Hopfions, associated with higher-dimensional topology through the Hopf fibration, exhibit exotic features like complex knots and improved stability compared to skyrmions, enhancing their appeal for innovative applications. In this paper, we study the nonlinear response of magnetic hopfion to microwave fields. We observe the emergence of higher-order harmonics of the driving microwave field as it interacts with the hopfion. By carefully selecting the driving frequency, the corresponding harmonic can efficiently excite the localized magnon state of a hopfion. Our results demonstrate the promising potential of hopfions in nonlinear magnonics.

Precise, real-time monitoring of magnetic field evolution is significant in applications including magnetic navigation and searches for physics beyond the standard model. One main field-monitoring technique, the spin-precession magnetometer (SPM), observes electron, nucleus, color center, or muon spins as they precess in response to their local magnetic field. Here, we study Bayesian signal-recovery methods for SPMs in the free-induction decay mode. In particular, we study tracking of field changes well within the coherence time of the spin system and thus well beyond the response bandwidth, as in [R. Jiménez-Martínez et al. Phys. Rev. Lett. 120, 040503 (2018)]. We derive the Bayesian Cramér-Rao bound that dictates the ultimate precision in estimating the Larmor frequency, which we show is attained by the computationally expensive prediction error method. Relative to this benchmark, we show that the extended Kalman filter (EKF) and cubature Kalman filter offer near-optimal tracking that is also computationally efficient, with the use of the latter giving better results only for a large spin number. Focusing thus on the EKF, we show that it is sufficient to accurately track fluctuating and unknown transient signals. Our methods can be easily adapted to other types of sensors undergoing nonlinear dissipative dynamics and experiencing intrinsic Gaussian-like stochastic noises.

A coupled-oscillator system displays enhanced sensitivity of its saturated steady-state (SS) oscillation frequency to small parameter perturbations near an exceptional-point degeneracy (EPD), a property that can be used to realize EPD-based sensors. Linear $\mathcal{P}\mathcal{T}$-symmetric systems, consisting of two coupled resonators, exhibit EPDs around which square-root sensitivity is observed. However, linear models are insufficient for realistic systems that rely on nonlinear, saturable-gain elements, particularly when $\mathcal{P}\mathcal{T}$-symmetry is broken. Thus, we study the SS of a general system of two coupled oscillators featuring EPDs and saturable nonlinear gain, using coupled-mode theory. We do this by synthesizing and extending prior SS analyses of the system’s stability and its square-root and cubic-root oscillation frequency sensitivity at a unique third-order SS-EPD. We add an SS analysis of saturated gain, energy, and oscillation-frequency sensitivity in the vicinity of the third-order SS-EPD, enabling characterization of the various SS regimes. We determine that the stable and bistable regions in parameter space directly depend on the saturated-gain values; that the dynamic range of high sensitivity around degenerate conditions is extended by increasing losses, consequently reducing the system’s stored energy; and that, to exploit the cubic-root-like sensitivity associated with the third-order SS-EPD, the suggested working regime is best confined to operation within the weakly coupled regime and not exactly at the third-order SS-EPD. Finally, we apply the model to two electronic circuits that exhibit cubic-root sensitivity, demonstrating the application and limitations of this analysis.

Scalable quantum computing in frequency-crowded nuclear spin registers promises long coherence times and native many-body logic. However, as system size increases, spectral crowding introduces two fundamentally competing challenges: coherent-control-induced spectral crosstalk and fragility to frequency fluctuations arising from charge and magnetic noise. Conventional pulse shaping optimized for crosstalk suppression is intrinsically incompatible with robustness against frequency fluctuations. In this work, we show that this incompatibility reflects a fundamental breakdown of single-qubit robust control principles in many-body entangling operations, manifested as a robustness inversion under single-tone ESR control: locally robust pulses disrupt intersubspace phase synchronization and degrade the robustness of many-body operations. We further uncover a Hilbert-space dilution effect, whereby $C$ Z gate robustness decays exponentially with system size, scaling as $1/2^M$. Leveraging these insights, we establish a phase-synchronized global multitone control paradigm that simultaneously suppresses frequency fluctuations and spectral crosstalk, in which square pulses—traditionally avoided due to spectral leakage—induce an intersubspace dynamical decoupling mechanism that converts unstructured crosstalk into effectively static, geometrically neutralized frequency noise. Full Hamiltonian simulations demonstrate programmable quantum logic units achieving the fidelities of many-body entangling operations approaching 99.99%, representing an order-of-magnitude improvement over conventional strategies, and establishing a scalable route toward fault-tolerant modular quantum computing.

Hong-Ou-Mandel (HOM) interference is a fundamental tool for assessing photon indistinguishability in quantum information processing. While the effect of chromatic dispersion on HOM interference has been widely studied, the interplay between dispersion and the finite detection window of realistic measurement devices remains underexplored. In this work, we demonstrate that the rectangular coincidence window inherent to modern time-tagging modules, which effectively acts as a temporal filter, breaks the standard dispersion cancellation condition and restores sensitivity to symmetric group-velocity dispersion. We derive an analytical model for type-II SPDC processes that predicts a modification of the HOM dip shape, specifically the emergence of characteristic oscillations and dip broadening. We experimentally validate this theoretical framework using a ppKTP source and transmission through optical fibers of lengths up to 29 km. The experimental data show excellent agreement with the model, confirming the presence of window-induced oscillations and allowing for the precise extraction of the fiber dispersion parameter. These findings underscore the significance of accounting for finite timing resolution in the design and characterization of dispersive quantum communication links.

Nitrogen-vacancy (NV) centers in diamond have been shown to be capable of detecting ac magnetic fields with high sensitivity, spectral resolution, and spatial resolution. However, most studies so far have focused on the regime of time-averaged or time-correlated measurements, while little attention has been paid to the single-shot regime. Here we show that the amplitude and phase of an ac field can be retrieved from a single pair of two consecutive measurements. We demonstrate this concept by measuring a 4 MHz ac field with a per-shot amplitude and phase sensitivity of $78\mathrm{nT}$ and $63\mathrm{mrad}$, respectively, at a temporal resolution of $320\mathrm{\mu }\mathrm{s}$. We also investigate the effects and quantify the errors resulting from probe frequency detunings, as well as operating in the strong field regime. Moreover, we showcase the ability of the measurement protocol to dynamically change the probe frequency in real time. This work advances the use of NV centers for real-time measurements of ac magnetic fields.

We study the propagation of charge carriers in planar graphene under the combined influence of a constant transversal magnetic field $B$ and an in-plane varying electric potential $\varphi (x)$. By suitably designing the potential landscape $\varphi (x)$, we may effectively steer charge carriers generated by photoexcitation, for example, in order to achieve an efficient charge separation. In comparison to previously considered scenarios for the magnetophotoelectric effect in graphene involving folded graphene or graphene edges, for example, this scheme offers advantages in terms of robustness, scalability, and control. Thus, our findings may pave the way for transport schemes (“graphene electronics”) or photoelectric/photovoltaic applications.

Exploring materials with unconventional spin transport properties and manipulating magnetic moments are core focuses in spintronics. Herein, we report the crystallographic orientation-dependent field-free switching of perpendicular magnetization in $\mathrm{STO}//{\mathrm{RuO}}_2(100)/[\mathrm{C}\mathrm{o}/\mathrm{Pt}{]}_2$ heterostructure, driven by spin splitting torque of ${\mathrm{RuO}}_2$. Unlike ${\mathrm{RuO}}_2(101)$-based systems, the $\mathrm{STO}//{\mathrm{RuO}}_2(100)/[\mathrm{C}\mathrm{o}/\mathrm{Pt}{]}_2$ eliminates confounding factors including crystal structural effects and perpendicular magnetic moment tilting, which allows us to attribute field-free switching exclusively to ${\mathrm{RuO}}_2$ antiferromagnetic order. When the Néel vector in $\mathrm{STO}//{\mathrm{RuO}}_2(100)$ deviates from the [001] easy axis and acquires an out-of-plane component, the anisotropic spin splitting effect generates out-of-plane spin polarization spin current, which provides damping-like torque to drive field-free switching at a critical current density of approximately $1.6\times {10}^7\text{A}/{\text{cm}}^2$. Complemented by temperature-dependent oscillating exchange bias that reverses sign at 90 K, our results unambiguously confirm the antiferromagnetic order of ${\mathrm{RuO}}_2$ in the heterostructure. This work offers evidence for spin splitting torque in ${\mathrm{RuO}}_2$-based heterostructures, deepens the understanding of altermagnetic spin transport, and paves the way for the development of field-free spintronic devices.

A major source of error in quantum error correction (QEC) arises from imperfect two-qubit gates, where leakage errors are notoriously difficult to correct within the QEC framework. The iswap gate’s inherently low-leakage nature makes it a compelling approach to address this challenge. However, its implementation in transmon qubits is hindered by parasitic $ZZ$ coupling induced by the required $XY$ interaction, posing a significant challenge for achieving high-fidelity control. In this work, we propose a Graph Surgery framework to theoretically analyze this problem and present a dual-microwave-drive scheme that dynamically cancels $ZZ$ interaction. To address residual transition errors, which we identified as the key bottleneck after $ZZ$ suppression, we further develop the Calibrated Derivative Error Nulling via Correlated Envelopes pulse-shaping protocol. Through this optimized approach, we demonstrate a 46-ns iswap gate with a fidelity of $(99.84\pm 0.06)\%$, suppressing intrinsic leakage to $(3.5\pm 2.6)\times {10}^{-5}$ and conditional phase error to $2.1\times {10}^{-6}$. The scheme features low dependency on specific hardware parameters and requires no auxiliary control architecture. Our results provide a flexible pathway to mitigate leakage challenges, establishing the iswap gate as a high-fidelity primitive for scalable QEC architectures.

A cold-atom gravimeter, with high sensitivity, long-term stability, and absence of mechanical wear, provides an unprecedented technical means for geology, resource exploration, and the establishment of a high-resolution marine geoid. However, present atom gravimeters still face severe challenges from broadband and large-amplitude vibrations caused by waves and engines in the dynamic marine environment. Conventionally, vibration compensation is employed to address such issues, but it is insufficient for accelerations with amplitudes reaching up to $1\mathrm{m}/{\mathrm{s}}^2$ during navigation. Variations in the probe velocity can lead to large detuning of the Raman laser and thus introduce additional phase shifts. To address this problem, we proposed a postcorrection method, Raman detuning compensation, built upon the existing vibration compensation, and validated its effectiveness aboard a commercial cargo ship, where the data noise can be reduced to 45% of the previous value after compensation during the voyage. This scheme is expected to overcome the limitations of existing vibration compensation methods and advance cold-atom gravimeters toward practical vehicular, marine, and aviation applications.

Pressure metrology in cryogenic ultrahigh vacuum is limited by the need for in situ readout that does not perturb the cold environment. We propose a passive gauge based on the vertical translational mode of a ferromagnetic sphere levitated above a superconducting surface by the Meissner effect. In the molecular-flow regime, gas-surface momentum exchange adds a damping rate ${\gamma }_{\mathrm{gas}}\propto P$, so the pressure can be inferred from mechanical ring-down. Using Fisher-information analysis, we derive Cramér–Rao lower bounds for estimating the total damping rate and propagate them to an analytic pressure uncertainty that includes pressure-independent losses from residual dissipation and eddy currents. The resulting scalings with sphere radius $R$ reveal an optimum: larger $R$ improves low-$P$ sensitivity but increases intrinsic damping and narrows the molecular-flow range. For $T_{\mathrm{env}}=4.2\mathrm{K}$ and intrinsic damping ${\gamma }_0={10}^{-6}{\mathrm{s}}^{-1}$, we find $R_{\mathrm{opt}}\approx 2.4\mathrm{mm}$ and a resolution floor $\delta P_{\text{mea}}\approx 4\times {10}^{-10}\mathrm{Pa}$ at a signal-to-noise ratio of 1, with a molecular-flow upper limit of ${10}^{-2}–{10}^{-1}\mathrm{Pa}$ set by gas species and the Knudsen criterion. These results provide sizing and integration-time guidelines for levitated mechanical cryogenic vacuum gauges.

A broadband electromagnetic source is important for scientific and technological applications. Quantum vacuum fluctuations, which manifest most prominently in the Casimir effect, provide a fundamentally broadband electromagnetic source. Here, we explore a potential consequence of the broadband nature of quantum vacuum fluctuations, by showing that such fluctuations can enable measurement of material permittivity over a broad frequency range. Specifically, we consider the Casimir force in a parallel-plate geometry, with one plate covered by a nanoscopic thin film. Using a machine learning approach, we show that one can infer both the thickness of the film and its permittivity over a broad frequency range, starting from the dependency of the Casimir forces on the spacing between the two plates. Our work highlights the application potential of using vacuum fluctuations as a naturally existing broadband electromagnetic source for material characterization and shows that the inverse problem in Casimir force calculation can be solved with machine learning.

The imprint effect, a major reliability issue in ferroelectric memories, degrades the device by shifting the coercive field over time. This work reviews existing imprint models and introduces a phase-field model for polycrystalline thin films. The model identifies grain-boundary charge screening (GBCS) as a key bulk imprint mechanism. It demonstrates that the depolarization field near grain boundaries attracts trapped charges, which in turn suppress domain nucleation for reverse polarization switching. Furthermore, the model reveals that domain wall motion is essential for the GBCS mechanism to induce imprint in a thin film and can explain the widened hysteresis loop observed in experiments. These findings provide new insights into imprint physics and advance strategies for improving ferroelectric memory reliability.

Interfacial engineering of spin currents is crucial for developing spintronic and memory devices. Here, we demonstrate the nonreciprocal transport of spin currents in Pt/Ti and Ti/Pt bilayers adjacent to a Py ferromagnetic layer using spin pumping and spin-torque ferromagnetic resonance (ST-FMR) techniques. Systematic thickness-dependent measurements reveal that the magnetic damping, which reflects the efficiency of spin-current injection, depends strongly on the stacking order. In Py/Pt/Ti structures, the magnetic damping increases with Pt thickness and saturates, following the conventional spin-diffusion model. In contrast, Py/Ti/Pt structures exhibit a rapid decline and saturate at thicker Ti thicknesses. The reduction of damping in the Py/Ti/Pt structures upon adding the Pt layer indicates strong orbital pumping and spin backflow at the Ti/Pt interface. Furthermore, ST-FMR measurements show opposite signs and distinct magnitudes of the spin-orbit torque efficiency for the two stacking configurations. These results confirm that the Pt layer dominates spin-current generation via the spin Hall effect, while the Ti layer contributes through the orbital Hall effect. Our results establish a clear asymmetry in spin-current propagation across Pt/Ti interfaces and provide a quantitative framework for understanding interfacial spin transport in multilayer spintronic systems.

Fast and robust entanglement generation is a central requirement for scalable quantum technologies, where limited coherence time, parameter drift, and timing uncertainty can otherwise erase quantum advantage. We investigate entanglement generation in topological open quantum systems governed by an effective non-Hermitian Hamiltonian. For a lossy two-qubit dimer with asymmetric dissipation, tuning the coherent coupling across an exceptional point (EP) produces a PT-like crossover between decay-rate splitting and frequency splitting, which directly reshapes the conditional (no-jump) concurrence dynamics in the single-excitation manifold. Embedding the dimer into a non-Hermitian Su-Schrieffer-Heeger (SSH)-like ladder yields multiple EPs through edge-bulk hybridization. Our key contribution is a practical design rule: among these EPs, the operational one for entanglement is the “edge-mode EP,” defined by the EP whose coalesced eigenvector is maximally localized on the target edge pair; the near-optimal working point lies slightly above this EP, balancing preparation speed, no-jump success probability, timing-jitter tolerance, and robustness to bulk detuning disorder. Using thresholded operational metrics (preparation time, success probability, rate, jitter window, and disorder sensitivity), we map these trade-offs and show that topology-assisted confinement plus EP-enabled mode selection enables fast and robust heralded edge entanglement.

Bioinspired neuromorphic spiking sensors hold great promise for energy-efficient and architecturally simplified neuromorphic networks. Here, an energy-efficient artificial spiking sensor based on a patterned polycrystalline vanadium dioxide (${\text{VO}}_2$) memristor grown by direct-current (dc) reactive magnetron sputtering was developed to achieve high sensitivity and low-energy consumption simultaneously. The memristor demonstrates high endurance in both static and dynamic electrical measurements with low cycle-to-cycle variations and excellent spiking performance when integrated into a 1R (memristor)-1T (transistor) spiking circuit. By optimizing the memristor current and output capacitor, the circuit achieves tunable output frequencies of 181–784 kHz under a 5-V supply voltage and an estimated intrinsic capacitance of approximately 0.51 nF. In-sensor temperature encoding is also achieved under a memristor current of 0.1478 mA without an additional external capacitor, exhibiting an excellent sensitivity of $2.98–13.62\mathrm{kHz}/°\mathrm{C}$, a low total energy consumption of 2.73–5.63 nJ/spike and a signal-to-noise and distortion ratio (SNDR) of 30.95–41.21 dB from 30 to $50°\mathrm{C}$, as well as a high resolution of $0.18°\mathrm{C}$ at $47.5°\mathrm{C}$. Compared with conventional CMOS readout integrated circuits, the energy consumption can be further reduced by lowering the supply voltage and minimizing the intrinsic capacitance through full circuit integration, while the SNDR can be enhanced by mitigating the stochasticity of ${\text{VO}}_2$ and reducing circuit noise, which will require further optimizations of material characteristics and device geometry.

Large language models have dominated the scientific and media landscape due to their impressive performance in processing large amounts of data and producing humanlike text. Nevertheless, their high energy demand and slow processing remain bottlenecks to further improving model quality while making the models broadly accessible. To address these bottlenecks, we investigate how reservoir computing performs in natural language processing, which could enable fast and energy-efficient hardware implementations. Studies investigating the use of reservoir computing as a language model remain sparse. In this paper, we compare three distinct approaches to character-level language modeling: two reservoir-computing approaches, in which only an output layer is trainable, and a well-known transformer-based architecture, which learns a fully trainable attention-based sequence representation. We explore the performance, computational cost, and prediction accuracy of both paradigms while varying the number of trainable parameters consistently across all models. Using a consistent pipeline for all three approaches, we demonstrate that transformers excel in prediction quality, whereas reservoir computers remain highly efficient, substantially reducing training and inference times. Furthermore, we investigate two types of reservoir computing: a traditional reservoir with a static linear readout and an attention-enhanced reservoir that dynamically adapts its output weights through an attention mechanism. Our findings illustrate how these paradigms scale and provide guidelines for balancing resource constraints with performance.