Traditional fixed-sign coupling schemes impose rigid directional constraints on interaction pathways, while integer-order differential models inherently lack the capacity to describe memory effects and long-range temporal correlations. To overcome these limitations, here we establish a fractional-order coupled Van der Pol oscillator system with a rotation parameter to investigate how the rotation parameter and fractional-order derivative control the dynamics. The rotation parameter distributes the coupling to the $x$ and $y$ variables via trigonometric functions, precisely regulating the sign and weight of coupling in each direction; this governs bifurcations and qualitatively determines the steady-state mode. Moreover, the memory effect of the fractional-order derivative exhibits quadrant dependence: As the fractional-order derivative decreases, the rotation parameter delays amplitude death in the second and third quadrants but accelerates incoherent oscillation death in the fourth quadrant. Finally, employing phase reduction theory, we derive the phase model and numerically verify the system’s transition path. Our findings break away from traditional frameworks, deepen the understanding of fractional-order coupled systems, elucidate the regulatory mechanisms of rotation parameters, and provide a theoretical foundation for controlling synchronization, chimera states, and death states in real-world systems.

Thermal counterflow of superfluid ${}^4\mathrm{He}$ past a cylinder produces quasisteady eddies not only downstream but also anomalously upstream. However, the mechanism and organizing principles behind the observed multistable wake topologies (zero-, two-, four-, and six-vortex states) have remained unclear. We show that the full spectrum of reported normal-fluid wake states is captured numerically with a two-fluid model coupled to Vinen’s vortex-line-density equation. Our simulations further reveal that the superfluid component can also develop anomalous upstream eddies, a feature not previously reported. We trace these behaviors to a self-organized zone of enhanced mutual-friction dissipation near the cylinder shoulders that reshapes the effective obstacle, drives upstream eddies in both components, and suppresses intrinsic wake oscillations in the normal fluid. Guided by this mechanism, we perform systematic parameter scans and construct a unified phase diagram in terms of the normal-fluid Reynolds number ${\text{Re}}_n$ and a dimensionless interaction number $N$, separating inertia- and mutual-friction-controlled transitions and delineating the parameter windows for the discrete wake topologies. These results turn a striking phenomenology into a predictive map and establish mutual-friction feedback as a robust route to unusual wake structures in quantum fluids.

The transport and localization of quantum droplets in time-dependent periodic disorder potentials are systematically studied. Our numerical results indicate that such exquisite periodically driven structures may support quantum phases that are principally different compared to static systems. We observe an intriguing anomalous diffusion, with a diffusion exponent depending on the strength of quantum fluctuations and on noise parameters (amplitude and frequency). We show that the interplay of quantum fluctuations and noise tends to suppress localization especially in a large droplet, while the transport is subdiffusive in a small droplet only for a very weak noise. For reducing modulation strength and at fixed dephasing time, the system may exhibit Anderson localization of the Floquet states in the small droplet. We also elucidate the role of thermal effects in the transport properties of quantum droplets. The obtained anomalous diffusion is justified in the frame of a heuristic model.

We apply machine learning methods to demonstrate radar range superresolution using a denoising autoencoder trained without supervision. Focusing on the estimation of a single physical parameter, the separation between two scatterers in the subwavelength regime, we constrain the network to a one-dimensional bottleneck layer with its size matched to the parameter dimensionality. We find that the bottleneck layer forms a reproducible, monotonic mapping with the true separation, showing that the network learns a low-dimensional representation directly aligned with the underlying physical parameter. We further show that this representation preserves the Fisher information of the signal, indicating that the network recovers a physically meaningful representation for parameter estimation. We investigate the behavior of the bottleneck layer for the following types of pulses: a traditional sinc pulse, a bandlimited triangle-type pulse, and a theoretically near-optimal pulse created from a spherical Bessel function basis. Our results demonstrate that neural networks can discover physically meaningful compressed representations without explicit supervision, with performance ultimately governed by the information content of the signal.

Turing patterns are a central paradigm for describing spatial patterns in nature. The corresponding theory of reaction-diffusion dynamics combines ideal diffusion with nonlinear reactions, resulting in patterns when species diffuse at different rates and reactions are sufficiently nonlinear. However, real systems are more complex and particularly involve physical interactions between constituents. While such interactions can promote patterns, we here show that they can also induce persistent spatiotemporal patterns. These patterns exhibit well-defined length and timescales, which result from cycles of droplet coarsening and fission. The dynamical patterns combine properties of traditional Turing patterns and chemically active droplets, which emerge for strong physical interactions. Our analysis thus reveals three qualitatively different regimes that emerge when two components interact physically and undergo nonlinear reactions.

Topological defects are a conspicuous feature of active liquid crystals that have been associated with important morphogenetic transitions in organismal development. Robust development thus requires a tight control of the motion and placement of topological defects. In this article, we study a mechanism to control $+1$ topological defects in an active polar fluid confined to a disk. If activity is localized in an annulus within the disk, the defect moves on a circular trajectory around the center of the disk. Using an ansatz for the polar field, we determine the dependence of the angular speed and the circle radius on the boundary orientation of the polar field and the active annulus. Using a proportional-integral controller, we guide the defect along complex trajectories by changing the active annulus size and the boundary orientation.

Preparation of nonclassical light with special quantum properties is essential for quantum technologies. High-harmonic generation (HHG) is a process that not only enables the creation of attosecond pulses but also has the potential to generate light with intricate quantum properties. In a recent experiment [PRX Quantum 5, 040319 (2024)], nonclassical interharmonic correlations have been measured from an HHG source between low-order harmonics. In this work, we theoretically investigate entanglement between different harmonics within an effective, phenomenological quantum optical model. This model implements a significant degree of simplification regarding the processes within the target material, treating the material through susceptibilities, as it is usual in quantum optics. Such an approach yields a general description of HHG in the few-harmonic generation regime, permitting the implications that can be derived within it to hold broadly within the domain of validity. We find that entanglement is produced as a result of the often neglected backaction. We can qualitatively reproduce experimentally measured nonclassicalities, which suggests that intermodal entanglement can, to an extent, be considered a universal phenomenon associated with HHG, rather than a result of using specific material targets.

We investigate the generation of genuine tripartite entanglement in a triangular spin-qubit system due to spatially correlated noise. In particular, we demonstrate how the formation of a highly entangled dark state, a $W$ state, enables robust, long-lived tripartite entanglement. Surprisingly, we find that environmentally induced coherent coupling does not play a crucial role in sustaining this entanglement. This contrasts sharply with the two-qubit case, where the induced coupling significantly influences the entanglement dynamics. Furthermore, we explore two promising approaches to enhance the tripartite entanglement by steering the system toward the dark state: postselection and coherent driving. Our findings offer a robust method for generating high-fidelity tripartite entangled states with potential applications in quantum computation.

We address the problem of how to prepare single-spinon wave functions, relevant for one-dimensional $S=1/2$ spin models, in a quantum computer. We adopt the recently proposed ansatz [Kulka et al., Phys. Rev. Lett. 134, 236504 (2025)] for the single-spinon wave function, where a state with $S=1/2$ is built in a spin chain with $L+1$ sites, adding a site with $S_z=1/2$ to the configurations of the ground-state wave function for the spin chain with length $L$. We extend the original work to the case of the Haldane-Shastry model. We discuss how to prepare the single-spinon ansatz for both the Heisenberg and Haldane-Shastry models in quantum computers, using a linear combination of unitaries. We consider three different strategies to compute the single-spinon energy in a quantum computer, we analyze their cost in terms of the number of qubits, gates, and circuits, and we test them in silico.

The observation of pressure-induced superconductivity in two- and three-layer Ruddlesden-Popper nickelates has spurred intense interest in these materials as a platform for exploring unconventional superconductivity. While the ground state of these systems has been shown to exhibit magnetism, the direct determination of their magnetic structure remains elusive. This is a crucial aspect, as magnetism may play a role in the pairing mechanism of superconductivity in these materials. In this study, we resolve the magnetic structures in the bilayer (2222) polymorphs of ${\mathrm{La}}_3{\mathrm{Ni}}_2{\mathrm{O}}_7$ and ${\mathrm{La}}_2{\mathrm{PrNi}}_2{\mathrm{O}}_7$ compounds, using a combination of complementary techniques, namely, neutron powder diffraction and muon-spin rotation/relaxation ($\mu \mathrm{SR}$). Magnetic neutron scattering in both samples emerges below $\sim 150$ K and is observed at the ($q_x,\frac{1}{2},0$) position, with $q_x=0$ and $\frac{1}{2}$ for ${\mathrm{La}}_3{\mathrm{Ni}}_2{\mathrm{O}}_7$ and $q_x=0$ for ${\mathrm{La}}_2{\mathrm{PrNi}}_2{\mathrm{O}}_7$. Alternating low-magnetic-moment (0.05–$0.075{\mu }_{\text{B}}$) and high-magnetic-moment ($0.66{\mu }_{\text{B}}$) stripes form a single layer; the bilayers are formed through antiferromagnetic stacking of single layers along the out-of-plane direction. The magnetic scattering with two propagation vectors $q_x=0$ and $\frac{1}{2}$ in the undoped ${\mathrm{La}}_3{\mathrm{Ni}}_2{\mathrm{O}}_7$ is attributed to two magnetic stacking polymorphs within a single crystallographic phase. The magnetic structures are substantiated by the $\mu \mathrm{SR}$ spectra. These findings provide a detailed understanding of the magnetic ground state in bilayer nickelates, offering crucial insights into the possible precursor states that may influence the emergence of superconductivity in these materials.

Hyperspectral photoluminescence maps of moiré transition-metal dichalcogenide heterobilayers encode rich information about the underlying disorder, but extracting it is hampered by the ambiguity of assigning individual spectral peaks. We show that the spatial correlations among a set of simple, peak-decomposition-free spectral descriptors—such as the centroid energy, the dominant-peak energy, and a sharp-line fraction—provide a peak-decomposition-free route to infer features of that disorder. Different descriptors act as filters that select different components of a multiscale disorder landscape—a smooth, micron-correlated background and a dense set of localized traps—and therefore acquire different spatial correlation lengths. The central prediction is a correlation-length hierarchy, $\xi \left(E_{\mathrm{cent}}\right)\ge \xi \left(E_{\mathrm{dom}}\right)$, which we derive by splitting the dominant-peak energy into a smooth background part and a short-range trap-switching fluctuation. The same picture explains the measured interdescriptor correlations, including the near-perfect anticorrelation ${\rho }_{\mathrm{S}}(\mathrm{\Delta }{E}_{\mathrm{cd}},R_{\mathrm{HL}})\approx -0.978$, which we show to be a robust geometric trend for spectra dominated by a common emission-envelope asymmetry. Benchmarked against phenomenological simulations, Hamiltonian diagonalization, and the measured ${\mathrm{MoSe}}_2/{\mathrm{WSe}}_2$ descriptor correlations, the framework turns descriptor maps into a quantitative, peak-decomposition-free probe of slow disorder and local traps in moiré excitons and, more broadly, in disordered semiconductor emitters.

The shortest path problem is related to many dynamic processes on networks, ranging from routing in communication networks to signaling in molecular interaction networks. When the network is fully known, the shortest path problem can be solved precisely and in polynomial time. If, however, the network of interest is only partially observable, the shortest path problem is no longer straightforward. Inspired by the shortest path problem in partially observable networks, we investigate the geometric properties of shortest paths in Euclidean soft random geometric graphs (SRGGs). We find that shortest paths are aligned along geodesic curves connecting shortest path end points. The strength of the shortest path alignment, as quantified by the average distance to geodesic from shortest path nodes and the average path stretch, is higher for larger SRGGs with short-range connections. In addition, we find that the strength of the shortest path alignment is nonmonotonic with respect to the average degree of the SRGG. Based on these observations, we establish the conditions under which the alignment of shortest paths may be sufficiently strong to allow the identification of shortest path nodes based on their proximity to geodesic curves. We show that in partially observable networks with uncertain node positions, our geometric approach can outperform network-based shortest path algorithms. In practical settings, our findings may have applications to navigation, wireless routing, and flow characterization in infrastructure networks.

Quantum reflection is usually described as an effectively one-dimensional phenomenon governed by motion along the surface normal. However, when translational symmetry is broken by sharp geometric features, scattering becomes intrinsically multidimensional. Here, we show that singular corners generate new geometric scaling laws for quantum reflection. In a minimal two-dimensional corner model with an attractive quadrant interaction, the reflected scattering width scales as ${\sigma }_{\mathrm{refl}}\propto E^{-2}$ in the intermediate Born regime, followed at lower energies by a crossover to the unitarity-limited threshold law ${\sigma }_{\mathrm{refl}}\propto E^{-1/2}$. The $E^{-2}$ exponent arises from two geometric ingredients: half-space support of the interaction and specular boundary-layer kinematics. More generally, for corner-supported potentials of the form $V(x,z)=W(x,z)\mathrm{\Theta }\left(x\right)\mathrm{\Theta }\left(z\right)$, we show that the Born exponent is universal under mild regularity assumptions. The leading coefficient is asymptotically determined by a specular boundary layer and depends only on the boundary trace $W(x,0)$, while microscopic details away from the boundary enter only through subleading structure. These results identify corners as the simplest surface singularities that support genuinely multidimensional geometric scaling laws, showing that geometry alone can control reflection across different energy regimes beyond the standard one-dimensional framework.

Ising machines, which are dynamical systems designed to operate in a parallel and iterative manner, have emerged as a paradigm for solving combinatorial optimization problems. Despite computational advantages, the quality of solutions depends heavily on the form of dynamics and tuning of parameters, which are, in general, set heuristically due to the lack of systematic insights. Here, we focus on optimal Ising machine design by analyzing phase diagrams of spin distributions in the Sherrington-Kirkpatrick model. We find that the ground state can be achieved in the phase where the spin distribution becomes binary, and optimal solutions are produced where the binary phase and gapless phase coexist. Our analysis shows that such coexistence phase region can be expanded by carefully placing a digitization operation, giving rise to a family of superior Ising machines, as illustrated by the proposed algorithm digCIM.

We show that a Bose-Hubbard model with local loss exhibits a first-order dark-state phase transition between a dark soliton and a uniform superfluid. Semiclassical simulations and stability analysis reveal that the soliton acts as a many-body dark state, whose suppressed fluctuations modify the transition relative to the comparable phenomenon of optical bistability in Kerr resonators. This mechanism quantitatively captures the bistable phase boundary observed in the experiment of Labouvie et al. [Phys. Rev. Lett. 116, 235302 (2016)], resolving long-standing discrepancies in previous theoretical modeling. Our results identify a general route by which spatial coherence and engineered loss can generate nonequilibrium phase transitions in ultracold gases.

We present a scheme to detect itinerant microwave radiation at the single photon level. Using existing Josephson-photonics devices, where two microwave cavities are coupled by a dc-voltage-biased superconducting junction, we theoretically show how to implement a stroboscopically repeated, near-projective measurement of a photon impinging on one of the cavities. Optimizing rate, duration, and strength of the measurement by flux control of the junction and developing a threshold protocol to detect the photon from a homodyne measurement of the radiation output of the other cavity, we achieve highly efficient detection with low dark counts. By cascading the detector with a preamplifier, where a similar two-cavity Josephson-photonics device acts as a photon multiplier, we can further improve the device to reach a detection efficiency of $88.5\%$ with a dark count rate of $\sim {10}^{-4}{\gamma }_a$, set by the resonance width ${\gamma }_a$ of the absorbing cavity. These results for a preamplification factor of 2 suggest that higher preamplification factors may yield near-unity efficiencies.

Time-resolved atom interferometry, as employed in applications such as gravitational-wave detection and searches for ultralight dark matter, requires precise control over systematic effects. In this work, we investigate phase noise arising from shot-to-shot fluctuations in the atoms’ transverse motion in the presence of the wavefront curvature of the interferometer beam, and analyze its dependence on the laser-beam geometry in long-baseline, large-momentum-transfer atom interferometers. We use a semiclassical framework to derive analytical expressions for the effective phase perturbation in position-averaged measurements and validate them using Monte Carlo simulations. Applied to 100 m and 1 km atom gradiometers representative of next-generation experiments, the model shows that configurations maximizing pulse efficiency also amplify curvature-induced phase noise, requiring micron-level control of the atom cloud's center-of-mass position and submicron-per-second control of its center-of-mass velocity to achieve sub-${10}^{-5}$ rad phase stability. Alternative beam geometries can suppress this noise by up to 2 orders of magnitude, but at the cost of reduced pulse efficiency. To address this limitation, we propose a mitigation strategy based on position-resolved phase-shift readout, which empirically learns and corrects the wavefront-induced bias from measurable quantities such as the phase-shift gradient and final cloud position. This approach restores high-sensitivity operation in the maximum-pulse-efficiency configuration without detailed beam characterization, providing a practical route toward next-generation, time-resolved atom interferometers operating at the ${10}^{-5}$ rad noise level.

Electroadhesion conventionally relies on kilovolt potentials to bridge macroscopic gaps in many practical applications. Here, we demonstrate that the governing length scale for strong electroadhesion is not the device-level separation but the nanoscale gap distribution imposed by surface roughness. By combining boundary-element rough-contact modeling with macroscopic friction measurements on oxidized silicon interfaces, we establish a quantitative framework that predicts adhesion pressures approaching 100 MPa at voltages below 30 V. Furthermore, we uncover a strong polarity-dependent asymmetry in adhesion and friction, which we attribute to charge trapping at grain boundaries. Our findings demonstrate that strong, low-voltage electroadhesion is viable and identify mechanisms through which undesired electroadhesion can be suppressed.

Nonlinear integrated optical devices that can realize threshold filtration of signals are in demand in photonics and optical computing. However, a list of requirements exists for such devices to make them practical. Here, to design a thresholder with the desired behavior, we suggest a mechanism that implements the property of resonators to provide extremely sharp (with respect to the wavelength) $\pi$ phase shifts near the critical coupling regime. By combining this feature with a nonlinear switching mechanism, one may obtain highly sensitive devices. Notably, the sharpness of the phase step in the considered case is independent of the quality factor of the resonators and the corresponding width of the resonances in transmittance. Instead, it is defined by the proximity to the critical coupling regime. Balancing near the critical coupling allows one to vary the sensitivity and achieve controllable smearing of the step function. The described effect is quite robust and can be realized for different materials and types of nonlinearity. The possibility of using sharp steps and low-quality resonators simultaneously provides multiple advantages for the resulting device. These include compact size, low manufacturing requirements, high operation speed, and low switching intensities. These sensitive and tunable phase thresholders may have multiple applications in optical computing. Few examples are provided, including a minimally invasive logic gate and a signal intensity classifier. In particular, the considered thresholders are useful in neuromorphic chips since they may act as optical neurons. In this paper, we provide an example of a photonic scheme that represents the behavior of a neuron and discuss its characteristics. Both the amplitude and phase of light are actively used in the scheme to store and update the state of a neuron.