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.

Flat-band systems, where electron kinetic energy is quenched over large regions of momentum space, are predicted to host exotic strongly correlated phenomena. Kagome metals have emerged as a prominent platform for exploring intriguing flat-band physics. Yet, their intrinsic charge dynamics have remained obscured because flat bands in most kagome materials either are located far from the Fermi level $\left(E_{\mathrm{F}}\right)$ or coexist with other dispersive bands near the $E_{\mathrm{F}}$. Here, we report infrared spectroscopy measurements of the kagome metal ${\mathrm{CsCr}}_6{\mathrm{Sb}}_6$, which features isolated Cr-derived flat bands near the $E_{\mathrm{F}}$. The optical conductivity spectra ${\sigma }_1\left(\omega \right)$ exhibit a striking power-law behavior proportional to ${\omega }^{-\alpha }$ with α ≈ 0.26, significantly deviating from conventional metallic response, where the conductivity falls like ${\omega }^{-2}$. Above the frustrated magnetic state temperature $T_{\mathrm{F}}\approx 72\mathrm{K}$, the low-energy ${\sigma }_1\left(\omega \right)$ displays incoherent charge dynamics without a well-defined Drude response. Below $T_{\mathrm{F}}$, the low-energy ${\sigma }_1\left(\omega \right)$ is further suppressed, indicating electron scattering due to the magnetic frustration. Moreover, the spectral weight of ${\sigma }_1\left(\omega \right)$ is redistributed with varying temperature over broad energy scales (∼4 eV), reflecting strong correlation effects. These findings demonstrate that ${\mathrm{CsCr}}_6{\mathrm{Sb}}_6$ belongs to the correlated bad metallic systems, which have not been witnessed among other kagome metals.

Accurately solving the Schrödinger equation remains a central challenge in computational physics, chemistry, and materials science. Here, we propose an alternative eigenvalue problem based on a system's autocorrelation function, avoiding direct reference to a wave function. In particular, we develop a rigorous approximation framework that enables precise frequency estimation from a finite number of signal samples. Our analysis builds on results involving prolate spheroidal wave functions and yields error bounds that reveal a sharp accuracy transition governed by the observation time and spectral density of the signal. These results are very general and thus carry far. As one important example application, we consider the quantum computation for molecular systems. By combining our spectral method with a quantum subroutine for signal generation, we define quantum prolate diagonalization (QPD)—a hybrid classical-quantum algorithm. QPD simultaneously estimates ground- and excited-state energies within chemical accuracy at the Heisenberg limit. An analysis of different input states demonstrates the robustness of the method, showing that high precision can be retained even under imperfect state preparation.

Carriers in flat bands (FBs) possess high effective masses and are predicted to exhibit unconventional transport properties. The study of the photocarrier dynamics in FBs is of fundamental importance for understanding many-body interactions and the emergence of exotic quantum phenomena. $1\mathrm{T}\text{−}\mathrm{Ti}{\mathrm{S}}_2$, a layered transition-metal dichalcogenide featuring a quasiflat band near the Fermi level, provides an ideal platform for investigating nonequilibrium carrier dynamics in electronic flat-band systems. Here, we employed transient absorption microscopy to uncover a picosecond, quasi-flat-band-mediated bimolecular recombination of photoexcited electrons and holes confined within the flat-band states in the 80–295 K experimental window. In addition, the launch of coherent acoustic phonons in ${\mathrm{TiS}}_2$ crystals at 45 GHz is demonstrated, from which sound velocity and Young's modulus are determined to be 4.39 $\text{km}{\text{s}}^{-1}$ and 62 GPa, agreeing well with the prediction from the first-principles calculation. The present study provides microscopic insight into ultrafast energy relaxation and the associated phonon generation in layered materials.

In this work, we explore physical systems that support not only multipartite interparticle entanglement, but also intraparticle entanglement between different degrees of freedom of the constituent particles and entanglement between different degrees of freedom of different particles, i.e., algebraic entanglement. We derive a simple method for calculating the algebraic entanglement entropy between two of the particles’ degrees of freedom from collective states of the whole ensemble. Our procedure makes use of underlying symmetries in these systems, in particular, permutation symmetry of the particle indices, and shows a connection between the algebraic entanglement entropy in these systems and the irreducible representations of Lie groups which describe the particles’ degrees of freedom. Namely, we use the direct sum over irreducible representations to diagonalize the reduced density matrices in a block-by-block manner, and then utilize the multiplicity of these irreducible representations to reproduce the results from an exponentially scaled Hilbert space in only polynomial complexity. We use this to explore a variety of systems where the constituent particles support two degrees of freedom each with two levels, such as atoms with two electronic states and two momentum states. Notably, these systems may be exactly simulated in a polynomial-scaled Hilbert space, yet they support an algebraic entanglement entropy that grows linearly with the particle number, which typically requires an exponentially scaled Hilbert space.

Hierarchy is the architecture of complex systems. While Euclidean metric describes homogeneous and static systems, ultrametric geometry is for heterogeneous ensembles, hierarchic relations, and dynamic contexts. Applications spread across all fields: communication technologies, information retrieval, clusterwise regression, analysis, and synthesis of narratives and emotions. The paradigmatic model describing complex systems is the spin glass theory, according to which the topology of the many metastable energy states is intrinsically ultrametric, as a consequence of the breaking of their symmetry. Despite the importance, a real experimental observation of ultrametricity in spin glasses with a large number of spins has not yet been reported, due to the difficulty of finding a physical system in which the order parameter can be easily obtained from direct measurements. Random lasers have recently been proposed as excellent photonic counterparts of spin glasses with robust replica symmetry breaking features. Here, we report the ultrametric structure of the replica space with clustered domains in random lasers, as predicted in the Parisi ansatz. We show that the number of states forming isosceles triangles in the metric space increases through the laser threshold giving rise to the construction of a genealogical tree. Moreover, from the hierarchical topology of the states, we obtain a direct observation of the complex energy landscape with evident breaking of ergodicity in the glassy regime. These results mark a key advance in complexity science and invigorate current efforts to harness physical systems for the realization of optical computers and quantum optimization processors.

Nitrogen-rich compounds have emerged as promising candidates for high-energy-density applications owing to their superior energy content and environmental benignity, yet uncovering compounds that integrate high energy density with stability and persistence remains a significant scientific challenge. Building upon the synthesized all-single-bonded framework of Fdd2-${\mathrm{TaN}}_5$, we perform computational studies where the heaviest group-V element (Ta) was strategically substituted with its lightest congener (V), obtaining ${\mathrm{VN}}_5$—a novel compound that retains the original orthorhombic Fdd2 space group symmetry while exhibiting branched, all-single-bonded nitrogen chains. This compound exhibits a remarkable energy density ($E_d$) of 5.18 kJ/g, far exceeding that of ${\mathrm{TaN}}_5$ at 2.02 kJ/g. explo5 calculations reveal that its detonation velocity ($V_d$) and detonation pressure ($P_d$) reach 16.33 km/s and 187.4 GPa, all surpassing those of TNT. These exceptional characteristics make ${\mathrm{VN}}_5$ a highly competitive potential high-energy-density material.

Active and living matter exhibits a wide range of complex phenomena, including collective motion, pattern formation, and hierarchical structures. Collective motion in living systems is often quantified using spatial correlation functions; however, competing definitions—especially for velocity fields—yield inconsistent results across studies. Here, we clarify the distinction between “normalize-first” and “average-first” velocity correlations, and establish a robust and practical framework for computing correlation functions and extracting director and velocity correlation lengths, ${\xi }_d$ and ${\xi }_v$, respectively, from a wide range of active cell systems. Using synthetic shear and vortex fields and experimental datasets spanning epithelial monolayers, neural progenitors, and bacterial colonies, we demonstrate how noise and fitting choices affect inferred length scales, and provide recipes that yield consistent outcomes. Finally, we introduce two state diagrams—${\xi }_v$ versus ${\xi }_d$ and ${\xi }_v/{\xi }_d$ versus motility anisotropy—that locate systems within different dynamical regimes and track their trajectories during development. These tools standardize correlation analysis and link single-cell motility to emergent colony-scale flows, enabling rigorous, comparable measurements across living systems.