From numerical simulations, it is known that the barrier-crossing time of a non-Markovian one-dimensional reaction coordinate with a single exponentially decaying memory function exhibits a memory turnover: For intermediate values of the memory decay time, the barrier-crossing time is reduced compared to the Markovian limit, and for long memory times, it increases quadratically with the memory time when keeping the total integrated friction and the mass constant. The intermediate memory acceleration regime is accurately predicted by Grote-Hynes theory; for the asymptotic long-memory slowdown behavior, no systematic analytically tractable theory is available. Starting from the Green's function for a general inertial (i.e., finite-mass) non-Markovian Gaussian reaction coordinate in a harmonic well, we derive by an exact mapping a generalized Fokker-Planck equation with a time-dependent effective diffusion constant. To first order in a systematic cumulant expansion, we derive an analytical Arrhenius expression for the barrier-crossing time with the preexponential factor given by the energy relaxation time, which can be used to robustly predict barrier-crossing times from simulation or experimental trajectory data of general non-Markovian inertial systems without the need to extract memory functions. For a single-exponential memory kernel, we give a closed-form expression for the barrier-crossing time, which reproduces the Kramers turnover between the high-friction and high-mass limits as well as the memory turnover from the intermediate memory acceleration to the asymptotic long-memory slowdown regime. We also demonstrate that a non-Markovian system with single-exponential memory is singular in the zero-mass limit and that the long-memory barrier-crossing slowdown reflects the interplay between mass and memory effects. Thus, physically sound models for non-Markovian systems should include a finite mass.

In active matter and living matter, such as clusters of migrating cells, collective dynamics emerges from the underlying interactions. A common assumption of theoretical descriptions of collective cell migration is that these interactions are pairwise additive. It remains unclear, however, whether the dynamics of groups of cells is solely determined by pairwise interactions or whether higher-order interaction terms come into play. To investigate this question, we use time-lapse microscopy to record the dynamics of three cells interacting together in a linear three-site geometry. We collect a large number of cellular trajectories and develop an inference scheme to infer both pairwise and potential three-body cell-cell interactions. Our results reveal evidence of three-body interactions in one of the two cell lines tested. However, these three-body interactions only introduce minor corrections to the overall dynamics. Our work provides a methodology to infer the existence of three-body interactions from trajectory data and supports the commonly assumed pairwise nature of cell-cell interactions.

The encounter of diffusing entities underlies a wide range of natural phenomena. The dynamics of these first-passage dynamics are strongly influenced by confining geometries. Confinement modifies microscopic diffusion through conservative and hydrodynamic interactions, making it essential for realistic modeling. In this article, we investigate how confinement affects the first-passage statistics of a diffusing particle. Using state-of-the-art holographic microscopy combined with advanced statistical inference, we probe this motion with nanometric precision. Our experimental and numerical results show that confinement can either hinder or enhance first-passage kinetics, depending on the spatial direction. In particular, a wall-normal target finding is accelerated by confinement-induced non-Gaussian displacement statistics—which increases the probability of rare, large displacements—compared to an analogous situation relying on a Gaussian process. The results presented hereafter carry implications for confined chemical reactions and biological winners-take-all processes near boundaries.

Actin flow in the cortical cytoskeleton underneath the cell membrane generates mechanical stresses that shape the cell surface. We study this mechanism using a hydrodynamic model of a compressible active gel polymerizing at the membrane and undergoing turnover. We determine how actin flow, density relaxation, and friction of actin with the membrane generate stress on a corrugated membrane at the linear order in deformation. Analytical solutions in limiting regimes, combined with finite element methods in the general case, provide a map of normal and tangential stresses as functions of compressibility, interfacial friction, and actin turnover, and determine the conditions under which actin polymerization can render the membrane linearly unstable. The nonlinear regime is also briefly discussed.

The emergence of functional connectivity between distant brain regions that lack a direct structural link remains a long-standing question in neuroscience. Remote synchronization (RS) offers a promising framework for uncovering the underlying mechanisms. So far, RS has been well studied in artificial network topologies such as star or starlike graphs but little attention has been paid to realistic brain networks with complicated topologies, due to their completely different synchronization pathways. In this study, we address this gap by introducing an efficient method, termed the noncompletely overlapping path algorithm, to detect RS using empirical structural and functional brain network data. Under this approach, two nodes are considered to exhibit RS if they are functionally synchronized despite being structurally disconnected. That is, they share neither a direct structural link nor an indirect path composed of synchronized nodes. We demonstrate that the proportion of RS nodes in a brain network strongly depends on the thresholds used to define both structural and functional connectivity, with optimal threshold values existing for each. Furthermore, we show that the method can be generalized: It applies not only to empirical time series but also to oscillator-based network models, and it admits a theoretical interpretation. This indicates that the algorithm offers a general framework to detect RS in complex networks.

In quantum computations of gauge theories at finite temperature and finite density, enforcing Gauss's law for all states contributing to the thermal ensemble is a nontrivial challenge. In this work, we adapt the quantum minimally entangled typical thermal states (QMETTS) algorithm to ${\mathbb{Z}}_2$ gauge-constrained systems and propose a method for computing finite-temperature and finite-density expectation values without eliminating redundant gauge-field degrees of freedom. In QMETTS, the thermal ensemble is sampled via a Markov chain of pure states generated by imaginary-time evolution and projective measurements. To preserve gauge invariance while maintaining efficient sampling, we introduce measurement bases that are gauge invariant and mutually unbiased within the physical subspace. We show that such measurement bases can be constructed efficiently for ${\mathbb{Z}}_2$ lattice gauge theories in arbitrary spatial dimensions and arbitrary boundary conditions by exploiting the correspondence between ${\mathbb{Z}}_2$ lattice gauge theories and the stabilizer formalism. Furthermore, since expectation-value estimation on quantum hardware is inherently affected by shot noise, we explicitly incorporate shot noise into the analysis. By formulating a finite-shot version of QMETTS, we show that the resulting estimator remains unbiased and that using one observable-measurement shot per sampled state is nearly optimal in terms of variance when the total number of circuit executions used to generate the Markov chain and measure observables is fixed. This result indicates that it is often more efficient to generate more QMETTS samples than to accurately estimate the expectation value for each individual pure state. We validate the proposed method numerically in a $(1+1)$-dimensional ${\mathbb{Z}}_2$ lattice gauge theory coupled to staggered fermions. Our results provide a gauge-invariant sampling framework for finite-temperature and finite-density quantum algorithms for lattice gauge theories.

The discrimination of quantum states is fundamental to quantum information processing. Inverse-squeezing Kennedy (IS-Kennedy) receivers can outperform the coherent-state binary phase-shift-keyed Helstrom benchmark at the same energy by converting transmitter-side squeezing into an effective coherent-state separation gain, without violating the Helstrom bound for the squeezed-state alphabet. This work investigates how squeezing mismatch degrades this mechanism. We show that imperfect inverse squeezing transforms the ideally nulled output into a residually squeezed state, thereby altering the photon-number statistics before detection. This residual-squeezing picture reveals a strong physical asymmetry between squeezing-magnitude and squeezing-phase mismatches. Magnitude mismatch produces an energy-independent error floor in the high-signal-energy regime, whereas phase mismatch generates a residual-squeezing term that grows with signal energy. In the small-residual-squeezing regime, this leads to a polynomial growth of the leading error contribution and a rapid collapse of the standard quantum limit advantage. We also identify a parity-step effect in photon-number-resolving detection: Because the nulled residual squeezed vacuum contains only even photon numbers, increasing detector resolution improves the high-energy robustness only when the effective saturation threshold crosses the next even photon number. These results identify phase locking as the dominant bottleneck for IS-Kennedy-type non-Gaussian receivers under unitary squeezing mismatch and provide design guidelines for robust squeezed-state quantum receivers.

Governed by the Nielsen-Ninomiya theorem, Weyl points (WPs) function as topological monopoles that cannot exist in isolation but must form charge-neutral assemblies in the momentum space of crystals. While these WPs are locally characterized by quantized chiral charges, the finite generating family governing their global assembly into a Weyl semimetal (WSM) phase remains undiscovered. Here, we resolve this by identifying “irreducible Weyl molecules” (IWMs) as the elementary, charge-neutral topological building blocks of WSMs. By rigorously imposing the constraints of 1651 magnetic space groups on minimal zero-sum chiral-charge sequences, we obtain exactly 16 crystallographically realizable IWMs. We establish a universal linear-combination principle, demonstrating that any crystallographically realizable charge-neutral chiral-node configuration $Y$ within $\left|C\right|\le 4$ is constructed from a linear superposition of these 16 generators $X_i$ with non-negative integer coefficients $n_i$, governed by $Y={\sum }_{i=1}^{16}{n}_i{X}_i$. Utilizing first-principles calculations on a predicted family of boron allotropes, we reveal that this superposition principle organizes the bulk nodal configurations and constrains the admissible end point connectivity of Fermi arcs, while the realized surface geometry remains dependent on termination, energy, and allowed inter-IWM reconstruction. Our work establishes a “periodic table” for WSMs, offering a general theoretical framework for the classification and rational design of Weyl complexes.

High-harmonic generation in solids enables probing of strong-field electron dynamics in condensed matter and the development of compact ultrafast light sources. Whereas most studies have focused on above-bandgap high-order harmonics, which are usually interpreted through short electron-hole trajectories that recombine within one optical cycle, the microscopic origin of low-order emission near the bandgap remains poorly understood. Here, we investigate near-bandgap harmonic generation in ZnO by combining semiconductor Bloch equations with a complex-time quantum-trajectory analysis. Our results indicate that these harmonics are not a continuation of the short trajectory. Rather, they originate from multiple-scattering trajectories, in which the electron-hole pair undergoes repeated Bragg scattering at the Brillouin-zone boundary and electron-hole reencounter near the $\mathrm{\Gamma }$ point before the actual recombination occurs. We identify that the imaginary part of the electron-hole displacement provides a practical diagnostic of the residual tunneling memory. Real-space electron-hole overlap alone does not imply coherent recombination unless the full complex displacement vanishes. These results clarify the microscopic picture of near-bandgap harmonic emission in ZnO and offer a framework for interpreting phase-resolved strong-field dynamics in solids.

We develop the semiconductor Wannier equations (SWEs), a real-time, real-space formulation of ultrafast light-matter dynamics in crystals, by deriving the equations of motion for the electronic reduced density matrix in a localized Wannier basis. Working in real space removes the structure-gauge ambiguities that hinder reciprocal-space semiconductor Bloch equations. Electron-electron interactions are included at the time-dependent Hartree plus static screened-exchange level. Decoherence is modeled with three complementary channels: pure dephasing, population relaxation, and distance-dependent real-space dephasing, providing physically grounded damping for strong-field phenomena such as high-harmonic generation. Conceptually, the SWEs bridge real-space semiclassical intuition with many-body solid-state optics, offering a numerically robust and gauge-clean alternative to reciprocal-space approaches for nonlinear optical response and attosecond spectroscopy in solids.

Many complex systems—be they financial, natural, or social—are composed of units—such as stocks, neurons, or agents—whose joint activity can be represented as a multivariate time series. An issue of both practical and theoretical importance concerns the possibility of inferring the presence of a static relationship between any two units solely from their dynamic behavior. The present contribution aims at tackling such an issue within the framework of traditional hypothesis testing: Briefly speaking, our suggestion is that of linking any two units if behaving in a sufficiently similar way. To achieve such a goal, we project a multivariate time series onto a signed graph by (1) comparing the empirical properties of the former with those expected under a suitable benchmark and (2) linking any two units with a positive (negative) edge in case the corresponding series shares a significantly large number of concordant (discordant) values. To define our benchmarks, we adopt an information-theoretic approach that is rooted into the constrained maximization of Shannon entropy, a procedure inducing an ensemble of multivariate time series that preserves some of the empirical properties on average, while randomizing everything else. We showcase the possible applications of our method by addressing one of the most timely issues in the domain of neurosciences, i.e., that of determining whether brain networks are frustrated or not, and, if so, to what extent. As our results suggest, this is indeed the case, with the major contribution to the underlying negative subgraph coming from the subcortical regions (and, to a lesser extent, from the limbic ones). At the mesoscopic level, the minimization of the Bayesian information criterion, instantiated with the signed stochastic block model, reveals that brain regions gather into modules aligning with the statistical variant of the relaxed balance theory.

Ponderomotive electron optics has attracted attention because structured optical fields provide round-lens functionalities, including negative lens power and negative spherical aberration, that are difficult to achieve with conventional Einzel and solenoid lenses. How ponderomotive lenses disperse with electron energy and whether that dispersion can be engineered for achromatization have remained largely unexplored. Here, we show that the transverse and longitudinal components of a vector optical field exhibit distinct energy dispersions because a relativistic correction modifies the effective lens action of the component polarized parallel to the electron velocity. In a radially polarized Bessel field coaxial with the electron beam, the two components form spatially colocated $J_1^2$- and $J_0^2$-type ponderomotive potentials whose relative weights depend on the electron energy, the Bessel cone angle, and the propagation direction of the light relative to the electrons. Using a local Abbe number defined in the energy domain, we find that this single field can operate as a self-achromatic round lens. We further construct zero-separation doublets—with a magnetic objective-lens model or an azimuthally polarized Bessel lens—that simultaneously cancel the first-order axial chromatic- and third-order spherical-aberration coefficients at a fixed electron-optical focal length, with the useful solutions occurring for counterpropagating light. Finite-aperture calculations at optical wavelengths of $1064\mathrm{nm}$ and $10.6\mu \mathrm{m}$ relate the achievable probe size to the required optical power, and at $10.6\mu \mathrm{m}$ they identify a low-energy, large-energy-spread regime in which the corrected doublets outperform the magnetic objective-lens model. The required optical power is compatible with demonstrated near-infrared ultrashort-pulse sources, so a single-pass proof-of-principle experiment is within reach.

The isomorphic property of strongly coupled three-dimensional (3D) Yukawa liquidlike fluids under steady shear is systematically investigated using nonequilibrium molecular dynamical simulations. It is discovered that, as the shear rate increases substantially, the shear viscosity $\eta$ and the radial distribution function $g\left(r\right)$ both exhibit excellent isomorphic scaling properties. The isomorphic scaling of shear viscosity is attributed to the dominant role of neighboring particles, whose averaged local configuration of $g\left(r\right)$ is invariant, even though 3D Yukawa fluids are continuously deformed and rearranged by the applied shear. Furthermore, it is found that the Stokes-Einstein relation is violated at higher shear rates because the diffusion coefficient $D$ is directional dependent and sensitive to the applied shear, i.e., not an isomorph invariant anymore.

Scattering processes are essential for understanding the structure of matter, yet their real-time dynamics remain challenging to simulate classically. Quantum computers offer a promising path toward efficient simulation of such physical systems. Here, we present a general and scalable framework for simulating meson scattering in lattice gauge theories on digital quantum hardware. Our approach addresses two key challenges: First, we introduce a symmetry-preserving quantum subspace expansion method for constructing high-fidelity meson creation operators across a wide range of coupling and momenta. Second, we design a quantum circuit for meson wave packet preparation using Givens rotations, improving accuracy while reducing circuit depth compared to existing approaches. We demonstrate the method in a ($1+1$)-dimensional ${\mathbb{Z}}_2$ gauge theory and explore meson scattering dynamics with tensor network simulations. We study both elastic and inelastic scattering and provide a comprehensive characterization of the scattering process in terms of energy transfer, entanglement entropy, and heavier particle production during the dynamics. Our work provides a scalable, nonvariational approach for simulating meson scattering on near-term quantum devices and offers a concrete strategy for probing nonperturbative dynamics in confining gauge theories.

We present a general framework for extracting conformal data from critical two-dimensional classical lattice models using finite-size tensor-network flow. The central idea is to identify, from transfer-matrix spectra, a self-consistent finite-size window together with a crossover scale that separates the finite-size-scaling regime from the finite-entanglement-scaling regime induced by bond-dimension truncation. Within this window, the central charge, scaling dimensions, and conformal spins can be estimated without requiring a unique critical fixed-point tensor or detailed prior knowledge of the underlying conformal field theory. We benchmark the framework using three tensor-network renormalization schemes for the critical two-dimensional Ising and three-state clock models. Across schemes, we find robust universal behavior below the crossover scale, enabling accurate extraction of conformal data up to relatively high conformal levels. The analysis also yields a natural operational definition of entanglement scaling for classical tensor-network calculations and, in turn, a complementary estimator of the central charge.

We propose and implement a quantum-informed reduction algorithm for the maximum independent set problem that integrates classical kernelization techniques with information extracted from quantum devices. Our larger framework consists of dedicated application, algorithm, and hardware layers, and easily generalizes to the maximum weight independent set problem. In this hybrid quantum-classical framework, which we call qReduMIS, the quantum computer is used as a coprocessor to inform classical reduction logic about frozen vertices that are likely (or unlikely) to be in large independent sets, thereby opening up the reduction space after removal of targeted subgraphs. We systematically assess the performance of qReduMIS based on experiments with up to 231 qubits run on Rydberg quantum hardware available through Amazon Braket. Our experiments show that qReduMIS can help address fundamental performance limitations faced by a broad set of (quantum) solvers including Rydberg quantum devices. We outline implementations of qReduMIS with alternative platforms, such as superconducting qubits or trapped ions, and we discuss potential future extensions.