We model bipartisan elections where voters are exposed to two forces: local homophilic interactions and external influence from two political campaigns. The model is mathematically equivalent to the random field Ising model with a bimodal field. When both parties exceed a critical campaign spending, the system undergoes a phase transition to a highly polarized state where homophilic influence becomes negligible, and election outcomes mirror the proportion of voters aligned with each campaign, independent of total spending. The model predicts a hysteresis region, where the election results are not determined by campaign spending but by incumbency. Calibrating the model with historical data from US House elections between 1980 and 2020, we find the critical campaign spending to be $\sim 1.8$ million USD. Campaigns exceeding critical expenditures increased in 2018 and 2020, suggesting a boost in political polarization.

Stochasticity is a defining feature of the pairwise forces governing interactions in biological systems—from molecular motors to cell-cell adhesion—yet its consequences on large-scale dynamics remain poorly understood. Here, we show that reciprocal but randomly fluctuating interactions between particles create active suspensions that can enhance the diffusion of an external tracer particle, even in the absence of self-propulsion or nonreciprocity. Starting from a lattice model with pairwise dynamics that minimally break detailed balance, we derive a coarse-grained dynamical theory for spatiotemporal density fluctuations and reveal an elevated effective temperature at short wavelengths. We then compute the self-diffusion coefficient of a tracer particle weakly coupled to our active fluid, demonstrating that purely reciprocal stochastic interactions provide a distinct and generic route to enhanced diffusivity in dense nonequilibrium suspensions.

Topological order (TO) provides a natural platform for storing and manipulating quantum information. However, its stability to noise has only been systematically understood for Abelian TOs. In this Letter, we exploit the nondeterministic fusion of non-Abelian anyons to inform active error-correction and design decoders where the fusion products, instead of flag qubits, herald the noise. This intrinsic heralding offers improved thresholds over those of Abelian counterparts. Furthermore, we use Bayesian inference to obtain a statistical mechanics model for fixed-point non-Abelian TOs with perfect measurements under any noise model, which yields the optimal threshold conditioned on measuring anyon syndromes. We numerically illustrate these results for $D_4\cong {\mathbb{Z}}_4⋊{\mathbb{Z}}_2$ TO. In particular, for non-Abelian charge noise and perfect syndrome measurement, we find a conditioned optimal threshold $p_c=0.218(1)$, whereas an intrinsically heralded minimum-weight perfect matching (MWPM) decoder already gives $p_c=0.20842(2)$, outperforming standard honeycomb-lattice MWPM with $p_c=0.15860(1)$. Our Letter highlights how non-Abelian properties can enhance stability, rather than reduce it, and discusses potential generalizations for achieving fault tolerance.

The strong coupling regime of four-dimensional $N=2$ supersymmetric vacua of the heterotic string is analyzed from a dual domain wall perspective. Using modular invariance, we compute a closed form for the nonperturbative corrections to the supersymmetric domain wall equations, which enables a quantitative study of gravitational strong coupling regimes. A strong coupling singularity for the hidden Hořava-Witten 9-brane is resolved, and the domain wall interpolates between the visible 9-brane and a supersymmetric anti–de Sitter vacuum, thereby realizing a variant of the Randall-Sundrum model.

Light dark matter with sub-eV masses has a high number density in our Galaxy, and its scattering cross section with macroscopic objects can be significantly enhanced by coherence effects. Repeated scattering with a target object can induce a measurable acceleration. Torsion balance experiments with geometric asymmetry are, in principle, capable of detecting such signals. Our analysis shows that existing torsion balances designed to test the equivalence principle already place the most stringent constraints on DM-nucleon scattering in the $({10}^{-2},1)\mathrm{eV}$ mass range.

This Letter reports the first measurement of photonuclear $D^0$ meson production in ultraperipheral heavy ion collisions. The study is performed using lead-lead collision data, with an integrated luminosity of $1.34{\mathrm{nb}}^{-1}$, collected by the CMS experiment at a nucleon-nucleon center-of-mass energy of 5.36 TeV. Photonuclear events, where one of the colliding nuclei breaks up and the other remains intact, are selected based on breakup neutron emissions and by requiring no particle activity in a large rapidity interval in the direction of the photon-emitting nucleus. The $D^0$ mesons are reconstructed via the $D^0\to K^{-}{\pi }^{+}$ decay channel, with the cross section measured as a function of $D^0$ meson transverse momentum and rapidity. The results are compared with next-to-leading-order perturbative QCD calculations that employ recent parametrizations of the lead nuclear parton distribution functions, as well as with predictions based on the color glass condensate framework. This measurement is the first photonuclear collision study characterizing parton distribution functions of lead nuclei for parton fractional momenta $x$ (relative to the nucleon) ranging approximately from a few ${10}^{-4}$ to ${10}^{-2}$ for different hard energy scale $Q^2$ selections.

Solids fracture under critical stress, while liquids exhibit continuous deformation. Viscoelastic liquids can fracture like solids when the deformation rate is high enough that the material’s storage modulus $G^{\prime }$ is approximately the same or higher than its loss modulus $G^{\prime \prime }$. Here, we present direct experimental evidence of solidlike fracturing in hydrocarbon blend liquids whose $G^{\prime \prime }$ is an order of magnitude greater than $G^{\prime }$ for the rates probed. In our experimental setup, high-viscosity simple liquids were subjected to shear and extensional flow. Fracture occurred at a total critical stress of $2(\pm 1)\mathrm{MPa}$ for hydrocarbon blends and styrene oligomers, which interestingly remained independent of viscosity, chemical composition, temperature, and velocity. Near the crack-onset velocity, ductile cup-cone fractures are observed, whereas at higher deformation rates the fracture becomes predominantly brittle. To test the generality of this phenomenon, we repeated the experiments using a different simple liquid, styrene oligomer, at different temperatures and observed the same fracture behavior. Our findings suggest that fractures in liquids can occur independent of the relative dominance of viscous or elastic behavior. These findings expand our understanding of fracture mechanics beyond purely elastic-induced phenomena. Further research is warranted to explore the underlying mechanisms and practical implications.

Among all materials, monocrystalline diamond has one of the highest measured thermal conductivities, with values above 2000 W/m/K at room temperature. Diamond nanostructures are increasingly used in photonics, electronics, and quantum technologies, where heat dissipation is critical. However, predicting nanoscale heat flow is made difficult by the predominance of momentum-conserving “normal” phonon-phonon scattering processes. Here, we use dilute nitrogen-vacancy color centers as in situ, highly precise spin defect thermometers to image temperature inhomogeneities in single-crystal diamond microstructures heated from ambient conditions. We analyze cantilevers with cross sections in the range from about 0.2 to $2.6{\mathrm{\mu m}}^2$, observing a strong reduction in the cantilevers’ conductivity as width decreases. We use first-principles simulations based on the linearized phonon Boltzmann transport equation and viscous heat equations to quantitatively predict the cantilevers’ thermal transport properties, rationalizing how the interplay between intrinsic and extrinsic phonon scattering mechanisms determines the observed nondiffusive behavior. Our temperature-imaging method paves the way for the exploration of unconventional, nondiffusive heat-transport phenomena in devices and nanostructures of arbitrary geometries.

Perhaps the simplest approach to constructing models with subdimensional particles or fractons is to require the conservation of dipole or higher multipole moments. We generalize this approach to allow for moments in phase space and classify all possible classical fracton models with phase-space multipole conservation laws. We focus on a new self-dual model that conserves both dipole and quadrupole moments in position and momentum; we analyze its dynamics and find quasiperiodic orbits in phase space that evade ergodic exploration of the full phase space.

Ultrafast pump-probe imaging reveals that the efficiency of optical excitation of coherent spin waves in epitaxial iron garnet films can be effectively controlled by an external electric field at room temperature. Although a femtosecond laser pulse alone does not excite any pronounced coherent spin oscillations, an electrical gating with the field of $0.5\mathrm{MV}/\mathrm{m}$ dramatically changes the outcome in a laser-induced launching of spin waves. The effect, demonstrated under room-temperature conditions, is estimated to be orders of magnitude larger than in magnetic van der Waals semiconductors observed at 10 K. This electrical gating of laser-induced spin dynamics enriches optomagnonics with a new tool and thus opens up a new avenue in fundamental and applied magnonics research.

Probing forces, deformations, and mechanical properties of cells are the hallmark of mechanobiology. Many techniques have been developed to this end that are largely based on deforming the cells and measuring the reaction force. In cells, an alternative approach was implemented in the mid-2010s based on Brillouin light scattering (BLS), which allows extracting acoustic parameters at picosecond timescales. In all of these measurements, the response of the cell is quantified with a colloquial “stiffness” that encompasses both the contribution of load-bearing structures and volume changes, to much confusion. To clarify the interpretation of the hypersonic data obtained from BLS spectra, we vary the relative volume fraction of an intracellular water and solid network by applying osmotic compressions to single cells. In the nucleus, we observe a nonlinear increase in the sound velocity and attenuation with increasing osmotic pressure that we fit to a poroelastic model. By comparing BLS data to volume measurements, our approach demonstrates clearly that BLS shift alone is mostly sensitive to water content while the additional analysis of the linewidth allows identifying the contribution of the biopolymer-based network dynamics in living cells.

The presence of Bell nonlocality in the correlations arising from measuring spatially separated systems guarantees that the sets of measurements used are necessarily incompatible. Not all sets of incompatible measurements can however lead to Bell nonlocality, as there exist incompatible sets of measurements which can only produce local correlations. In this Letter we prove that all sets of incompatible measurements are nevertheless able to generate nonlocality in an extended Bell scenario where quantum, instead of classical, measurement inputs are considered. In particular, this holds true for all incompatible-local sets of measurements and, consequently, shows that these sets of measurements posses a form of hidden nonlocality which can be revealed in such a scenario. We furthermore prove that the maximum amount of nonlocality that can be extracted in such a way is limited by the degree of incompatibility of the given set of measurements, thus effectively establishing an achievable upper bound. In order to obtain these results, we introduce a new object which we term a generalized set of measurements, which provides a unifying way to study any scenario involving quantum inputs.

Variational wave functions offer a practical route around the exponential complexity of many-body Hilbert spaces, but their expressive power is often sharply constrained. Matrix product states, for instance, are efficient but limited to area law entangled states. Neural quantum states (NQS) are widely believed to overcome such limitations, yet little is known about their fundamental constraints. Here we prove that feed-forward neural quantum states acting on $n$ spins with $k$ scalar nonlinearities, under certain analyticity assumptions, obey a bound on entanglement entropy for any subregion: $S\le ck\log n$, for a constant $c$. This establishes an NQS analog of the area law constraint for matrix product states and rules out volume law entanglement for NQS with $O(1)$ nonlinearities. We demonstrate analytically and numerically that the scaling with $n$ is tight for a wide variety of NQS. Our Letter establishes a fundamental constraint on NQS that applies broadly across different network designs, while reinforcing their substantial expressive power.

Entangled many-body states are a key resource for quantum technologies. Yet their preparation through analog control of interacting quantum systems is often hindered by experimental imperfections. Here, we introduce the adiabatic echo protocol, a general approach to state preparation designed to suppress the effect of static perturbations. We provide an analytical understanding of its robustness in terms of dynamically engineered destructive interference. By applying quantum optimal control methods, we demonstrate that such a protocol emerges naturally in a variety of settings, without requiring assumptions on the form of the control fields. Examples include Greenberger-Horne-Zeilinger state preparation in Ising spin chains and two-dimensional Rydberg atom arrays, as well as the generation of quantum spin liquid states in frustrated Rydberg lattices. Our results highlight the broad applicability of this protocol, providing a practical framework for reliable many-body state preparation in present-day quantum platforms.

Physical reservoir computing provides a powerful machine learning paradigm that exploits nonlinear physical dynamics for efficient information processing. By incorporating quantum effects, quantum reservoir computing offers superior potential for machine learning applications, as quantum dynamics are exponentially costly to simulate classically. Here, we present a novel quantum reservoir computing approach based on correlated quantum spin systems, exploiting natural quantum many-body interactions to generate reservoir dynamics, thereby circumventing the practical challenges of deep quantum circuits. Our experimental implementation supports nontrivial quantum entanglement and exhibits sufficient dynamical complexity for high-performance machine learning. We achieve state-of-the-art performance in experiments on standard time-series benchmarks, reducing prediction error by 1 to 2 orders of magnitude compared to previous quantum reservoir experiments. In long-term weather forecasting, our 9-spin quantum reservoir delivers greater prediction accuracy than classical reservoirs with thousands of nodes. This represents the first experimental demonstration of quantum machine learning outperforming large-scale classical models on real-world tasks.

We introduce frustration-free control, a measurement-feedback framework for quantum state preparation that extends frustration-free Hamiltonians to monitored stochastic dynamics. The protocol drives many-body systems into highly entangled target states, common dark states of all measurement projectors, through minimal local unitary corrections that realize an absorbing-state dynamics without postselection. We show that relaxation to the target state is governed by emergent transport of nonlocal charges, such as singlet excitations in SU(2)-symmetric dynamics. While measurement feedback annihilates compatible charge configurations, both measurement and scrambling unitaries induce charge transport and thus determine the convergence time. Mapping a baseline model of $\mathrm{SU}(N)$ SWAP measurements with local corrections to a solvable absorbing random walk yields a run-time scaling $t\sim L^z$ with transport exponent $z=2$. Simulations of Motzkin and Fredkin chains reveal subdiffusive scaling $z\ge \frac{8}{3}$, confirming absorbing-state transport as a general organizing principle for deterministic entangled-state preparation and transport diagnostics in monitored quantum dynamics.