One of the surprising, and potentially very useful, capabilities of analog quantum computers, such as D-Wave quantum annealers, is sampling from the Boltzmann, or Gibbs, distribution defined by a classical Hamiltonian. In this study, we thoroughly examine the ability of D-Wave quantum annealers to sample from the Boltzmann distribution defined by a canonical type of competing magnetic frustration $J_1\text{−}{J}_2$ model, the one-dimensional ANNNI (axial next-nearest-neighbor Ising) model. Boltzmann sampling error rate is quantified for standard linear-ramp anneals ranging from 5 ns annealing times up to 2000 µs on two different D-Wave quantum annealing processors. Interestingly, we find some analog hardware parameters that result in a very high accuracy (down to a total variation distance of 0.0003) and low-temperature sampling (down to $\beta =32.2$) in a frustrated region of the ANNNI model magnetic phase diagram. This bolsters the viability of current analog quantum computers for thermodynamic sampling applications of highly frustrated magnetic spin systems.

Flocking is a prime example of how robust collective behavior can emerge from simple interaction rules. The flocking transition has been studied extensively since the inception of the original Vicsek model. Here, we introduce a self-propelled particle model with quenched disorder in the pairwise alignment interaction couplings akin to a spin-glass model. We find that increasing the variance of the coupling distribution can promote (rather than destroy) the emergence of global polar order. In particular, we show that our model can display a flocking phase even when the majority of the interaction couplings are antialigning. Activity is the key ingredient to reduce frustration in the system as it allows local particle clustering combined with self-organization of the particles to favor neighborhoods with strong cooperative interactions.

We elaborate a mechanism for the creation of stable three-dimensional (3D) solitons in spin-orbit-coupled (SOC) atomic-molecular Bose-Einstein condensates, modeled by the mean-field equations with the quadratic three-wave interaction, characterized by mismatch $\alpha$. The planar (effectively two-dimensional) SOC is applied to the soliton’s atomic component, structuring it as a mixed mode (MM) or semivortex (SV). The molecular component of the SV soliton is shaped as a 3D vortex, while the molecular component in the MM soliton is an MM too. The solitons exist up to a critical value of $\alpha$. The system demonstrates a relatively large norm share of the vortex components, exceeding $50\%$ of the total norm, which is an essential feature of SOC-supported solitons. This is a scheme for realizing stable vortex solitons in free space with the quadratic nonlinearity.

Functional connectivity (FC) is fundamentally nonstationary, undergoing continuous reconfigurations that track shifting behavioral and cognitive states. Despite the importance of these transitions, existing analytical frameworks struggle to reconcile the high-dimensional nature of these reconfigurations with the need for structured trajectories and mechanistic interpretability. Specifically, identifying the precise network components responsible for driving these dynamics remains a significant challenge. To bridge this gap, we introduce RONI (Riemannian filtering of network interactions), a geometry-aware, unsupervised framework that treats time-varying FC as a signal evolving on the manifold of symmetric positive semidefinite (SPSD) matrices. By defining intrinsic filtering operators along the SPSD geodesics, RONI produces a multiresolution decomposition of FC dynamics directly on the manifold. This representation allows for the isolation of “dynamic drivers”—specific network elements that dominate coherent connectivity modes across distinct temporal scales. We demonstrate the versatility of RONI by applying it to a diverse array of large-scale neural recordings, including hippocampal electrophysiology data, cortex-wide and dendritic calcium imaging, and human electroencephalography. Across these varied modalities and spatiotemporal scales, RONI identifies biologically meaningful subnetworks that shape the geometry of the connectivity trajectory, providing a unified, interpretable, and quantitative framework for studying the evolution of distributed neural interactions.

Biological cells and synthetic analogues use liquid-liquid phase separation to dynamically compartmentalize their environment for various applications. In many cases, multiple droplets need to coexist, and their size needs to be controlled, which is challenging because large droplets tend to grow at the expense of smaller ones. Chemical reactions can, in principle, control droplet sizes, but there are no clear guidelines on how to robustly achieve size control. To provide guidelines, we consider a binary fluid model driven out of equilibrium by chemical reactions. We reveal two different classes of size-controlled droplets, depending on the ratio of droplet radius to the reaction-diffusion length. Moreover, we determine parameter regimes in which droplets become small. Taken together, our theory allows us to separately predict the chemical reactions necessary for maintaining droplets of a given class or size.

Despite extensive experimental efforts over the past two decades, topological superconductivity and Majorana fermions have remained elusive. By shifting focus from superconductors—whose topological nature is often debated—to the well-established $p$-wave superfluid ${}^3\mathrm{He}$, we propose an experimental approach designed to identify quantum Hall nature of the chiral superfluid ${}^3\mathrm{He}-A$ phase. The method exploits the interaction between surface waves and the induced current transverse to varying density of the superfluid. It allows one to quantitatively measure this Hall current and thus to directly evaluate whether the Hall current is quantized or not. As the quantum Hall effect is a hallmark of topological condensed matter, such an experiment would offer direct evidence of nontrivial topology of superfluid ${}^3\mathrm{He}$. With the advent of microscopic superfluid resonators coupled to optical cavities, this proposal is both realistic and promising, potentially opening the door to future experiments ranging from topological acoustics to fault-tolerant quantum computing.

Quantum networks promise scalable distributed quantum information processing. Realizing this potential depends critically on the efficient use of nonclassical resources. Sequential sharing of quantum nonlocality provides a resource-efficient route for recycling entanglement across multiple observers. In network settings, however, such recycling is typically constrained by a trade-off between the number of active branches and the achievable sharing depth. Here, we investigate this problem in star networks using probabilistic projective measurements. We establish an explicit entanglement threshold above which nonlocality can be shared across all branches up to any target depth, and below which we determine the optimal trade-off between the number of active branches and the achievable number of sequential rounds. We further analyze the protocol’s robustness to noise and its experimental observability, clarifying its practical feasibility. These results establish quantitative design principles and entanglement requirements for scalable nonlocality recycling in quantum networks.

Understanding the entanglement dynamics in quantum many-body systems under steady-state transport conditions is an actively pursued challenging topic. Hydrodynamic equations, akin to transport equations for charge or heat, would be of great interest but face severe challenges because of the inherent nonlocality of entanglement and the difficulty of identifying conservation laws. We show that progress is facilitated by using information as a key quantity related to—but distinct from—entanglement. Employing the recently developed “information lattice” framework, we formulate general continuity equations governing the flow of spatially and scale-resolved information currents in nonequilibrium open quantum systems. To illustrate our theory, we consider noninteracting fermion chains coupled to dissipative reservoirs, using Lindblad master equations. By relating the information lattice to a noise lattice constructed from particle-number fluctuations, we show that information is experimentally accessible via noise measurements. Similarly, local information currents can be obtained by measuring particle currents, on-site occupations, and covariances of particle numbers and/or particle currents. Using the fermionic negativity to quantify bipartite entanglement, we also study transport-induced entanglement and its relation to information currents. For a clean particle-hole symmetric chain, we find that information currents are shielded from entering the information lattice. Impurities or particle-hole asymmetry break this effect, causing information current flow and entanglement between end segments of the chain. Our work opens the door to systematic investigations of information transport and entanglement generation in driven open quantum systems far from equilibrium.

Remote state preparation (RSP) allows one party to remotely prepare a known quantum state on another party's qubit using entanglement. This can be used in quantum networks to perform applications such as blind quantum computing or long-distance quantum key distribution (QKD) with quantum repeaters. Devices to perform RSP, referred to as a client, ideally have low hardware requirements, such as only sending photonic qubits. A weak coherent pulse source offers a practical alternative to true single-photon sources and is already widely used in QKD. Here, we introduce two protocols to the previously known protocol for RSP with a weak-coherent-pulse-based device. The known technique uses a double-click (DC) protocol, where a photon from both the server and the client needs to reach an intermediate Bell state measurement. Here, we add to that a single-click (SC) RSP protocol, which requires only one photon to reach the Bell state measurement, allowing for better performance in certain regimes. In addition, we introduce a double-single-click (DSC) protocol, where the SC protocol is repeated twice, and a cnot gate is applied between the resulting qubits. DSC mitigates the need for phase stabilization in certain regimes, lowering technical complexity while still improving performance compared to DC in some regimes. We compare these protocols in terms of fidelity and rate, finding that SC consistently achieves higher rates than DC and, interestingly, does not suffer from an inherently lower fidelity than DC, as is the case for entanglement generation. Although SC provides stronger performance, DSC can still show performance improvements over DC, and it may have reduced technical complexity compared to SC. Finally, we show how these protocols can be used in long-distance QKD using quantum repeaters.

Disorder in photonic lattices creates localized states inside the photonic band gap. The energy distribution of these states is often described as a Lifshitz tail, even though it is inconsistent with Lifshitz statistics near the band edge. Here, we show that in photonic-crystal waveguides with intentionally engineered anisotropic disorder, the band-edge tail accessible experimentally follows an Urbach law, with cumulative statistics $F\left(\mathrm{\Delta }\right)=exp[-{(\mathrm{\Delta }/\alpha )}^{\beta }]$, where $\mathrm{\Delta }$ is the spectral detuning from the band edge, and an exponent $\beta \approx 1$ independent of disorder strength and orientation. In contrast to Lifshitz behavior, the density of states is maximal at the band edge and decays into the gap. Crucially, we find that the Urbach energy $\alpha$ is anisotropic, with a pronounced directional splitting and qualitatively different scaling for disorder parallel and perpendicular to the waveguide axis. These conclusions are supported by quantitative agreement between optical measurements of GaAs photonic-crystal waveguides and full-vector simulations. The anisotropic Urbach energy emerges as a sensitive probe of the coupling between structural disorder and the guided Bloch mode, and a practical metric to characterize structural disorder in photonic devices.

We study the triangular lattice optical Su-Schrieffer-Heeger (SSH) model using determinant quantum Monte Carlo. By varying the model's carrier concentration $\langle n\rangle$, electron-phonon coupling strength, and phonon energy $\mathrm{\Omega }$, we identify two doping regimes of interest. At one-quarter filling ($\langle n\rangle =0.5$), corresponding to the case of a circular noninteracting Fermi surface, we find evidence for a metal to insulating bond-order-wave (BOW) phase transition that breaks a local $C_6$ rotational symmetry. Conversely, at three-quarter filling ($\langle n\rangle =1.5$), corresponding to a hexagonal Fermi surface, we find evidence for transitions to a metallic BOW phase for small $\mathrm{\Omega }$ and an $s$-wave superconducting phase for sufficiently large $\mathrm{\Omega }$. This tendency toward pairing appears to be associated with the possibility of a sign change in the effective nearest-neighbor intersite hopping, which can occur for sufficiently large lattice displacements. We also find no evidence for enhanced magnetic correlations in the model, contrary to what has been reported for some square lattice SSH models.

We present a native realization of iSWAP and parametrized exchange gates for neutral-atom quantum processing units. Our approach leverages strong dipole-dipole interactions between two different dipole-coupled Rydberg states, employing optimal control techniques to design high-fidelity, time-efficient gate pulses. To minimize experimental complexity, we utilize global driving fields acting identically on all atoms and apply pulse smoothing techniques. While detrimental van der Waals interactions pose a significant challenge, we demonstrate that for both ${}^{133}\mathrm{Cs}$, as a representative alkali atom, and ${}^{88}\mathrm{Sr}$, an alkaline-earth species, high-fidelity pulses can nevertheless be obtained over a broad range of parameters. We identify candidate protocols with reduced susceptibility to noise and analyze their performance under realistic conditions, accounting for atomic motion, Rydberg decay, and experimentally motivated laser frequency and intensity noise. Crucially, we demonstrate that in both Alkali and alkaline-earth-based systems, we can obtain fast iSWAP gates with fidelities of $99.9\%$ under realistic experimental conditions. These results pave the way for expanding the neutral-atom gate set beyond conventional Rydberg-blockade-based entangling gates.

This article is part of a Physical Review Collection on the Physics in a Changing Climate.

The Atlantic Meridional Overturning Circulation (AMOC) has been identified as a tipping element in the Earth system. Under the current climate change scenarios, it is urgent to develop robust methods for determining the probability of future AMOC transitions. Recent studies using an Earth system model of intermediate complexity (EMIC) have revealed the importance of an AMOC edge state, located on the boundary of the attraction basin of the collapsed state, in AMOC transitions. Here, we provide a characterization of this edge state through climate networks, using instantaneous temporal correlations between geographical locations to define the network links. We apply the climate network analysis to a set of EMIC simulations with ${\mathrm{CO}}_2$ forcing according to an intermediate climate change scenario (SSP2-4.5), which exhibit qualitatively different AMOC responses as a result of interaction with the edge state. We show that network measures, specifically the normalized degree centrality, reveal the presence of teleconnections across the equator as the AMOC approaches the edge state. A similar result is obtained for an Earth system model (ESM) simulating AMOC collapse or recovery, suggesting that climate networks could be used to detect an AMOC instability in ESMs and observations.

Recently proposed analog solvers based on dynamical systems, such as Ising machines, are promising platforms for large-scale combinatorial optimization. Yet, given the heuristic nature of the field, there is very limited insight on optimality guarantees of the solvers, as well as how parameter schedules shape dynamics and outcomes. Here, we develop a dynamical mean-field framework to analyze Ising-machine dynamics for finding the ground-state energy of the Sherrington-Kirkpatrick (SK) model of spin glasses and identify mechanisms that enable rapid convergence to provably near-optimal energies. For a fixed target energy density $E_c$, we show that solutions are typically reached within $O\left(1\right)$ matrix vector multiplications, indicating constant time complexity. We further delineate theoretical limitations arising from different parameter-scheduling trajectories and demonstrate a pronounced benefit of temperature-only annealing for the coherent Ising machine. Building on these insights, we propose a general framework for designing optimized parameter schedules, thereby improving the practical effectiveness of Ising machines for complex optimization tasks. The superior performance of the dynamical solvers is illustrated by the attainment of the ground-state energy of the SK model.

Point defects play a central role in driving the properties of materials. First-principles methods are widely used to compute defect energetics and structures, including at scale for high-throughput defect databases. However, these methods are computationally expensive, making machine learning force fields (MLFFs) an attractive alternative for accelerating structural relaxations. Most existing MLFFs are based on graph neural networks (GNNs), which can suffer from oversmoothing, oversquashing, and poor representation of long-range interactions. Both of these issues are especially of concern when modeling point defects. To address these challenges, we introduce the Accelerated Deep Atomic Potential Transformer (ADAPT), an MLFF that replaces graph representations with a direct coordinates-in-space formulation and explicitly considers all pairwise atomic interactions. Atoms are treated as “tokens,” with a transformer encoder modeling their interactions. Applied to a dataset of silicon point defects, ADAPT achieves an $\sim 22\%$ reduction in force and an $\sim 40$ reduction in energy prediction error relative to a state-of-the-art GNN-based model, while requiring only a fraction of the computational cost.

Active matter generates order or patterns through nonequilibrium dynamics. An open research challenge is to determine how efficiently a nonequilibrium self-organizing system can convert consumed energy into macroscopic order. We study an information-theoretic quantity that directly addresses this challenge by estimating the entropy reduction induced by a small control-parameter perturbation, relative to the generalized work required for the perturbation. This quantity has previously been considered mainly in an equilibrium or near-equilibrium context, and here we extend this framework and apply it to two nonequilibrium self-organizing systems: persistent and active Ising models. We observe that the thermodynamic efficiency of nonequilibrium systems maximizes at phase transitions, as in equilibrium systems. Furthermore, we compare thermodynamic efficiency and inferential efficiency across control parameters. While these two quantities are equal in equilibrium as a consequence of the fluctuation-dissipation theorem, we report that they diverge out of equilibrium, and the gap serves as a phenomenological signature of broken detailed balance.

There is widespread interest in many-body quantum systems that exhibit limit-cycle or time-crystalline behavior. An ideal quantum limit cycle would be realized using fully coherent driving (to minimize noise) and also have a continuous internal symmetry (to ensure generation of monochromatic radiation). While these two requirements may seem incompatible, we introduce in this work a large class of multimode bosonic limit-cycle models based on coherent parametric driving, which possess an $\text{O}\left(N\right)$ continuous symmetry. Surprisingly, the full quantum dissipative steady state of these models can be found exactly. They exhibit rich physics, including steady-state entanglement, reduced phase diffusion, and the possibility of realizing quantum limit tori. The basic mechanism we identify provides a unified way to understand how coherent parametric driving can yield symmetry-enriched limit cycles, and also helps us understand related models where the relevant symmetries are weakly broken. The models we study are compatible with a range of different experimental platforms, including quantum optical setups and superconducting quantum circuits.

The divergence of the electron density of states (DOS) plays an important role in enhancing many-body interactions and inducing various quantum phases in low-dimensional systems. However, such unique electronic structures remain experimentally elusive in three-dimensional (3D) systems, particularly those with strong spin-orbit coupling (SOC). Using angle-resolved photoemission spectroscopy and first-principles calculations for a Laves-phase superconductor ${\mathrm{CsBi}}_2$, which features a Bi-pyrochlore 3D network with strong SOC, we identify two characteristic electronic structures with a large DOS. One is a quasiflat band within a topologically nontrivial band sector with $p$-orbital character, locally formed around the U-K line, which enhances DOS near the Fermi level. The other involves type-I and type-II saddle points connected by a quasiflat band, which cooperatively produce an enhancement in the DOS. Our findings lay a foundation for exploring exotic phenomena driven by the interplay of multiple singularities with a large DOS, nontrivial topology, and strong SOC in 3D pyrochlores.