We theoretically explore a dynamical generalization of the Aubry-André model in two dimensions formed by superimposing two square-lattice potentials. Motivated by the rich physics emerging at different twist angles between the two lattices at equilibrium, we introduce periodic twisting by continuously rotating one of the lattices with respect to the other in the plane. We demonstrate that the distinct time-dependent twisting in this system gives rise to an intricate form of periodic multifrequency driving that changes with the distance from the rotation axis. We find that the incommensurate nature of the potential no longer plays the pivotal role as it does in the static case. Rather, the tunneling can be understood in terms of a local, spatially varying dynamical localization effect, which we show to yield ring-shaped states localized within the bulk that have interesting transport signatures. Quantifying the eigenstates with the Bott index and local Chern marker, we find that there is a zoo of states with nontrivial topological signatures, the most ubiquitous of which result in relatively uniform ring-shaped regions of the Chern marker. We investigate the origin of these effects from various angles and identify that hybridization between different delocalized ring states plays a vital role. Finally, we discuss possible experimental realizations in quantum simulation settings. Our results open an avenue of investigation with periodic twisting inducing a spatially varying multifrequency drive.

We explore the correlated dynamics underlying the formation of the quantum Peregrine soliton, a prototypical rogue-wave excitation, utilizing interaction quenches from repulsive to attractive couplings in an ultracold bosonic gas confined in a one-dimensional box trap. The latter emulates the so-called semiclassical initial conditions and the associated gradient catastrophe scenario facilitating the emergence of a high-density, doubly localized waveform. The ensuing multiorbital variant of the Peregrine soliton features notable deviations from its mean-field sibling, including a reduced peak amplitude, wider core, absence of the side density dips, and earlier formation times. Moreover, Peregrine soliton generation yields coherence losses, while experiencing two-body bunching within each of its sides, which show anti-bunching between each other. Controllable seeding of the Peregrine soliton is also demonstrated by tuning the atom number or the box length, while reducing the latter favors the generation of the time-periodic Kuznetsov-Ma breather. Our results highlight that correlations reshape the morphology of rogue waves in the genuinely quantum, nonintegrable realm, while setting the stage for the emergent field of quantum dispersive hydrodynamics.

Random ensembles of pure states have proven to be extremely important in various aspects of quantum physics such as benchmarking the performance of quantum circuits, testing for quantum advantage, studying many-body thermalization, and the black hole information paradox. Although generating a truly random quantum ensemble is experimentally challenging, approximate realizations are equally valuable and are known to emerge naturally in a variety of physical models, including Rydberg setups. These are referred to as approximate quantum state designs, and verifying their degree of randomness can be a measurement-intensive task, similar to performing full quantum state tomography on many-body systems. In this theoretical work, we present a measurement scheme and analysis techniques to validate the degree of randomness of a quantum ensemble generated by a simulated experimental setup. This is achieved by translating the information residing in the complex many-body state into a succinct representation of classical data using projective measurements in randomly chosen bases, which is then processed using methods of statistical inference such as maximum-likelihood estimation and neural networks, benchmarked against the predictions of shadow tomography. Our scheme only requires individually addressed single-qubit operations to be performed in order to be employed, making it applicable for a range of physical platforms.

We study the dynamics of light interacting with a near-resonant atomic medium using the truncated Wigner and positive $P$ phase-space representations. By mapping the atomic degrees of freedom via the Jordan-Schwinger transformation, we first analyze the system under unitary evolution before extending the treatment to include an optical reservoir. While both methods capture the main features of the light-matter dynamics, our results demonstrate that the truncated Wigner approximation deviates significantly at higher interaction strengths and in regimes where reservoir-induced noise is prominent.

We investigate the Lotka-Volterra model for predator-prey competition with a finite carrying capacity that varies periodically in time, modeling seasonal variations in nutrients or food resources. In the absence of time variability, the ordinary differential equations have an equilibrium point that represents coexisting predators and prey. The time dependence removes this equilibrium solution, but the equilibrium point is restored by allowing the predation rate also to vary in time. This equilibrium can undergo a parametric resonance instability, leading to subharmonic and harmonic time-periodic behavior, which persists even when the predation rate is constant. We also find period-doubling bifurcations and chaotic dynamics. If we allow the population densities to vary in space as well as time, introducing diffusion into the model, we find that variations in space diffuse away when the underlying dynamics is periodic in time, but spatiotemporal structure persists when the underlying dynamics is chaotic. We interpret this as a competition between diffusion, which makes the population densities homogeneous in space, and chaos, where sensitive dependence on initial conditions leads to different locations in space following different trajectories in time. Patterns and spatial structure are known to enhance resilience in ecosystems, suggesting that chaotic time-dependent dynamics arising from seasonal variations in carrying capacity and leading to spatial structure might also enhance resilience.

Multiswarm systems, where two or more swarms of mobile agents occupy the same region of space with different parameters and goals, occur in a variety of biological, engineering, and defense applications. Composites of multiple swarms can produce hybrid spatiotemporal patterns, which compared to single swarming systems, are relatively unexplored. In this work, we develop a framework for studying the collision of countermoving swarms, each with its own preferred, stable velocity before collision. We show that redirection of such swarms after collision occurs when a stable velocity synchronized state of the multiswarm composite exists. Using a rigid-body approximation, we are able to extract how scatter-redirection transitions scale with swarm parameters in a variety of scenarios from reciprocal and nonreciprocal systems to symmetric and antagonistic parameter values. Our results compare well to simulations of both particle modeled agents and wheeled robots.

The statistics of fluctuations on large regions of space encodes universal properties of many-body systems. At equilibrium, it is described by thermodynamics. However, away from equilibrium such as after quantum quenches, the fundamental principles are more nebulous. In particular, although exact results have been conjectured in integrable models, a correct understanding of the physics is largely missing. In this paper, we explain these principles, taking the example of the number of particles lying on a large interval in one-dimensional interacting systems. These are based on simple hydrodynamic arguments from the theory of ballistically transported fluctuations, and, in particular, the Euler-scale transport of long-range correlations. Using these principles, we obtain the full counting statistics in terms of thermodynamic and hydrodynamic quantities, whose validity depends on the structure of hydrodynamic modes and on the fluctuations in the initial state. In fermionic-statistics interacting integrable models with a continuum of hydrodynamic modes, such as the Lieb-Liniger model for cold atomic gases, the formula reproduces previous conjectures, but is in fact not exact: It gives the correct cumulants up to, including, order 5, while long-range correlations modify higher cumulants. In integrable and nonintegrable models with two or less hydrodynamic modes, the formula is expected to give all cumulants.

During slow-wave sleep, the brain produces traveling waves of slow oscillations (SOs; $\le 2\text{Hz}$), characterized by the propagation of alternating high- and low-activity states. They play a crucial role in memory consolidation and are frequently investigated, empirically and with the support of in silico studies. The question of internal mechanisms that modulate traveling waves of SOs is still unanswered even though it is established that it is an adaptation mechanism that mediates them. One of the main mechanisms investigated is spike-frequency adaptation, a hyperpolarizing feedback current that is activated during periods of high activity. An alternative mechanism that has recently been suggested is based on hyperpolarization-activated (h-)currents, which are positive feedback currents that are activated in low-activity states. Both adaptation mechanisms were shown to feature SO-like dynamics in neuronal populations, and the inclusion of a spatial domain seems to enhance observable differences in their effects. To investigate the effects of both adaptation mechanisms on the neural dynamics in detail, we examine a spatially extended, adaptive Wilson-Cowan model of interacting excitatory and inhibitory populations of neurons with local spatial coupling. The excitatory populations are equipped with either one or the other adaptation mechanism. We describe both mechanisms using the same dynamical equation and include the inverse mode of action by changing the signs of the adaptation strength and the gain of activation function. We then show that the dynamical systems including the two feedback currents are mathematically equivalent under a compensatory external input, which depends on the adaptation strength and which in turn leads to a shift in state space of the otherwise equivalent bifurcation structure. A detailed analysis of state space shows that strong enough adaptation is required to induce traveling waves of SO-like dynamics, while only stationary or homogeneous activity patterns emerge if adaptation is weak. Additionally, adaptation modulates the properties of the spatiotemporal activity patterns, such as temporal frequencies, spatial frequencies, and the speed of the traveling waves, all of which increase with increasing strength. Though being dynamically equivalent, our results also explain why location-dependent variations in feedback strength cause differences in the propagation of traveling waves between both adaptation mechanisms.

Noise affecting qubit preparation and measurements accounts for a significant fraction of errors in quantum information processing. This is especially critical in tasks like variational quantum algorithms, quantum error correction, and entanglement distribution through repeaters. In this work, we present a protocol to purify noisy state preparation and measurement (SPAM), effectively suppressing these errors to an arbitrarily low level. For instance, in a realistic scenario where qubits contain error rates around 0.05 in both preparation and measurement, the protocol can suppress error rates up to ${10}^{-3}$ with two ancillas and ${10}^{-6}$ with four ancillas. We show how to distill error-free SPAM by repeating noisy SPAMs. The protocol is also feasible with superconducting qubits. We envisage that our results can be used to realize quantum information tasks in computing and communication with negligible SPAM errors.

Experiments using high-power lasers and relativistic electron beams will soon be capable of precision testing of the theory of strong-field quantum electrodynamics. The comparison between experiment and theory always occurs via numerical simulations, but the lack of quantitative uncertainty bounds for the latter means that the origin of any discrepancies cannot be identified conclusively. Here, I present a simulation framework that can place meaningful bounds on the theory uncertainties inherent to its operation. This work shows that the use of the locally constant field approximation leads to a theory uncertainty of a few percent in the signals of quantum radiation reaction expected in near-term experiments.

We demonstrate the modulation of high-energy electrons using a nanosized pore in solid as a strong electrostatic lens. The inner Coulomb potential of matter decreases rapidly from the edge of the pore toward the center, creating a strong electric field on the order of 10 GV/m. This electric field strongly modulates the phase of the incident electron beam and deflects the beam as a defocusing lens. We measure the strength of the electric field by combining electron holography with quantitative scanning transmission electron microscopy. We also observe changes in the transmitted probe through the nanopore using electron confocal imaging. The shrinking electron Airy patterns on the detector plane indicate that the exit probe's convergent angle increases under the deflection of the nanolens. This behavior corresponds to an effective concave lensing effect that cannot be achieved with rotationally symmetric electromagnetic fields in vacuum due to fundamental constraints imposed by the governing field equation. This demonstration of electron matter lensing shows the potential to manipulate high-energy electrons at the nanometer scale, expanding conventional electromagnetic lensing into nanoelectron optics.

Time delay can have a significant impact on the properties of collective organization of active matter. In the previous paper [Phys. Rev. E 109, 014205 (2024)], we discussed delay-induced breathing in a system of swarmalators—a model coupling particles’ internal phases to spatial interactions. Here, we build on that study to investigate the aging phenomenon in this system. It is the aging of a two-dimensional crystal with defects and inhomogeneous lattice constants and takes place after the breathing transients subside. We show that aging proceeds through the gradual elimination of fivefold and sevenfold coordination number defects, which merge pairwise or migrate to the cluster boundary, incrementally increasing the hexatic order parameter in the bulk. Despite this process, defects usually do not fully disappear; some residual number of defects remain frozen in the interior. However, we found that it is possible to achieve a nearly total elimination of coordination number defects at sufficiently low delay—when the surface of the cluster develops a sufficeintly thick fluidized “boiling layer.” This mechanism of boundary-mediated annealing reveals a nonequilibrium pathway to achieving high crystalline order in the bulk and raises a tantalizing possibility for controlling defects in active matter with free boundaries.

Pattern-forming dynamics govern the behavior of many quantum, electrochemical, and soft-matter systems, yet learning and controlling the corresponding partial differential equation (PDE) models on realistic geometries remains challenging. In this work, we develop a unified, differentiable framework for free-energy-based PDEs that enables end-to-end parameter inference and optimal control directly on image-based domains. Starting from a variational description in terms of an energy or free energy functional, we combine PDE-based smoothing of segmented geometries, the smoothed boundary method, advanced integrators for stiff pattern-forming PDEs, and memory-efficient automatic differentiation implemented in JAX to construct scalable PDE solvers amenable to gradient-based optimization. We demonstrate the capabilities of this framework across four classes of applications: (1) learning Cahn-Hilliard and Allen-Cahn free energies and kinetic laws from noisy spatiotemporal data on complex battery electrode microstructures; (2) designing time-dependent wetting boundary conditions that steer phase boundaries to desired orientations; (3) optimizing spatially varying reaction rates, interpreted as surface coatings, to suppress phase separation in intercalation electrode models; and (4) computing time-dependent trapping potentials that transfer Bose-Einstein condensates between ground states of qualitatively different Gross-Pitaevskii potentials while minimizing excitations. Together, these results show that variational PDE models, when equipped with differentiable solvers on complex domains, provide a versatile substrate for data-driven discovery, design, and control of pattern-forming materials and quantum fluids, and they point toward tighter integration of physics-based PDE modeling with modern optimization and machine learning pipelines.

We demonstrate strong coupling in a solid-state hybrid quantum system comprising a fixed-frequency coplanar-waveguide resonator, a superconducting transmon qubit, and an ensemble of nitrogen-vacancy centers in diamond. Frequency-domain spectroscopy reveals a characteristic three-mode avoided crossing, consistent with excitations being distributed across all three subsystems through hybridized eigenmodes. At higher probe powers, we observe nonlinear features and signatures of transmon-${}^{14}\mathrm{N}$ nuclear-spin interactions, highlighting the accessibility of higher-excitation manifolds in this architecture. These results establish an experimentally accessible regime of hybrid cavity QED that integrates superconducting and spin degrees of freedom, providing a platform for exploring complex multicomponent dynamics and developing hybrid quantum interfaces.

Stimulated Raman scattering (SRS) plays a crucial role in the energy conversion process from lasers to plasmas in the subrelativistic regime, where laser intensities range around ${10}^{15–16}{\text{W/cm}}^2$. SRS induces excitations of Langmuir waves (LWs) and density fluctuations, such as plasma density cavities. These excitations modify laser absorption in underdense plasma regions and subsequently generate suprathermal hot electrons (HEs) that transport laser energy into overdense plasma regions, changing plasma dynamics, including shock wave formation and propagation. In this paper, we report saturations of SRS-induced HE generation within tens of picoseconds under continuous laser irradiation and a mechanism for HE generation driven by a stochastic process. One-dimensional particle-in-cell simulations with a large density-scale plasma ($\sim {10}^2\mu \mathrm{m}$) over durations of up to $100\mathrm{ps}$ reveal the clear transition of the electron acceleration mechanism from previously reported electron trapping by SRS-excited LWs to a stochastic acceleration that produces fast electrons with mean energies greater than $100\mathrm{keV}$ as a result of random walks in fluctuating electric fields generated by SRS-induced density perturbations.

We propose a flow-matching Markov chain Monte Carlo (FM-MCMC) algorithm for estimating the orbital parameters of exoplanetary systems, especially for those in which only one exoplanet is involved. Compared to traditional methods that rely on random sampling within the Bayesian framework, our approach first leverages flow-matching posterior estimation to efficiently constrain the prior range of physical parameters and then employs MCMC to accurately infer the posterior distribution. For example, in the orbital parameter inference of $\beta$ Pictoris b, our model achieved a substantial speedup while maintaining comparable accuracy—running 77.8 times faster than parallel tempered MCMC and 365.4 times faster than nested sampling. Moreover, our FM-MCMC method also attained the highest average log-likelihood among all approaches, demonstrating its superior sampling efficiency and accuracy. This highlights the scalability and efficiency of our approach, making it well suited for processing the massive datasets expected from future exoplanet surveys. Beyond astrophysics, our methodology establishes a versatile paradigm for synergizing deep generative models with traditional sampling, which can be adopted to tackle complex inference problems in other fields, such as cosmology, biomedical imaging, and particle physics.

We propose a robust platform for simulating chiral quantum magnetism using linear arrays of trapped asymmetric-top molecules, specifically 1,2-propanediol (${\mathrm{C}}_3{\mathrm{H}}_8{\mathrm{O}}_2$). By mapping the Stark-dressed rotational states onto an effective spin-$1/2$ subspace, we rigorously derive a generalized $XXZ$ Heisenberg Hamiltonian governing the underlying many-body dynamics. Unlike standard solid-state models where the topological Dzyaloshinskii-Moriya interaction (DMI) is introduced phenomenologically, we demonstrate that DMI emerges ab initio from the molecular stereochemistry. Specifically, the interference between the transition dipole moments of heterochiral enantiomer pairs (left- and right-handed), which breaks inversion symmetry, generates a tunable DMI that stabilizes a chiral Luttinger liquid phase. Through a comprehensive phase-diagram analysis, we identify an optimal experimental regime characterized by intermolecular separations of $r\approx 1.5\mathrm{nm}$ and intermediate electric-field strengths $d\varepsilon /B\approx 2.5$. In this window, the system is protected from trivial field-polarized phases and exhibits a robust gapless spin-spiral texture. Our results establish 1,2-propanediol arrays as a versatile quantum simulator, providing a direct microscopic link between molecular chirality and topological many-body phases.

We develop a microscopic description of the fluctuation-mediated Casimir-Polder (CP) shifts on a “test” two-level atom placed near a two-dimensional atomic array of two-level atoms. We derive the resonant and off-resonant CP potentials experienced by the excited test atom using fourth-order perturbation theory, under the assumption that the test atom resonance is far detuned from those of the array atoms. The total potential on the test atom can be described as the sum of the pairwise resonant and off-resonant potentials resulting from its interaction with the individual atoms of the array. We analyze the asymptotic scaling of CP shifts as a function of the test atom-array separation, and its dependence on various system parameters: array spacing and size, and dipole orientation of the array atoms. Our results bridge the description of CP potential across two distinct regimes: from (1) a single-atom limit, where we recover the well-known two-atom van der Waals potential, to (2) a macroscopic boundary limit, where we demonstrate unconventional asymptotic scaling laws. We demonstrate that these scaling laws can be tuned via the microscopic parameters of the atomic array, establishing atomically controlled arrays as a versatile platform for tailoring fluctuation-induced quantum electrodynamics phenomena.