Human populations exhibit complex behaviors—characterized by long-range correlations and surges in activity—across a range of social, political, and technological contexts. Yet it remains unclear where these collective behaviors come from or if there even exists a set of unifying principles. Indeed, existing explanations typically rely on context-specific mechanisms, such as traffic jams driven by work schedules or spikes in online traffic induced by significant events. However, analogies with statistical mechanics suggest a more general mechanism: that collective patterns can emerge organically from fine-scale interactions within a population. Here, across four different modes of human activity, we show that the simplest correlations in a population—those between pairs of individuals—can yield accurate quantitative predictions for the large-scale behavior of the entire population. To quantify the minimal consequences of pairwise correlations, we employ the principle of maximum entropy, making our description equivalent to an Ising model whose interactions and external fields are notably calculated from past observations of population activity. In addition to providing accurate quantitative predictions, we show that the topology of learned Ising interactions resembles the network of interhuman communication within a population. Together, these results demonstrate that fine-scale correlations can be used to predict large-scale social behaviors, a perspective that has critical implications for modeling and resource allocation in human populations.

Qubits strongly coupled to a photonic crystal give rise to qubit-photon dressed bound states. These bound states, comprising the qubits and spatially localized photonic modes induced around the qubits, are the basis for many exotic physical scenarios. The localization of these states changes with qubit detuning from the photonic crystal band edge, offering an avenue of in situ control of bound-state interaction. Here, we present experimental results from a device with two transmon qubits coupled to a superconducting microwave photonic crystal and realize tunable on-site and interbound state interactions. We observe a fourth-order two-photon virtual process between bound states indicating strong coupling between the photonic crystal and transmon qubits. Because of their localization-dependent interaction, these states offer the ability to realize one-dimensional chains of bound states with tunable and potentially long-range interactions that preserve the qubits’ spatial organization. The widely tunable, strong, and robust interactions demonstrated with this system are promising benchmarks towards realizing larger, more complex systems that use bound states to build and study quantum spin models.

An algorithmically hard phase is described in a range of inference problems: Even if the signal can be reconstructed with a small error from an information-theoretic point of view, known algorithms fail unless the noise-to-signal ratio is sufficiently small. This hard phase is typically understood as a metastable branch of the dynamical evolution of message-passing algorithms. In this work, we study the metastable branch for a prototypical inference problem, the low-rank matrix factorization, that presents a hard phase. We show that, for noise-to-signal ratios that are below the information-theoretic threshold, the posterior measure is composed of an exponential number of metastable glassy states, and we compute their entropy, called the complexity. We show that this glassiness extends even slightly below the algorithmic threshold, below which the well-known approximate message-passing (AMP) algorithm is able to closely reconstruct the signal. Counterintuitively, we find that the performance of the AMP algorithm is not improved by taking into account the glassy nature of the hard phase. This result provides further evidence that the hard phase in inference problems is algorithmically impenetrable for some deep computational reasons that remain to be uncovered.

Time-dependent processes are often analyzed using the power spectral density (PSD) calculated by taking an appropriate Fourier transform of individual trajectories and finding the associated ensemble average. Frequently, the available experimental datasets are too small for such ensemble averages, and hence, it is of a great conceptual and practical importance to understand to which extent relevant information can be gained from $S(f,T)$, the PSD of a single trajectory. Here we focus on the behavior of this random, realization-dependent variable parametrized by frequency $f$ and observation time $T$, for a broad family of anomalous diffusions—fractional Brownian motion with Hurst index $H$—and derive exactly its probability density function. We show that $S(f,T)$ is proportional—up to a random numerical factor whose universal distribution we determine—to the ensemble-averaged PSD. For subdiffusion ($H<1/2$), we find that $S(f,T)\sim A/f^{2H+1}$ with random amplitude $A$. In sharp contrast, for superdiffusion $(H>1/2)$ $S(f,T)\sim B{T}^{2H-1}/f^2$ with random amplitude $B$. Remarkably, for $H>1/2$ the PSD exhibits the same frequency dependence as Brownian motion, a deceptive property that may lead to false conclusions when interpreting experimental data. Notably, for $H>1/2$ the PSD is ageing and is dependent on $T$. Our predictions for both sub- and superdiffusion are confirmed by experiments in live cells and in agarose hydrogels and by extensive simulations.

The quantum Monte Carlo (QMC) method is applied to obtain the fundamental (quasiparticle) electronic band gap ${\mathrm{\Delta }}_f$ of a semiconducting two-dimensional phosphorene whose optical and electronic properties fill the void between graphene and 2D transition-metal dichalcogenides. Similarly to other 2D materials, the electronic structure of phosphorene is strongly influenced by reduced screening, making it challenging to obtain reliable predictions by single-particle density-functional methods. Advanced $GW$ techniques, which include many-body effects as perturbative corrections, are hardly consistent with each other, predicting the band gap of phosphorene with a spread of almost 1 eV, from 1.6 to 2.4 eV. Our QMC results, from infinite periodic superlattices as well as from finite clusters, predict ${\mathrm{\Delta }}_f$ to be about 2.4 eV, indicating that available $GW$ results are systematically underestimating the gap. Using the recently uncovered universal scaling between the exciton binding energy and ${\mathrm{\Delta }}_f$, we predict the optical gap of about 1.7 eV that can be directly related to measurements even on encapsulated samples due to its robustness against dielectric environment. The QMC gaps are indeed consistent with recent experiments based on optical absorption and photoluminescence excitation spectroscopy. We also predict the cohesion of phosphorene to be only slightly smaller than that of the bulk crystal. Our investigations not only benchmark $GW$ methods and experiments, but also open the field of 2D electronic structure to computationally intensive but highly predictive QMC methods which include many-body effects such as electronic correlations and van der Waals interactions explicitly.

Recent research has led to the discovery of fundamental new phenomena in network synchronization, including chimera states, explosive synchronization, and asymmetry-induced synchronization. Each of these phenomena has thus far been observed only in systems designed to exhibit that one phenomenon, which raises the questions of whether they are mutually compatible and, if so, under what conditions they co-occur. Here, we introduce a class of remarkably simple oscillator networks that concurrently exhibit all of these phenomena. The dynamical units consist of pairs of nonidentical phase oscillators, which we refer to as Janus oscillators by analogy with Janus particles and the mythological figure from which their name is derived. In contrast to previous studies, these networks exhibit (i) explosive synchronization with identical oscillators; (ii) extreme multistability of chimera states, including traveling, intermittent, and bouncing chimeras; and (iii) asymmetry-induced synchronization in which synchronization is promoted by random oscillator heterogeneity. These networks also exhibit the previously unobserved possibility of inverted synchronization transitions, in which a transition to a more synchronous state is induced by a reduction rather than an increase in the coupling strength. These various phenomena are shown to emerge under rather parsimonious conditions and even in locally connected ring topologies, which has the potential to facilitate their use to control and manipulate synchronization in experiments.

We construct fixed point lattice models for group supercohomology symmetry-protected topological phases of fermions $(2+1)\mathrm{D}$. A key feature of our approach is to construct finite depth circuits of local unitaries that explicitly build the ground states from a tensor product state. We then recover the classification of fermionic symmetry-protected topological phases, including the group structure under stacking, from the algebraic composition rules of these circuits. Furthermore, we show that the circuits are symmetric, implying that the group supercohomology phases can be many-body localized. Our strategy involves first building an auxiliary bosonic model, and then fermionizing it using the duality of Chen, Kapustin, and Radicevic. One benefit of this approach is that it clearly disentangles the role of the algebraic group supercohomology data, which are used to build the auxiliary bosonic model, from that of the spin structure, which is combinatorially encoded in the lattice and enters only in the fermionization step. In particular this allows us to study our models on 2D spatial manifolds of any topology, and to define a lattice-level procedure for ungauging fermion parity.

Based on calorimetry and dielectric spectroscopy, the influence of dopants as well as H/D-isotope substitution on the dynamics and thermodynamics of expanded high-density amorphous ice (eHDA) is studied. We find that dopants do not significantly alter the phase behavior, the dielectric relaxation times, and the calorimetric glass transition of eHDA. These observations starkly contrast those made for crystalline ices such as ice $I_h$, ice V, ice VI, and ice XII, where suitable dopants enhance the dielectric dynamics by several orders of magnitude and can trigger hydrogen order-disorder transitions, then taking place below the orientational glass transition temperature of undoped samples. This conspicuous contrast to the behavior of crystalline ices strongly argues against point-defect dynamics in amorphous ices and against a previously suggested “crystallinelike” nature of the amorphous ices. Furthermore, H/D substitution also does not affect the calorimetric glass transition in eHDA much, whereas for crystalline ices, the heat capacity increase at the glass transition is roughly halved. In addition, the H/D-isotope shift of the glass transition onset is much larger for crystalline ices than it is for amorphous ices. This observation favors the notion of eHDA’s glass transition as a glass-to-liquid transition and is evidence against a mere molecular-reorientation unfreezing at water’s second glass transition. Comparing the isotope effect on activation energies for dielectric relaxation with ice V suggests that in amorphous ice water molecules move translationally above $T_g$. Thus, the present work strongly supports that above this glass transition, water does indeed exist in its contested high-density liquid state.

When an amorphous material is strained beyond the point of yielding, it enters a state of continual reconfiguration via dissipative, avalanchelike slip events that relieve built-up local stress. However, how the statistics of such events depend on local interactions among the constituent units remains debated. To address this we perform experiments on granular material in which we use particle shape to vary the interactions systematically. Granular material, confined under constant pressure boundary conditions, is uniaxially compressed while stress is measured and internal rearrangements are imaged with x rays. We introduce volatility, a quantity from economic theory, as a powerful new tool to quantify the magnitude of stress fluctuations, finding systematic, shape-dependent trends. In particular, packings of flatter, more oblate shapes exhibit more catastrophic plastic deformation events and thus higher volatility, while rounder and also prolate shapes produce lower volatility. For all 22 investigated shapes the magnitude $s$ of relaxation events is well fit by a truncated power-law distribution $P(s)\sim s^{-\tau }\exp (-s/s^{*})$, as has been proposed within the context of plasticity models. The power-law exponent $\tau$ for all shapes tested clusters around $\tau =1.5$, within experimental uncertainty covering the range 1.3–1.7. The shape independence of $\tau$ and its compatibility with mean-field models indicate that the granularity of the system, but not particle shape, modifies the stress redistribution after a slip event away from that of continuum elasticity. Meanwhile, the characteristic maximum event size $s^{*}$ changes by 2 orders of magnitude and tracks the shape dependence of volatility. Particle shape in granular materials is therefore a powerful new factor influencing the distance at which an amorphous system operates from scale-free criticality. These experimental results are not captured by current models and suggest a need to reexamine the mechanisms driving mesoscale plastic deformation in amorphous systems.

The difficulty of validating large-scale quantum devices, such as boson samplers, poses a major challenge for any research program that aims to show quantum advantages over classical hardware. Towards this aim, we propose a novel data-driven approach, wherein models are trained to identify common pathologies using unsupervised machine-learning methods. We illustrate this idea by training a classifier that exploits $K$-means clustering to distinguish between boson samplers that use indistinguishable photons from those that do not. We tune the model on numerical simulations of small-scale boson samplers and then validate the pattern-recognition technique on larger numerical simulations as well as on photonic chips in both traditional boson-sampling and scatter-shot experiments. The effectiveness of such a method relies on particle-type-dependent internal correlations present in the output distributions. This approach performs substantially better on the test data than previous methods and underscores the ability to further generalize its operation beyond the scope of the examples that it was trained on.

We study the bulk-boundary correspondence for topological crystalline phases, where the crystalline symmetry is an order-two (anti)symmetry, unitary or antiunitary. We obtain a formulation of the bulk-boundary correspondence in terms of a subgroup sequence of the bulk classifying groups, which uniquely determines the topological classification of the boundary states. This formulation naturally includes higher-order topological phases as well as topologically nontrivial bulk systems without topologically protected boundary states. The complete bulk and boundary classification of higher-order topological phases with an additional order-two symmetry or antisymmetry is contained in this work.

We show, by solving Maxwell’s equations, that an electric charge on the surface of a slab of a linear magnetoelectric material generates an image magnetic monopole below the surface provided that the magnetoelectric has a diagonal component in its magnetoelectric response. The image monopole, in turn, generates an ideal monopolar magnetic field outside of the slab. Using realistic values of the electric and magnetic field susceptibilities, we calculate the magnitude of the effect for the prototypical magnetoelectric material ${\mathrm{Cr}}_2{\mathrm{O}}_3$. We use low-energy muon spin rotation to measure the strength of the magnetic field generated by charged muons as a function of their distance from the surface of a ${\mathrm{Cr}}_2{\mathrm{O}}_3$ film and show that the results are consistent with the existence of the monopole. We discuss other possible routes to detecting the monopolar field, and show that, while the predicted monopolar field generated by ${\mathrm{Cr}}_2{\mathrm{O}}_3$ is above the detection limit for standard magnetic force microscopy, the detection of the field using this technique is prevented by surface charging effects.

We perform microwave spectroscopy of Andreev states in superconducting weak links tailored in an InAs-Al (core-full shell) epitaxially grown nanowire. The spectra present distinctive features with bundles of four lines crossing when the superconducting phase difference across the weak link is 0 or $\pi$. We interpret these features as arising from zero-field spin-split Andreev states. A simple analytical model, which takes into account the Rashba spin-orbit interaction in a nanowire containing several transverse subbands, explains these features and their evolution with magnetic field. Our results show that the spin degree of freedom is addressable in Josephson junctions and constitute a first step towards its manipulation.

Artificial electronic lattices, created atom by atom in a scanning tunneling microscope, have emerged as a highly tunable platform to realize and characterize the lowest-energy bands of novel lattice geometries. Here, we show that artificial electronic lattices can be tailored to exhibit higher-energy bands. We study $p$-like bands in fourfold and threefold rotationally symmetric lattices. In addition, we show how an anisotropic design can be used to lift the degeneracy between $p_x$- and $p_y$-like bands. The experimental measurements are corroborated by muffin-tin and tight-binding calculations. The approach to engineer higher-energy electronic bands in artificial quantum systems introduced here enables the realization of complex band structures from the bottom up.

Tunable directional scattering is of paramount importance for operation of antennas, routing of light, and design of topologically protected optical states. For visible light scattered on a nanoparticle, the directionality could be provided by the Kerker effect, exploiting the interference of electric and magnetic dipole emission patterns. However, magnetic optical resonances in small sub-100-nm particles are relativistically weak. Here, we predict inelastic scattering with the unexpectedly strong tunable directivity up to 5.25 driven by a trembling of a small particle without any magnetic resonance. The proposed optomechanical Kerker effect originates from the vibration-induced multipole conversion. We also put forward an optomechanical spin-Hall effect, the inelastic polarization-dependent directional scattering. Our results uncover an intrinsically multipolar nature of the interaction between light and mechanical motion and apply to a variety of systems from cold atoms to two-dimensional materials to superconducting qubits. An application for engineering of chiral optomechanical coupling and nonreciprocal transmission at nanoscale is proposed.

Decoherence is the process via which quantum superposition states are reduced to classical mixtures. Decoherence has been predicted for relativistically accelerated quantum systems; however, examples to date have involved restricting the detected field modes to particular regions of space-time. If the global state over all space-time is measured, then unitarity returns and the decoherence is removed. Here, we study a decoherence effect associated with accelerated systems that cannot be explained in this way. In particular, we study a uniformly accelerated source of a quantum field state—a single-mode squeezer. Even though the initial state of the field is vacuum (a pure state) and the interaction with the quantum source in the accelerated frame is unitary, we find that the final state detected by inertial observers appears to be decohered, i.e., in a mixed state. This unexpected result may indicate new directions in resolving inconsistencies between relativity and quantum theory. We extend this result to a two-mode state and find that entanglement is also decohered.

Out-of-time-order correlation (OTOC) functions provide a powerful theoretical tool for diagnosing chaos and the scrambling of information in strongly interacting, quantum systems. However, their direct and unambiguous experimental measurement remains an essential challenge. At its core, this challenge arises from the fact that the effects of both decoherence and experimental noise can mimic that of information scrambling, leading to decay of OTOCs. Here, we analyze a quantum teleportation protocol that explicitly enables one to differentiate between scrambling and decoherence. Moreover, we demonstrate that within this protocol, one can extract a precise “noise” parameter which quantitatively captures the nonscrambling-induced decay of OTOCs. Using this parameter, we prove explicit bounds on the true value of the OTOC. Our results open the door to experimentally measuring quantum scrambling with built-in verifiability.

We investigate the quantum Heisenberg model on the pyrochlore lattice for a generic spin $S$ in the presence of nearest-neighbor $J_1$ and second-nearest-neighbor $J_2$ exchange interactions. By employing the pseudofermion functional renormalization group method, we find, for $S=1/2$ and $S=1$, an extended quantum-spin-liquid phase centered around $J_2=0$, which is shown to be robust against the introduction of breathing anisotropy. The effects of temperature, quantum fluctuations, breathing anisotropies, and a $J_2$ coupling on the nature of the scattering profile, and the pinch points, in particular, are studied. For the magnetic phases of the $J_1\text{−}{J}_2$ model, quantum fluctuations are shown to renormalize phase boundaries compared to the classical model and to modify the ordering wave vectors of spiral magnetic states, while no new magnetic orders are stabilized.

A crucial limit to measurement efficiencies of superconducting circuits comes from losses involved when coupling to an external quantum amplifier. Here, we realize a device circumventing this problem by directly embedding an artificial atom, comprised of a transmon qubit, within a flux-pumped Josephson parametric amplifier. This configuration is able to enhance dispersive measurement without exposing the qubit to appreciable excess backaction. Near-optimal backaction is obtained by engineering the circuit to permit high-power operation that reduces information loss to unmonitored channels associated with the amplification and squeezing of quantum noise. By mitigating the effects of off-chip losses downstream, the on-chip gain of this device produces end-to-end measurement efficiencies of up to 80%. Our theoretical model accurately describes the observed interplay of gain and measurement backaction and delineates the parameter space for future improvement. The device is compatible with standard fabrication and measurement techniques and, thus, provides a route for definitive investigations of fundamental quantum effects and quantum control protocols.

We study rough high-dimensional landscapes in which an increasingly stronger preference for a given configuration emerges. Such energy landscapes arise in glass physics and inference. In particular, we focus on random Gaussian functions and on the spiked-tensor model and generalizations. We thoroughly analyze the statistical properties of the corresponding landscapes and characterize the associated geometrical phase transitions. In order to perform our study, we develop a framework based on the Kac-Rice method that allows us to compute the complexity of the landscape, i.e., the logarithm of the typical number of stationary points and their Hessian. This approach generalizes the one used to compute rigorously the annealed complexity of mean-field glass models. We discuss its advantages with respect to previous frameworks, in particular, the thermodynamical replica method, which is shown to lead to partially incorrect predictions.