Analog Ising machines are dedicated hardware solvers designed to solve NP hard optimization problems. However, the global optimum is often not found as the system gets stuck in local minima. While several strategies exist to increase the chance of escaping local minima, these methods often require extensive parameter tuning. In this work, we investigate the injection of large noise as a standalone scheme and in combination with annealing to improve the success rate and the time-to-target (TTT) of analog Ising machines for MaxCut problems. We demonstrate that optimizing the noise improves the TTT by several orders of magnitude and renders both approaches competitive with state-of-the-art schemes, such as chaotic amplitude control. Moreover, we are able to predict an optimal noise value based on the problem connectivity, statistics of the coupling matrix and the coupling strength, thereby eliminating the need for costly parameter optimization.

With the rapid advancement of generative artificial intelligence, efficiently training complex neural networks has emerged as a central challenge in deep learning. Ising machines, as specialized quantum-inspired hardware, show considerable promise for solving combinatorial optimization problems and training neural networks. However, current existing approaches are often limited to shallow architectures due to inefficient sampling strategies. In this study, we introduce a deep belief network (DBN) architecture that utilizes the sampling mechanism of a coherent Ising machine integrated with a spiking neural network (SNN-CIM). By stacking two restricted Boltzmann machines (RBMs), the model supports hierarchical feature learning while significantly enhancing training efficiency. The SNN-CIM mitigates amplitude heterogeneity through dissipative pulse injection and employs Gaussian noise to drive the system toward thermal equilibrium, enabling effective deep network training. Experimental results demonstrate that a single-layer RBM achieves $96.4\mathrm{\%}$ accuracy on the MNIST dataset, while the full DBN reaches $98.9\mathrm{\%}$ on the test set. Compared to Metropolis-Hastings-based MCMC sampling, the SNN-CIM exhibits broader sampling coverage and higher efficiency, achieving orders-of-magnitude performance improvements on large-scale problems. These findings underscore the potential of SNN-CIMs for scalable deep generative modeling and offer alternative pathways for enhancing performance in quantum-inspired computing and deep learning.

Determining the ground and low-lying excited states is critical in numerous scenarios. Recent work has proposed the ancilla-entangled variational quantum eigensolver (AEVQE) that utilizes entanglement between ancilla and physical qubits to simultaneously target multiple low-lying energy levels. In this work, we report the implementation of the AEVQE on a superconducting quantum cloud platform, demonstrating the full procedure of solving the low-lying energy levels of the $\mathrm{H}$${}_2$ molecule and the transverse-field Ising models (TFIMs). We obtain the potential energy curves of $\mathrm{H}$${}_2$ and show an indication of the ferromagnetic to paramagnetic phase transition in the TFIMs from the average absolute magnetization. Moreover, we investigate multiple factors that affect the algorithmic performance and provide a comparison with ancilla-free VQE algorithms. Our work demonstrates the feasibility of the AEVQE algorithm and offers guidance for the VQE approach in solving realistic problems on publicly accessible quantum platforms.

Linearly polarized elastic waves propagating in a linear path have been extensively explored in numerous applications from biomedical imaging to structural health monitoring; however, elastic waves propagating in a circularly polarized helical path have been less explored because of the challenges in their generation and control. In this paper, we harness conventional actuation methods combined with sheets decorated with Archimedean spirals to generate elastic helical waves. We show that our metamaterials can support the propagation of such waves along a curved path in a topologically protected manner. Moreover, we also show the creation and propagation of helical waves in our metamaterials without the need for wave guiding or domain interfaces, all with a single-mode excitation source. We establish our methodology for flat plates and show the wave evolution as the metamaterials transition from slightly curved plates to fully curved cylinders. We observe the preservation of topologically protected edge states and helical-wave beaming at different frequencies without the need for domain interfaces. Furthermore, we leverage these modes to tune the helicity of the propagating waves. Our methodology opens previously inaccessible avenues for the generation and control of elastic helical waves using single-source actuation, which can be applied in numerous applications.

Employing time-resolved Kerr rotation microscopy, we demonstrate electrical control over the orientation of the persistent spin helix in a double $\mathrm{Ga}\mathrm{As}$ quantum well structure equipped with independent front and back gates. We map spin polarization patterns under varying gate voltages and show that coordinated tuning of two gates enables switching between two orthogonal persistent spin helix (PSH) orientations. This is achieved by inverting the Rashba spin-orbit coupling parameter while maintaining a stable electron density, thus overcoming the leakage-current limitations inherent to single-gate systems. A Fourier analysis of the spin maps provides quantitative extraction of spin-orbit coupling strengths, revealing that the Dresselhaus term remains nearly constant while the Rashba parameter is controlled by the difference between the gate voltages. These results establish dual-gate quantum well architectures as an effective platform for precise PSH manipulation and highlight their potential for spintronic applications such as spin-logic devices and long-distance spin interconnects.

Using self-consistent electron Monte Carlo simulations, we optimize an alloy-graded heterobarrier layer for in situ recycling of phonons emitted in $\mathrm{Ga}\mathrm{N}$ semiconductor diode devices, leading to improved electrical and thermal performance. The band offset and effective mass of $\mathrm{Al}\mathrm{In}\mathrm{Ga}\mathrm{N}$ quaternary alloying are engineered to enhance thermionic transport across the built-in potential barrier in diode devices (e.g., LEDs, Schottky diodes), leading to an increase in current and upstream phonon reabsorption compared to the same device with no heterobarrier. The simulations indicate a current gain of over 10%, which is consistent with the results of a thermionic model and demonstrates potential for integrated cooling with simultaneous current gain in semiconductor devices.

Delay-line detectors (DLDs) are essential instruments for precise spatiotemporal particle detection. Traditional DLD event reconstruction methods struggle with overlapping signals from particles that arrive close together in space and time, limiting their multi-hit capabilities. Here, we report substantial updates to machine learning-based multi-hit reconstruction in DLDs, with a focus on the double-hit events and the first results for triple-hit events. Our enhanced neural-network pipeline includes improved data generation, cross-channel peak detection, and peak matching models. Using a spatial grid measurement, as well as a measurement with a discrete temporal structure, as benchmarks, we demonstrate significant improvements in both the spatial and energy domains. These advancements enable improved temporal and spatially resolved multi-hit detection in particle correlation experiments, with potential applications in attosecond physics, cold target recoil ion momentum spectroscopy, ultracold chemistry, and other fields.

Phase correlations are an underexplored vulnerability in quantum key distribution. Here, we present an experimental and simulated characterization of correlations arising from electro-optic phase encoding, over repetition rates up to the GHz level. To mitigate this vulnerability (and all side channels arising from active phase modulators), we propose a “path-selection modulation” source that eliminates the need for active phase modulation altogether. Encoding is achieved by randomly selecting between multiple paths, each path corresponding to one of the desired encoded states. Phase randomization is achieved using gain switching. We characterize this source at a clock rate of 1 GHz.

We implement a feedback protocol to suppress the ac Stark shift in a two-photon rubidium optical frequency reference, reducing its sensitivity to optical power variations by a factor of 1000. This method alleviates the tradeoff between short-term and long-term stability imposed by the ac Stark shift, enabling us to simultaneously achieve instabilities of $3\times {10}^{-14}$ at 1 s and $2\times {10}^{-14}$ at ${10}^4$ s. We also quantitatively describe, and experimentally explore, a stability limit imposed on clocks using this method by frequency noise on the local oscillator.

Dispersive readout is widely used to perform high-fidelity measurement of superconducting qubits. Much work has been focused on the qubit readout fidelity, which depends on the achievable signal-to-noise ratio and the qubit relaxation time. As groups have pushed to increase readout fidelity by increasing readout photon number, dispersive readout has been shown to strongly affect the postmeasurement qubit state. Such effects hinder the effectiveness of quantum error correction, which requires measurements that both have high readout fidelity and are quantum nondemolition (QND). Here, we experimentally investigate non-QND effects in the fluxonium. We map out the state evolution of fluxonium qubits in the presence of resonator photons and observe that these photons induce transitions in the fluxonium both within and outside the qubit subspace. We numerically model our system and find that transitions to higher-excited states and coupling to an external spurious mode are necessary to explain observed non-QND effects.

Networks of coupled nonlinear oscillators are emerging as powerful physical platforms for implementing Ising machines, yet the relationship between parametric oscillator implementations and traditional oscillator-based Ising machines remains underexplored. In this work, we develop a Kuramoto-style canonical phase description of parametric oscillator Ising machines by starting from the Stuart-Landau oscillator model, the canonical normal form near a Hopf bifurcation, and a natural reduced description for many parametric oscillator implementations such as the degenerate optical parametric oscillator. The resulting phase dynamics combine the usual phase-difference coupling observed in the standard Kuramoto model along with an intrinsic phase-sum term that is generated when conjugate coupling is considered. Moreover, our formulation helps explain why explicit second-harmonic driving is unnecessary in parametric oscillators and also reveals how quasi-steady amplitude heterogeneity scales the original strength of the spin interaction with potentially adverse impacts on the solution quality. Our work helps develop a unifying view of the oscillator-based approach to designing Ising machines.

This investigation employed microwave whispering-gallery mode (WGM) analysis to characterize the dielectric properties of a cylindrical, single-crystal sample of calcium tungstate (${\mathrm{Ca}\mathrm{WO}}_4$). Through investigation of quasi-transverse-magnetic and quasi-transverse-electric mode families, we can assess loss mechanisms and relative permittivity from room temperature to cryogenic conditions. We report the biaxial permittivity values of ${\epsilon }_{||}^{295\mathrm{K}}=9.029\pm 0.009$ and ${\epsilon }_{\perp }^{295\mathrm{K}}=10.761\pm 0.011$ at room temperature, and ${\epsilon }_{||}^{4\mathrm{K}}=8.794\pm 0.009$ and ${\epsilon }_{\perp }^{4\mathrm{K}}=10.440\pm 0.010$ at liquid-helium temperature. Components are denoted with respect to the $c$-axis of the crystal unit cell. The parallel component agrees well with the published literature at megahertz frequencies; however, the measured perpendicular component is 4.8% lower. The WGM technique offers greater precision, with accuracy limited primarily by the uncertainty in the crystal’s dimensions. WGMs also serve as sensitive probes of lattice dynamics, enabling the monitoring of temperature-dependent loss mechanisms. At room temperature, the measured loss tangents were $\tan {\delta }_{||}^{295\mathrm{K}}=(4.1\pm 1.4)\times {10}^{-5}$ and $\tan {\delta }_{\perp }^{295\mathrm{K}}=(3.64\pm 0.92)\times {10}^{-5}$. Upon cooling to 4 K, the loss tangents improved by approximately two orders of magnitude, reaching $\tan {\delta }_{||}^{4\mathrm{K}}=(1.56\pm 0.52)\times {10}^{-7}$ and $\tan {\delta }_{\perp }^{4\mathrm{K}}=(2.05\pm 0.79)\times {10}^{-7}$. These cryogenic values are higher than those reported in prior studies, likely due to a magnetic loss channel associated with an unidentified paramagnetic spin ensemble. These findings have implications for the use of ${\mathrm{Ca}\mathrm{WO}}_4$ in applications such as spin-based quantum systems and cryogenic bolometry.

We demonstrate a quasicontinuous sub-$\text{μ}\mathrm{K}$ strontium source achieved without the use of a high-finesse cavity-locked laser. Our frequency reference is based on a dispersion-optimized, fiber-based frequency comb that enables sub-kHz linewidths. The long-term stability of the comb is defined by an external rf reference: either a 10 MHz rf signal from the Dutch Metrology Institute (VSL) or a tunable rf source whose long-term stability is maintained by monitoring and stabilizing the position of a narrow-line magneto-optical trap (MOT) [Sillus et al., Rev. Sci. Instrum., 92, 033204 (2021); Heizenreder et al., Continuous cloud position spectroscopy using a magneto-optical trap, Phys. Rev. Appl. (2026)]. The comb-stabilized system is benchmarked against a conventional cavity-locked laser and achieves comparable performance in broadband and single-frequency MOTs using the narrow ${}^1{S}_0\to {}^3{P}_1$ laser-cooling transition. We generate high-flux, sub-$\text{μ}\mathrm{K}$ samples of all three bosonic strontium isotopes and demonstrate quasicontinuous outcoupling from the MOT. These results highlight the system’s suitability for compact, robust, and field-deployable continuous cold-atom devices.

Fisher information provides a rigorous theoretical benchmark for evaluating quantum sensor sensitivity; however, a comprehensive framework for quantifying the fundamental limits of Rydberg-atom microwave electrometers remains lacking. In this work, we establish such a framework by deriving the Fisher information for slope detection and establishing its connection to sensitivity through the signal-to-noise ratio, leading to an analytical expression jointly determined by photon shot noise and atomic response. Numerical implementation with real parameters in cesium vapor systems reveals a Fisher-optimized sensitivity below the $\mathrm{nV}\mathrm{c}{\mathrm{m}}^{-1}\mathrm{H}{\mathrm{z}}^{-1/2}$ level, highlighting a substantial potential for sensitivity increase in practical experiments through the suppression of technical noise. Importantly, the theory predicts that subnanovolt sensitivity is robust regarding moderate variations in system parameters, thereby delineating both the ultimate sensitivity and the optimal operational regime of Rydberg-atom microwave electrometers.