We investigate the nature of memory effects in the non-Markovian dynamics of spin-boson models. Local quantum memory criteria can be used to indicate that the reduced dynamics of an open system necessarily requires a quantum memory in its environment. We focus on two such criteria, one based on the dynamical map and the other on single-intervention process tensors, and discuss their connection. We apply these criteria to quench dynamics in spin-boson and two-spin-boson models, computed using a numerically exact method for non-Markovian open-system dynamics based on matrix product operator influence functionals. This method is ideally suited to simulate quantum multitime processes in spin-boson models across broad parameter regimes. We find that, with access to single-intervention process tensors, one can generally predict quantum memory in the dynamics at low temperatures. Given instead only the dynamical map, it is still possible to detect quantum memory in the case of resonant environments at short evolution times. Moreover, we confirm quantum memory in the stationary dynamical regime using process tensors with the correlated steady state of system and environment as initial condition.

The Hubbard model has occupied the minds of condensed matter physicists for most part of the last century. This model provides insight into a range of phenomena in correlated electron systems. We wish to examine the paradigm of quantum algorithms for solving such many-body problems. The focus of our current work is on the one-dimensional model that is integrable, meaning that there exist analytical results for determining its ground state. In particular, we demonstrate how to perform a gate-based quantum computer simulation of quantum annealing for the Hubbard Hamiltonian. We perform simulations for systems with up to 40 qubits to study the scaling of required annealing time for obtaining the ground state. We find that for the half-filled cases considered, there is a polynomial quantum speedup over algorithms based on the Bethe-ansatz equations.

We study the quantum relaxation dynamics for a lattice version of the one-dimensional $N$-flavor Gross-Neveu model after a Hamiltonian parameter quench. Allowing for a system-reservoir coupling $\gamma$, we numerically describe the system dynamics through a time-dependent self-consistent Lindblad master equation. For a closed ($\gamma =0$) finite-size system subjected to an interaction parameter quench, the order parameter dynamics exhibits oscillations and revivals. In the thermodynamic limit, our results imply that the order parameter reaches its postquench stationary value in accordance with the eigenstate thermalization hypothesis. However, time-dependent finite-momentum correlation matrix elements equilibrate only if $\gamma >0$. Our findings are consistent with the system being described by a pertinent generalized Gibbs ensemble and, accordingly, highlight subtle yet important aspects of the postquench relaxation dynamics of quantum many-body systems.

We report the formation of a soliton—termed “event soliton”—in nonlinear photonic spacetime crystals (STCs). In these media, simultaneous spatiotemporal periodic modulation of the dielectric constant generates mixed frequency ($\omega$) and wave vector ($k$) gaps. Under Kerr nonlinearity, the event solitons emerge as fully localized entities in both spacetime and energy-momentum domains, providing a tangible demonstration of the concept of “event” in relativity. The $\omega k$-gap mixture arises from the coexistence and competition between time-reflected and Bragg-reflected waves due to the spatiotemporal modulation. We propose a partial differential equation to capture various spatiotemporal patterns and present numerical simulations to validate our theoretical predictions, reflecting a three-way balance among $k$-gap opening, $\omega$-gap opening, and nonlinearity. Our work opens avenues for fundamental studies and fosters experimental prospects for implementing spacetime crystals and pattern formation in time-varying photonics.

Stark broadening of spectral lines in plasmas is a cornerstone of opacity modeling and plasma diagnostics, with critical implications for controlled fusion and astrophysics. Despite recent advances in fully quantum-mechanical close-coupling calculations for electron-impact broadening, the impact of denser plasma environments remains largely unexplored due to theoretical bottlenecks associated with electron-ion collision processes. Based on our close-coupling theory for electron-ion collisions in plasmas, which resolves the problem of extracting short-range scattering phase shifts, we introduce a fully relativistic close-coupling approach for the Stark broadening that incorporates plasma screening effects. Systematic investigations of hydrogenic radiators reveal distinct patterns of line broadening dependence on plasma conditions, offering valuable insights for plasma diagnostic applications. Furthermore, we provide a quantum-mechanical interpretation of the screening factor commonly introduced in semiclassical impact theories. This work establishes a robust foundation for future studies on complex atomic systems in high-density plasmas.

Flat-band states in topological systems provide a unique platform for investigating strongly correlated phenomena and many-body physics. However, in two-dimensional (2D) static tight-binding systems, perfectly flat bands can only exist in the topologically trivial phase, as characterized by a zero Chern number. Here, we show that by introducing periodic driving into a 2D photonic Lieb lattice composed of coupled microring resonators, the resulting Floquet topological insulator can host perfectly flat bands with nontrivial topology. In particular, by tracking the evolution of the flat-band modes over each cycle, we show that the non-Abelian displacements of the flat-band modes are characterized by a nontrivial quantized helicity even though the quasienergy bands have zero Chern number. The helical motion of the flat-band modes can be described by a braiding of the world lines of their trajectories, with a nontrivial winding number directly connected to the helicity. We also propose a scheme to experimentally measure the quantized non-Abelian helicity in a microring lattice subject to a synthetic magnetic field. These results suggest that Floquet topological photonic insulators based on coupled microring resonators can provide a versatile platform for investigating non-Abelian topological physics and strongly correlated phenomena in photonic flat-band systems.

We develop an age-structured hydrodynamic (HD) theory that describes the collective behavior of $N\gg 1$ anomalously diffusing particles under stochastic renewal resetting. The theory treats the age of a particle—the time since its last reset—as an explicit dynamical variable and allows for resetting rules that introduce global interparticle correlations. The anomalous diffusion is modeled by the scaled Brownian motion (sBm): a Gaussian process with independent increments, characterized by a power-law time dependence of the diffusion coefficient, $D\left(t\right)\sim t^{2H-1}$, where $H>0$. We apply this theory to three different resetting protocols: independent resetting to the origin (model A), resetting to the origin of the particle farthest from it (model B), and a scaled-diffusion extension of the “Brownian bees” model of Berestycki et al. [Ann. Probab. 50, 2133 (2022)]. In all these models, nonequilibrium steady states are reached at long times, and we determine the steady-state densities. For model A, the (normalized to unity) steady-state density coincides with the steady-state probability density of a single particle undergoing sBM with resetting to the origin. For model B, and for the scaled Brownian bees, the HD steady-state densities are markedly different: In particular, they have compact supports for all $H>0$. The age-structured HD formalism can be extended to other anomalous diffusion processes with renewal resetting protocols that introduce global interparticle correlations.

Correlation functions and correlation lengths are frequently used to describe phase transitions in quantum systems, but they require an explicit choice of observables. The recently introduced information lattice instead provides an observable-independent way to identify where and at which scale information is contained in quantum lattice models. Here, we use it to study the difference between the metallic and insulating regimes of one-dimensional noninteracting tight-binding chains. We find that the information per scale follows a power law in metals at low temperature and that Friedel-like oscillations are visible in the information lattice. At high temperature or in insulators at low temperature, the information per scale decays exponentially. Thus, the information lattice is a useful tool for analyzing the metal-insulator transition.

We study the Schrödinger equation with $1/r^3$ and attractive $1/r^2$ potentials. Using the quantum defect theory, we obtain analytical solutions for both repulsive and attractive $1/r^3$ interactions. The obtained discrete-scale-invariant energies and wave functions, validated by excellent agreement with numerical results, provide a natural framework for describing the universality of Efimov states in mixed dimension. Specifically, we consider a three-body system consisting of two heavy particles with large dipole moments confined to a quasi-one-dimensional geometry and resonantly interacting with an unconfined light particle. With the Born-Oppenheimer approximation, this system is effectively reduced to the Schrödinger equation with $1/r^3$ and $1/r^2$ potentials, and manifests the Efimov effect. Our analytical solution suggests that, for repulsive dipole interactions, the three-body parameter of the mixed-dimensional Efimov states is universally set by the dipolar length scale, whereas for attractive interactions it explicitly depends on the short-range phase. We also investigate the effects of finite transverse confinement and find that our analytical results are useful for describing the Efimov states composed of two polar molecules and a light atom.

Marine organisms manipulate their surrounding flow through their swimming dynamics, which affects the transport of their own odor cues. We demonstrate by direct numerical simulations how a group of swimmers, moving at intermediate Reynolds numbers, immersed in a turbulent flow, alter the shape of the odor plume they release in the water. Odor mixing is enhanced by increased velocity fluctuations and a swimmer-induced flow circulation that widens the odor plume at close range while speeding up dilution of the chemical trace. Beyond a short-range increase in the likelihood of being detected, swimming considerably reduces detections with effects that can persist at distances on the order of ten times the size of the group or more. We find that pullerlike swimmers are more effective at olfactory shielding than pusherlike swimmers. We trace this difference back to the dynamics at the swimmer location, which tends to trap odor at the source for pushers and to dilute it for pullers. Olfactory shielding is robust to changes in the conditions, and is more pronounced for weak turbulent Reynolds numbers and large swimmer Reynolds numbers. Our results suggest that olfactory shielding may play a role in the emergence of different swimming modalities by marine organisms.

Effective-medium approaches, such as the coherent potential approximation, are commonly used to describe the rigidity transition of disordered elastic networks. While successful in capturing the universal critical behavior of these systems near the onset of rigidity, its traditional formulation neglects spatial correlations in the underlying disorder. Here, we propose a multipurpose generalization of the coherent potential approximation to describe the mechanical behavior of elastic networks with spatially correlated disorder. We apply our theory to a simple rigidity-percolation model for colloidal gels and study the effects of correlations on both the critical point and the overall scaling behavior. We find that although the presence of spatial correlations (mimicking attractive interactions in gels) shifts the critical packing fraction to lower values, suggesting subisostatic behavior, the critical coordination number of the associated network remains isostatic. More importantly, we discuss how our theory can be employed to describe a large variety of systems with spatially correlated disorder.

Tensor network formalisms have emerged as powerful tools for simulating quantum state evolution. While widely applied in the study of optical quantum circuits, such as boson sampling, existing tensor network approaches fail to address the complexity mismatch between tensor contractions and the calculation of photon-counting probability amplitudes. Here, we present an alternative tensor network framework that exploits the input-output relations of quantum optical circuits encoded in the unitary interferometer matrix. Our approach bridges the complexity gap by enabling the computation of the permanent—central to boson sampling—with the same computational complexity as the best known classical algorithm based on a graphical representation of the operator-basis matrix product states that we introduce. Furthermore, we exploit the flexibility of tensor networks to extend our formalism to incorporate partial distinguishability and photon loss, two key imperfections in practical interferometry experiments. This work offers a significant step forward in the simulation of large-scale quantum optical systems and the understanding of their computational complexity.

Modular architectures offer a scalable path toward fault-tolerant quantum computing by interconnecting smaller quantum processing units provided that high-rate, fault-tolerant interfaces can be realized across modules. We present a comprehensive analysis and comparison of known methods for establishing such interfaces, including lattice surgery, transversal gates, and grow-and-distill protocols based on code growing and logical distillation. Using the surface code, we identify optimal interface strategies across a wide range of hardware parameters, such as gate fidelities, entangling rates, and memory resources, and estimate the requirements to achieve logical error rates of ${10}^{-6}$ and ${10}^{-12}$. Our results establish when the interface becomes a bottleneck in the computation and provide guidance for experimental implementations with superconducting, atomic, and solid-state hardware.

We explore how the quantum geometric properties of the Bloch wave function, characterized by the Hilbert-Schmidt quantum distance, impact magnetic phases in solid-state systems. To this end, we investigate the spin susceptibility within the random phase approximation, considering the on-site Coulomb interaction. We demonstrate that spin susceptibility can be decomposed into a trivial part, dependent solely on the band dispersion, and a geometric part, where the quantum distance plays a crucial role. Focusing on a model of a quadratic band-touching semimetal, we show that a magnetic phase transition between ferromagnetic and antiferromagnetic orders can be induced solely by tuning the wave function geometry, even while the energy spectrum is held constant. This highlights the versatility of quantum geometry as a mechanism for tuning magnetic properties independent of the energy spectrum. Applying our framework to the Fe pnictide and kagome lattice models, we further show that the geometric contribution is decisive in stabilizing their known antiferromagnetic and ferromagnetic states, respectively. Our work sheds light on the hidden quantum geometric aspects necessary for understanding and engineering magnetic order in quantum materials.

We present an algorithm for extracting a smooth, positive-definite function $\psi \left(x\right)$ encoded in a quantum state vector of size $2^n$, while avoiding exponentially suppressed subnormalization of a naive extraction step. The method addresses a known limitation in quantum algorithms for differential equations, namely, the efficient retrieval of classical information from quantum-encoded solutions. It applies to settings where the target solution is smooth and positive definite, such as certain instances of the heat equation and related diffusive models arising in fluid dynamics and finance.

Analog quantum simulators provide access to many-body dynamics beyond the reach of classical computation. However, extracting physical insights from experimental data is often hindered by measurement noise, limited observables, and incomplete knowledge of the underlying microscopic model. Here, we develop a machine learning approach based on a variational autoencoder (VAE) to analyze interference measurements of tunnel-coupled one-dimensional Bose gases, which realize the sine-Gordon quantum field theory. Trained in an unsupervised manner, the VAE learns a minimal latent representation that strongly correlates with the equilibrium control parameter of the system. Applied to nonequilibrium protocols, the latent space uncovers signatures of frozen-in solitons following rapid cooling, and reveals anomalous postquench dynamics not captured by conventional correlation-based methods. These results demonstrate that generative models can extract physically interpretable variables directly from noisy and sparse experimental data, providing complementary probes of equilibrium and nonequilibrium physics in quantum simulators. More broadly, our work highlights how machine learning can supplement established field-theoretical techniques, paving the way for scalable, data-driven discovery in quantum many-body systems.

Driven-dissipative bosonic systems exhibit a rich variety of nonequilibrium steady states (NESS) due to the interplay between coherent drives, interactions, and dissipation. In the semiclassical limit, the flow topology of phase-space dynamics governs the stability and structure of these dynamical phases. Topological transitions occur when the number, chirality, and connectivity of NESS changes, reflecting a global reorganization of the dynamical phase-space landscape. Here, we study the impact of these topological signatures in a quantum driven-dissipative Kerr oscillator. Employing a Lindblad master equation and quantum-trajectory methods, we reveal that quantum dynamics retain key topological features of the underlying semiclassical flows, with clear signatures accessible via quantum state tomography and linear response. In this manner, we predict flow-topological phases whose signatures arise from a reorganization of fluctuation modes and are not captured by Liouvillian-gap closing alone. We, thus, generalize the conventional criteria for diagnosing phase transitions. Our findings position phase-space flow topology as a powerful tool to identify and control robust quantum phases, enabling advances in error correction and sensing.