratio, in a nonzero-magnetic-field setting, and in an atomic shot noise–limited regime.

Quantum simulators offer the potential to utilize the quantum nature of a physical system to study another physical system. In contrast to conventional simulation, which experiences an exponential increase in computational complexity, quantum simulation cost increases only linearly with increasing size of the problem, rendering it a promising tool for applications in quantum chemistry. The variational-quantum-eigensolver algorithm is a particularly promising application for investigating molecular electronic structures. For its experimental implementation, spin-based solid-state qubits have the advantage of long decoherence time and high-fidelity quantum gates, which can lead to high accuracy in the ground-state finding. This study uses the nitrogen-vacancy-center system in diamond to implement the variational-quantum-eigensolver algorithm and successfully finds the eigenvalue of a specific Hamiltonian without the need for error-mitigation techniques. With a fidelity of 98.9% between the converged state and the ideal eigenstate, the demonstration provides an important step toward realizing a scalable quantum simulator in solid-state spin systems.

With an explosive increase in demand for efficient luminescent materials in integrated optical systems, research on lanthanide ion-doped cubic sesquioxide ceramics has become important and attractive. Because of the large doping capability of lanthanide atoms and a low preparation temperature that is much lower than the melting point, sesquioxides have demonstrated promising potential as a host matrix in solid-state laser gain media. Here, for the first time, we demonstrate that two types of cation sites with different symmetries in cubic sesquioxides could empower effective manipulation of the luminescence properties of lanthanide dopants, leading to either magnetic dipole (MD) or electrical dipole (ED) emission, respectively. Using rigorous first-principle calculations, the luminescence properties of $\mathrm{Eu}$-doped sesquioxide $M_2{\mathrm{O}}_3$ ($M$ = $\mathrm{Sc},\mathrm{Y},\mathrm{La}$) are systematically investigated, unveiling the underlying competition mechanisms between MD and ED spontaneous emission. Through analyzing the formation energies of $\mathrm{Eu}$ dopants and intrinsic defects, the impact of strain and temperature on the doping concentration and dopant sites of $\mathrm{Eu}$ in sesquioxide is unambiguously elucidated, facilitating effective and selective manipulation of MD and ED emission.

A ternary cold source field effect transistor (T-CSFET) is proposed based on source density-of-state engineering, using a narrow-band-gap semiconductor at the source region. A current plateau at the subthreshold region is obtained in the transfer characteristics of T-CSFETs, namely an intermediate state with a constant current between on and off states. We meticulously study a two-dimensional T-CSFET based on a graphene-${\mathrm{Mo}\mathrm{S}}_2$ heterojunction by quantum transport simulations. It is shown that ternary states can be well distinguished with a current ratio between two adjacent states of over ${10}^3$ at a low overall supply voltage of 0.6 V. The intermediate state is stable with a constant current in a gate voltage region over 0.2 V and can be modulated by varying the doping density. We also obtain ternary transfer curves for T-CSFETs based on one-, two-, and three-dimensional materials. Based on T-CSFETs, a two-bit ternary adder with hybrid logic is implemented and verified by circuit simulations. The proposed T-CSFETs exhibit excellent properties for multivalue logic, including high drive current, tunable multivalue states, stable and reliable operation, energy and area efficiency, and a variety of material systems.

Recently, great progress has been made in the entanglement of multiple photons at various wavelengths and with different degrees of freedom for optical quantum information applied in diverse scenarios. However, multiphoton entanglement in the transmission window of green light under water has not yet been reported. Here, by combining femtosecond-laser-based multiphoton entanglement and entanglement-maintaining frequency up-conversion techniques, we successfully generate a green two-photon polarization-entangled Bell state and a green three-photon Greenberger-Horne-Zeilinger state, whose state fidelities are $0.893\pm 0.002$ and $0.595\pm 0.023$, respectively. Our result provides a scalable method to prepare green multiphoton entanglement, which may have wide applications in underwater quantum information.

In this work, we propose a deep convolutional attention neural network to realize the recognition of acoustic vortex fields. Convolutional attention mechanisms are introduced into the network together with the residual idea. The deep neural network is trained and then evaluated, and the performance is compared with those of several typical convolutional neural networks, including AlexNet, GoogLeNet, and ResNet. The results show that the improved neural network model based on the convolutional attention mechanism proposed here has better classification performance and stronger stability. The classification accuracy of the improved model on the whole test set reaches more than 95%, indicating that the model has a stable classification ability. Our work helps further study the detection and recognition of acoustic vortex fields, which will find many applications in scientific research and industry.

A wavy dielectric grating hosts bound states in the continuum (BICs) at nonzero Bloch wave number. For an oblique incident optical field with parameters near to the BICs, the reflectance spectrum exhibits an ultrasharp Fano line shape, and the reflected beam has a large negative Goos-Hänchen shift, due to excitation of the corresponding quasi-BIC with negative group velocity. Under incidence of a Gaussian beam with a sizable beam width, the excited quasi-BIC could travel a long distance along the direction of the Goos-Hänchen shift, designated as $L_{\mathrm{GH}}$, before the energy is completely radiated. If the length between the termination of the wavy shape and the focus of the incident Gaussian beam is smaller than $L_{\mathrm{GH}}$, sizable energy flux can be coupled into the waveguide mode of the flat dielectric slab that is connected to the wavy dielectric grating. Measurement of the energy flux of the waveguide mode can sense the variation of the refractive index of the background medium. The proposed sensing scheme can be integrated with a waveguide in an optical circuit.

Isometric feature mapping (Isomap) is a nonlinear dimensionality reduction algorithm based on the concept of manifold learning. The algorithm is widely used in neuroimaging, spectral analysis, and other fields. While Isomap performs well in certain scenarios, it still faces the challenge of time complexity when dealing with large-scale data sets. In this paper, we proposed a quantum Isomap algorithm that runs with quadratic dependence on the number of data points. Technically, our algorithm is based on two subroutines, quantum Floyd’s algorithm and quantum multidimensional scaling. They are of independent interest and may serve as potential tools for addressing other problems.

We investigate the dynamic properties of elastic lattices defined by tessellations of a curved hyperbolic space. The lattices are obtained by our projecting nodes of a regular hyperbolic tessellation onto a flat disk and then connecting those sites with simple linkages. Numerical and experimental investigations illustrate how their vibrational spectral properties are characterized by a high density of modes that are localized at the domain boundaries. Such properties govern the propagation of waves induced by broadband inputs. This suggests the potential for applications seeking the protection of bulk media from boundary-incident perturbations. We uncover the boundary-dominated nature of an exemplary hyperbolic lattice through the evaluation and analysis of its integrated density of states and vibrational spectrum. The dynamics of the lattice are also contextualized by our comparing them with those of continuous disks characterized by Euclidean and hyperbolic property distributions, which confirms that the lattice retains the boundary-dominated spectrum observed in the hyperbolic plane. We then numerically investigate the response of the lattice to transient pulses incident on the boundary and find that edge-confined wave propagation occurs. The modal and transient pulse-propagation behavior of the lattice is experimentally validated in a milled aluminum sample. By leveraging hyperbolic geometry, our mechanical lattice ushers in a novel class of mechanical metamaterials with boundary-dominated wave phenomena reminiscent of topologically protected systems suitable for applications in advanced wave control.

Pseudomagnetic fields are promising for manipulating classical waves, including optic, acoustic, and elastic waves. One fascinating phenomenon is the presence of Landau energy levels and the involved quantum Hall effect, which are usually considered to exist only in quantum systems. Unlike using synthetic Landau gauge fields, as in existing works, here we successfully create a symmetric gauge field to achieve a large-area uniform pseudomagnetic field in a two-dimensional phononic crystal by introducing linear variations in the single-cell parameters of the scatterer along both the x and y directions. Discrete Landau levels are generated near the Dirac cone region, and the unidirectional propagation of acoustic waves along the domain wall, i.e., quantum Hall transport, is observed in experiment. The proposed structure offers greater flexibility by allowing free choice of the effective vector potential. Our study expands the application perspective of artificial acoustic devices that rely on a pseudomagnetic field.

Spectral and band topologies have different degrees of freedom, usually treated separately. Recent studies have shown that spectral topology is not only related to the topological phase transition of bulk bands but can also influence the original boundary states. However, the interplay of these two topologies remains elusive, and the rich phase transitions resulting from their combination have yet to be explored. Here, we construct a two-dimensional non-Hermitian topological acoustic model using honeycomb-lattice cavity-tube configurations with controllable in-plane hopping and out-of-plane radiation losses. The phase diagram obtained is based on the interaction between trivial and nontrivial topological bands and unbroken and broken parity-time symmetry, depending on the hopping difference and loss strength trade-off. We experimentally observe novel exceptional points of topological boundary states, indicating that the energy band attraction effect is more substantial for the boundary than for the bulk. These results enrich non-Hermitian topological physics and may lead to robust yet ultrasensitive sensing applications by taking advantage of both topological and parity-time systems.

Recent advances in glass fabrication technology have allowed for the development of high-precision inertial sensors in devices weighing of the order of grams. Gram-scale inertial sensors can be used in many applications with tight space or weight requirements. A key element of these devices’ performance is the behavior of a mechanical resonator. We present a detailed study on the design of resonators for such sensors. First, we consider how the mechanical parameters of a resonator couple with an inertial sensor’s performance. Then, we look at how to geometrically design resonators to achieve specific mechanical behavior without undergoing brittle failure. Both analytic tools and finite element analysis are used to this end. We then derive expressions that can be used to optimize the performance of an inertial sensor for a specific sensitive bandwidth. A simple geometry used throughout the field is studied as an example. However, the results are presented in a general form so that they can be easily adapted to any required geometry and use case. Ultimately, the results presented here guide the design of gram-scale inertial sensors and will improve the performance of devices that follow them.

Optical beam deflection is a popular method to measure the deformation of micromechanical devices. As it measures mostly a local slope, its sensitivity depends on the location and size of the optical spot. We present a method to evaluate precisely these parameters, using the relative amplitude of the thermal noise–induced vibrations. With a case study of a microcantilever, we demonstrate the accuracy of the approach, as well as its ability to fully characterize the sensitivity of the detector and the parameters (mass and stiffness) of the resonator.

We propose the design of single-layer, double-layer, and triple-layer configurations of magnonic ring couplers, which perform spin-wave mode filtering and provide interlayer signal transmission in three-dimensional architectures of magnonic integrated circuits. We study the characteristics of spin-wave dynamics in coupled magnonic structures with a ring resonator in planar and vertical configurations using Brillouin light scattering and the micromagnetic simulation method based on numerical solution of the Landau–Lifshitz–Gilbert equation. The mechanisms of backward and forward coupling control of spin-wave transport in yttrium iron garnet stripe placed in the proximity of the magnonic microring resonator are elucidated. The possibility of reversing the direction of spin-wave propagation with simultaneous selection of transverse spin-wave modes is demonstrated. It is shown that, in the proposed structure, multistream selection of a spin-wave signal is possible due to spatial frequency and simultaneous mode separation. Lateral and vertical magnonic rings could be used for magnonic logic application with the variation of the phase and amplitude of signals. We also demonstrate that the spin-wave mode order is an additional parameter that can be used to simultaneously control the transmission of the ring coupler with the facility to encode the logical state “0” or “1” with the width mode order. The multistream selection of a spin-wave signal and the spatial frequency and simultaneous mode separation lie behind the application of the proposed magnonic ring coupler as a multiport interconnection element and/or functional logical unit in reconfigurable integral blocks of magnonic networks.

Classification, the computational process of categorizing an input into preexisting classes, is now a cornerstone in modern computation in the era of machine learning. Here, we propose an approach for a quantum physical computer; a quantum classifier, based on quantum transport of particles in a trained quantum network. The classifier is based on sending a quantum particle into a network and measuring the exit point of the particle, which serves as a “class” and can be determined by changing the network parameters, differing from standard quantum computers as no gate operations are required to perform the computation. Using this scheme, we demonstrate three examples of classification. In the first, wave functions are classified according to their overlap with predetermined (random) groups. In the second, we classify wave functions according to their level of localization. Both examples use small training sets and achieve over 95% precision and recall. The third classification scheme is a “real-world problem,” concerning classification of catalytic aromatic aldehyde substrates according to their reactivity. Using experimental data, the quantum classifier reaches an average 86% classification accuracy. We show that the quantum classifier outperforms its classical counterpart for these examples and demonstrates clear advantage, especially in the regime of “small data.” These results pave the way for a classification scheme that can be implemented as an algorithm and potentially realized experimentally on quantum hardware.

The design of a highly efficient planar focal lens with a near-unity numerical aperture remains a challenge, despite efforts made on this topic. In this paper, we propose a two-dimensional nonlocal transmission-type metasurface composed of subwavelength-sized channels and groove arrays, aiming to attain highly efficient acoustic focusing. We show that such a nonlocal structure can be efficiently designed by an inverse method based on the multistructural model, even when the number of constituent units becomes considerably large. As examples, metasurfaces both for the plane-wave source and for the point source have been designed. Numerical results show that our proposed nonlocal metasurface exhibits a much higher focusing efficiency than the corresponding structures based on the principle of the generalized Snell law. The structure designed for the point source has also been verified experimentally, showing good agreement between the numerical and experimental results. Our design contributes an alternative idea for wave control, which should be useful in acoustic sensors, energy harvesting, and so on.

Photonic reservoir computing has been successfully utilized in time-series prediction as the need for hardware implementations has increased. Prediction of chaotic time series remains a significant challenge, an area where the conventional reservoir computing framework encounters limitations of prediction accuracy. We introduce an attention mechanism to the reservoir computing model in the output stage. This attention layer is designed to prioritize distinct features and temporal sequences, thereby substantially enhancing the prediction accuracy. Our results show that a photonic reservoir computer enhanced with the attention mechanism exhibits improved prediction capabilities for smaller reservoirs. These advancements highlight the transformative possibilities of reservoir computing for practical applications where accurate prediction of chaotic time series is crucial.

We report spin-wave diffraction, caustic beam emission, and the formation of Talbot carpets in an yttrium iron garnet (YIG) film equipped with magnonic Fabry-Perot resonators. The resonator structures are created by patterning cobalt iron boron ($\mathrm{Co}$-$\mathrm{Fe}$-$\mathrm{B}$) nanostripes on the YIG film. Small gaps in the $\mathrm{Co}$-$\mathrm{Fe}$-$\mathrm{B}$ nanostripes generate a magnetic field profile within the YIG film, functioning as a slit grating when the resonators block incoming spin waves at specific frequencies. We employ super-Nyquist sampling magneto-optical Kerr effect (SNS-MOKE) microscopy to image the transport of spin waves through the slits and supplement our experimental observations with micromagnetic simulations. For a single slit, we observe a transition from spin-wave diffraction to caustic beam emission as the slit size decreases. These phenomena are influenced by the effective magnetic field within the slit, which varies with the direction of magnetization in either the YIG film or the $\mathrm{Co}$-$\mathrm{Fe}$-$\mathrm{B}$ nanostripes. For multiple slits, we detect self-imaging of spin-wave profiles and the formation of Talbot carpets. Furthermore, we demonstrate active tuning of spin-wave interference patterns through magnetic switching in the Fabry-Perot resonators or by rotating the in-plane magnetization of the YIG film. The magnonic grating system described here integrates low-loss spin-wave transport and programmable spin-wave interference, offering potential applications in advanced magnonic computing devices.