We investigate the nature of the excitations captured by the dynamical response of XYZ triangular spin-1/2 ladders. We complement experimental inelastic neutron scattering results on the compound ${\mathrm{Cs}}_2{\mathrm{CoBr}}_4$ with numerically exact simulations based on time-dependent matrix product state methods. Our results show that bound states of spinon excitations can arise in XYZ beyond the requirement of strong Ising anisotropies. We analyze the role of the frustrated triangular couplings on the excitations giving rise to the spin dynamical structure factor and show how the features of the bound states manifest themselves in the different polarization channels.

Intermittency represents a fundamental route to chaos in nonlinear dynamical systems. In this work, we introduce an adaptive control strategy in which the control parameter of an intermittent system is promoted to a dynamical variable that evolves autonomously under an auxiliary nonlinear map drawn from the same functional hierarchy as the system itself. The construction eliminates the need for orbit identification, local linearization, and trajectory-triggered perturbations, which are central ingredients of conventional feedback schemes. The theoretical framework is developed within a class of one-dimensional nonlinear ergodic maps with exactly known invariant (Sinai-Ruelle-Bowen) measures, for which we derive in closed form (1) the dynamics and invariant measure of the evolving control parameter, (2) the invariant measure of the coupled system, and (3) the $q$-generalized Lyapunov exponents before and after control. The generalized Lyapunov spectrum serves as an analytical order parameter for the control process: The collapse of its positive regions provides a quantitative and initial-condition-independent signature of chaos suppression, and yields the sensitivity to initial conditions in explicit form. To establish the physical relevance of the approach beyond low-dimensional maps, we apply the same construction to a cluster of three interacting ultrasound-driven microbubbles described by the Keller-Herring model, promoting the experimentally accessible acoustic driving frequency to a dynamical variable. Systematic bifurcation and Lyapunov analyses, performed over wide ranges of driving pressure, frequency, and equilibrium radii, demonstrate that intermittent chaotic radial oscillations are progressively suppressed and replaced by stable periodic motion. These results establish intermittency regulation as a unifying and physically realizable mechanism for stabilizing complex nonlinear dynamics.

Recent experiments with rotating Bose gases have demonstrated the interaction-driven hydrodynamic instability of an initial extended striplike state in the lowest Landau level. We investigate this phenomenon in the low-density limit, where the mean-field Gross-Pitaevskii theory becomes inadequate, using exact diagonalization studies and analytic arguments. We show that the behavior can be understood in terms of weakly interacting repulsively bound few-body clusters. Signatures of cluster behavior are observed in the expectation values of observables that oscillate at frequencies characterized by the energies of few-body bound states. Using a semiclassical theory for interacting clusters, we predict the long-time growth of the cloud width to be a power law in the logarithm of time. This slow thermalization of bound clusters represents a form of quantum many-body scars.

Variational quantum algorithms (VQAs) aim at solving classical or quantum optimization problems by optimizing parametrized trial states on a quantum device, based on the outcomes of noisy projective measurements. The associated optimization process benefits from an accurate modeling of the cost function landscape using Gaussian process models (GPMs), whose performance is critically affected by the choice of their kernel. Here, we introduce specialized trigonometric kernels, inspired by the observation that typical VQA cost functions display oscillatory behavior with only few frequencies. Appropriate scores to benchmark the reliability of a GPM are defined, and a systematic comparison between different kernels is carried out on prototypical problems from quantum chemistry and combinatorial optimization. We further introduce RotoGP, a sequential line-search optimizer equipped with a GPM, and test how different kernels can help mitigate noise and improve optimization convergence. Overall, we observe that the trigonometric kernels show the best performance in most of the cases under study.

Schelling's model of segregation demonstrates that even in the absence of social or governmental interventions, individuals with mild in-group preferences can self-organize into strongly segregated neighborhoods. Many variants of this celebrated model have been proposed by assuming that agents tend to increase their satisfaction. Complementary to this traditional, utility-based approach, we model residential moves using satisfaction-independent reaction rates in a spatially extended chemical reaction network. The resulting model exhibits an emergent phenomenon: Despite symmetric in-group preferences, the system undergoes a tipping transition at a critical preference level, beyond which one agent type dominates. We characterize this asymmetric phase transition in details using mean-field analysis, numerical simulations, and finite-size-scaling methods. We find that while the transition shares key features with the Ising-universality class, such as ${\mathbb{Z}}_2$ symmetry breaking and similar exponent ratios, the full set of critical exponents does not match any known universality class.

We investigate collective search by self-propelled agents that are repelled by their own chemically produced trails, a minimal mechanism that simultaneously generates indirect interactions and memory. Using lattice and off-lattice models, we show that this mechanism enhances search efficiency through two distinct regimes. In a weak-memory regime, chemical cues are short-lived and interactions primarily promote spatial separation between agents. This reduces redundant exploration while preserving mobility, leading to an optimal trade-off between spatial order and persistence. In a strong-memory regime, long-lived chemical trails induce effective self-avoidance, strongly suppressing revisits and long search times. Here, optimal search occurs at finite memory strength: Permanently persistent trails lead to self-caging, while moderate memory enables efficient exploration. At higher densities, overlapping chemical trails give rise to a collective self-avoidance mechanism that yields substantial cooperative speedup without global spatial order. Together, these results show how chemically mediated memory and interactions can optimize collective search across distinct dynamical regimes.

We theoretically investigate the collisions between ultracold polar molecules in the presence of two lasers ensuring a Raman resonant transition on individual molecules to suppress photon scattering, taking the example of bosonic ${}^{23}\mathrm{Na}{}^{39}\mathrm{K}$ molecules. By varying laser detunings and intensities, we enable a repulsive long-range interaction potential between molecules. After solving a set of coupled Schrödinger equations with the Hamiltonian written in the basis of laser-dressed states of the molecule pair at infinite distance, we identify quasiresonant conditions under which elastic collisions are favored over inelastic and reactive ones, by a factor of about 2, thus demonstrating a promising pathway for efficient two-photon optical shielding of ultracold molecular collisions. The results are analyzed in terms of scattering length of the colliding laser-dressed molecules, which exhibit prominent resonances assigned to the interaction of the entrance channel with other specific channels, consistent with the existence of a quasibound level of the long-range molecular pair induced by the lasers.

In this work, we present a numerical and experimental investigation of the collective early-time decay rates of an optically dense cold atomic cloud supporting a large number of excitations. We prepare the atomic ensemble by driving the system to its steady state with varying Rabi frequencies $\mathrm{\Omega }$ that go from the low excitation $\mathrm{\Omega }\ll \mathrm{\Gamma }$ to the multiple excitation regime $\mathrm{\Omega }\gg \mathrm{\Gamma }$, where $\mathrm{\Gamma }$ is the single-atom decay rate. We investigate the early-time dynamics in the transition between the strong and weak driving regimes using (1) angular-dependent observables, such as the light emitted by the cloud, and (2) global observables, i.e., the excited-state population. When driving the cloud on resonance, we find that as a function of the driving frequency, the behavior of the collected light at certain angles transitions from the single-photon subradiant regime to a superradiant regime, while the behavior of the excited-state population does not show superradiance. The experiment shows good agreement with numerical predictions at the chosen angle of observation in the regime of parameters under study.

We study dynamical correlations of interacting hard-core anyons on a one-dimensional lattice at infinite temperature. This is a setting in which the many-body spectrum is independent of the statistical phase $\theta$, while dynamical correlators remain sensitive to $\theta$ through nonlocal Jordan-Wigner strings. We compute single-particle Green's functions, spectral functions, and density-density correlators, thereby separating the effects of fractional statistics on one-body coherence from those on density transport in a maximally mixed ensemble. In the noninteracting case $V=0$, high-temperature averaging leads to inversion-symmetric Green's functions for all $\theta$ despite the presence of anyonic strings. Finite nearest-neighbor interactions $V$ generate, however, a pronounced left-right asymmetry in the Green's functions for $0<\theta <\pi$, with the strongest chirality appearing at intermediate couplings $V\sim J$ where interactions and hopping compete most effectively. In this regime, the Green's function decays exponentially in time with a statistical-angle-dependent decay rate. At strong coupling, the dynamics crosses over to an atomic-limit regime in which the dependence on $\theta$ is reduced. Here, the Green's function decays universally as $t^{-1}$ and the corresponding spectral function displays a three-band structure. In contrast, density-density correlations are insensitive to statistics and recover the known infinite-temperature transport regimes of the XXZ chain, including ballistic, superdiffusive, and diffusive behaviors. These results identify dynamical correlation functions as direct probes of fractional statistics in high-entropy quantum systems.

We show that Andreev spin qubits can be realized in a Josephson junction based on the helical edge states of a two-dimensional topological insulator (quantum spin Hall system) proximized by superconducting films, in the presence of magnetic doping. We demonstrate that the electric dipole transitions between the Andreev spin states induced by the magnetic doping can be harnessed to manipulate the Andreev spin qubit by microwave radiation pulses, without applying an external Zeeman field or invoking ancillary states. We numerically simulate the realization of not and Hadamard quantum logic gates, and discuss implementations in realistic setups.

Powerful approaches to squeeze the motional state of a harmonic oscillator rely on the stepwise modulation of its resonance frequency. Such protocols can be limited by forces that vary slowly between experimental runs but are constant during a single experimental shot. Such shot-to-shot noise gives rise to a spread in experimental outcomes that masks the uncertainty intrinsic to quantum theory. Taking inspiration from spin-echo protocols, we propose a decoupling technique that, under ideal conditions, perfectly cancels shot-to-shot force noise in squeezing experiments based on parametric modulation. We implement the protocol using an optically levitated nanoparticle, where shot-to-shot force noise arises from slowly varying stray fields acting on the charge carried by the particle. Using our oscillator-echo protocol, we demonstrate shot-to-shot noise suppression to the measurement-backaction limit.

We report the discovery of a compound, ${\mathrm{Ce}}_3{\mathrm{MgBi}}_5$, and reveal the hidden time-reversal-like degenerate states within it. ${\mathrm{Ce}}_3{\mathrm{MgBi}}_5$ is an antiferromagnet with the distorted kagome lattice of Ce atoms, in which several fractional magnetization plateaus emerge with the increase of magnetic field. At the 1/2 magnetization plateau, obvious hysteresis has been observed in the magnetoresistance and Hall resistivity during the rise and fall of the magnetic field. However, hysteresis vanishes in the corresponding measurements of magnetization, indicating the existence of degenerate states with the same net magnetization but different electronic transport properties. The degenerate states can be connected by the time-reversal-like operation. In addition, by comparing with HoAgGe, it is suggested that the special crystal structure in ${\mathrm{Ce}}_3{\mathrm{MgBi}}_5$ may have a shielding effect on the time-reversal-like operation, thereby affecting the distinction of degenerate states. Our work establishes ${\mathrm{Ce}}_3{\mathrm{MgBi}}_5$ as an example of utilizing electronic transport properties to identify and distinguish hidden symmetries in frustrated magnetic systems.

Real-time decoding of quantum error correction is essential for enabling fault-tolerant quantum computation. A practical decoder must operate with high accuracy at low latency, while remaining robust to spatial and temporal variations in hardware noise. We introduce a hardware-conditioned neural decoder framework designed to exploit the natural separation of timescales in superconducting processors, where calibration drifts occur over hours while error correction requires microsecond-scale responses. By processing calibration data through a graph-based encoder and conditioning a lightweight convolutional backbone via featurewise linear modulation (FiLM), we decouple the heavy processing of device statistics from the low-latency syndrome decoding. We evaluate this approach using the repetition code as a test bed on IBM Fez, Kingston, and Pittsburgh processors, collecting over 2.7 million experimental shots spanning distances up to $d=11$. Training one decoder per code distance, basis, and round count $(d,r)$, we demonstrate that each trained model generalizes to unseen qubit chains and new calibration data acquired days later without retraining. The FiLM-conditioned decoder achieves up to a $11.1\times$ reduction in logical error rate relative to modified minimum-weight perfect matching. Cross-conditioning ablations further show that the calibration input actively improves decoding, with performance degrading when the decoder is conditioned on incorrect backend data or the conditioning is disabled. We observe that by employing a network architecture that exploits the highly asynchronous nature of system calibration and decoding, hardware-conditioned neural decoding demonstrated promising, adaptive performance with negligible latency overhead relative to unconditioned baselines.

Crosstalk between qubits fundamentally limits the scalability of quantum processors, necessitating physics-based models that can handle the complexity of large qubit arrays. Here, we develop a comprehensive theoretical and experimental framework that captures residual interactions between both adjacent and nonadjacent qubits in fixed-frequency transmon lattices. The model integrates the combined effects of exponential localization in banded capacitance matrices, suppression of virtual couplings through detuning products across intermediate modes, and evanescent decay of below-cutoff electromagnetic fields, yielding predictive scaling relations for coupling strength as a function of spatial separation and spectral detuning. Experimental characterization of a $4\times 4$ superconducting qubit lattice with inductive shunt pillars reveals exponential spatial decay and frequency-dependent suppression consistent with theoretical predictions, achieving quantitative agreement for all nearest-neighbor couplings across the $4–6\mathrm{GHz}$ operating range. Our results show that standard dispersive Hamiltonian approximations systematically overestimate long-range coupling when spatial and spectral dependencies are neglected; these errors propagate into circuit simulation and design strategies. Our framework provides design guidance for crosstalk mitigation in larger-scale quantum processors under realistic fabrication constraints, addressing a bottleneck in scalability.

Direct measurement of quantum non-Gaussianity requires some variant of a discrete photon-resolving detection, which is feasible only for low mean photon numbers. For a large mean photon number, intensity detection by linear photodiodes provides a continuous signal; therefore, the Fock probabilities of the unknown input state are not directly available. On the other hand, intensity moments can be measured directly, and photon-number moments can be estimated. Therefore, we derive and analyze a quantum non-Gaussianity witness based solely on the photon-number mean and variance (or alternatively, the second-order correlation $g^{\left(2\right)}$) of an unknown state. Due to the simplicity of the used photon-number moments, the measurement results are easy to correct for losses and additive noise. We provide examples of simple amplification-based measurement schemes where our witness can be applied directly, thereby opening pathways to proof-of-principle tests and applications.

Biological systems often combine intrinsic rotation with directional sensing and nonreciprocal interactions. However, the collective consequences of these combinations are poorly understood. Here, we extend a previously studied model of active Brownian particles with vision-mediated steering, polar alignment, and steric repulsion by adding intrinsic chirality, and examine how the additional rotational timescale introduced by intrinsic chirality reorganizes the resulting collective dynamics. We vary the alignment-to-vision maneuverability ratio, the vision angle, and the chirality to obtain dynamical state diagrams containing compact spinning clusters, vortices, ripple loops, wormlike swarms, and mobile rotary clusters. Intrinsic chirality alters the balance between vision-mediated cohesion and velocity alignment, giving rise to the observed rotary behavior. Large chirality suppresses collective organization, while moderate-to-low chirality stabilizes rotating and translating clusters. At moderate chirality, the model exhibits a ripple-loop morphology. We use both structural and dynamical measures like polarization, orientational correlations, solid-body spin, and mean squared displacement to distinguish the different regimes and the pathways between them.

Time-delayed oscillator networks underlie diverse biological and physical systems, yet standard first-order phase reductions fail to capture their high-dimensional collective dynamics. In this work, we develop a universal second-order predictive reduction for time-delayed Kuramoto-Daido networks that maps delayed one-dimensional phase dynamics to a delay-free network of two-dimensional rotators. Delay induces effective inertia and triadic interactions, yielding accurate predictions of nontrivial attractors and their collective-state statistics, including splay, cyclops, and chimera states. The reduction reveals a division of roles: Inertia organizes higher-dimensional dynamics, whereas triadic terms are crucial for lower-dimensional patterns such as chimeras. Applicable to arbitrary topology, higher harmonics, and intrinsic-frequency heterogeneity, it provides a compact, parameter-explicit reduced model. The same framework also extends to time-delayed amplitude-phase oscillator networks, including swarmalators, yielding analogous reduced equations with emergent inertia and triadic higher-order couplings. This unified and readily deployable description enables systematic prediction and analysis of delay-controlled collective dynamics across oscillator networks.

Optical thermodynamics is a recently developed framework that applies principles from statistical mechanics to describe the intricate behavior of weakly nonlinear, multimode photonic systems. Utilizing this theory, the collective dynamics of complex optical arrangements can be systematically uncovered and understood. The purpose of this work is to examine fundamental aspects of optical thermodynamics, including optical pressure, and provide a unified framework that can be applied effectively to any optical setting within the domain of validity of optical thermodynamics. We find that in addition to the conservation laws, the remaining extensive and intensive parameters of the system are naturally provided by the parameters of the propagation constants. At this point, several thermodynamic approaches exist for analyzing optical forces in multimode settings. Here, we develop a theoretical methodology that unifies these perspectives in a variety of different configurations, irrespective of whether they are discrete or continuous. We apply our theory in four different settings. By studying Su-Schrieffer-Heeger lattices, we elucidate the thermodynamics of polyatomic chains and show that intercell and intracell bonds can display different optical forces. In addition, we provide a thermodynamic formalism to predict and understand the optical pressure at equilibrium arising in arrangements characterized by a continuous index variation and apply our results to graded-index fibers.

In thermalizing many-body quantum systems without conservation laws, such as ergodic Floquet and random unitary circuits, local expectation values are predicted to decay to their equilibrium values exponentially quickly. In this work, we derive a relationship between said exponential decay rate $\overline{g}$ and the operator spreading properties of a local unitary evolution. A hydrodynamical picture for operator spreading allows us to argue that, for random unitary circuits, $\overline{g}$ is encoded by the leading eigenvalue of a dynamical map obtained by enriching unitary dynamics with dissipation, in the limit of weak dissipation. We argue that the size of the eigenvalue does not depend on the details of this weak dissipation (given mild assumptions on properties of the ergodic dynamics), so long as it only suppresses large operators significantly. Our calculations are based on analytical results for random unitary circuits, but we argue that similar results hold for ergodic Floquet systems. These conjectures are in accordance with existing results that numerically obtain quantum many-body analogs of classical Ruelle-Pollicott resonances [Prosen, J. Phys. A: Math. Gen. 35, L737 (2002); Mori, Phys. Rev. B 109, 064311 (2024)] by studying unitary evolutions subject to weak dissipation.