Strong zero modes (SZMs) are conserved operators localized at the edges of certain quantum spin chains, which give rise to long coherence times of edge spins. Here we define and analyze analogous operators in one-dimensional classical stochastic systems. For concreteness, we focus on chains with single occupancy and nearest-neighbor transitions, in particular particle hopping and pair creation and annihilation. For integrable choices of parameters we find the exact form of the SZM operators. Being in general nondiagonal in the classical basis, the dynamical consequences of stochastic SZMs are very different from those of their quantum counterparts. We show that the presence of a stochastic SZM is manifested through a class of exact relations between time-correlation functions, absent in the same system with periodic boundaries.

The fluctuation relation, a milestone of modern thermodynamics, is only established when a set of fundamental currents can be measured. Here we prove that it also holds for systems with hidden transitions if observations are carried “at their own beat,” that is, by stopping the experiment after a fixed number of visible transitions, rather than the elapse of an external clock time. This suggests that thermodynamic symmetries are more resistant to the loss of information when described in the space of transitions.

Quantum heat engines are often discussed under the weak-coupling assumption that the interaction between the system and the reservoirs is negligible. Although this setup is easier to analyze, this assumption cannot be justified on the quantum scale. In this study, a quantum Otto cycle model that can be generally applied without the weak-coupling assumption is proposed. We replace the thermalization process in the weak-coupling model with a process comprising thermalization and decoupling. The efficiency of the proposed model is analytically calculated and indicates that, when the contribution of the interaction terms is neglected in the weak-interaction limit, it reduces to that of the earlier model. The sufficient condition for the efficiency of the proposed model not to surpass that of the weak-coupling model is that the decoupling processes of our model have a positive cost. Moreover, the relation between the interaction strength and the efficiency of the proposed model is numerically examined by using a simple two-level system. Furthermore, we show that our model's efficiency can surpass that of the weak-coupling model under particular cases. From analyzing the majorization relation, we also find a design method of the optimal interaction Hamiltonians, which are expected to provide the maximum efficiency of the proposed model. Under these interaction Hamiltonians, the numerical experiment shows that the proposed model achieves higher efficiency than that of its weak-coupling counterpart.

Determining the universality class of a system exhibiting critical phenomena is one of the central problems in physics. There are several methods to determine this universality class from data. As methods to collapse plots onto scaling functions, polynomial regression, which is less accurate, and Gaussian process regression, which provides high accuracy and flexibility but is computationally expensive, have been proposed. In this paper, we propose a regression method using a neural network. The computational complexity is linear only in the number of data points. We demonstrate the proposed method for the finite-size scaling analysis of critical phenomena in the two-dimensional Ising model and bond percolation problem to confirm the performance. This method efficiently obtains the critical values with accuracy in both cases.

We study complexity in a spin system with infinite-range interaction, via the paradigmatic Lipkin-Meshkov-Glick (LMG) model, in the thermodynamic limit. Exact expressions for the Nielsen complexity (NC) and the Fubini-Study complexity (FSC) are derived, which helps us to establish several distinguishing features compared to complexity in other known spin models. In a time-independent LMG model, close to phase transition, the NC diverges logarithmically, much like the entanglement entropy. Remarkably, however, in a time-dependent scenario, this divergence is replaced by a finite discontinuity, as we show by using the Lewis-Riesenfeld theory of time-dependent invariant operators. The FSC of a variant of the LMG model shows different behavior compared to quasifree spin models. Namely, it diverges logarithmically when the target (or reference) state is near the separatrix. Numerical analysis indicates that this is due to the fact that geodesics starting with arbitrary boundary conditions are “attracted” toward the separatrix and that near this line, a finite change in the affine parameter of the geodesic produces an infinitesimal change of the geodesic length. The same divergence is shared by the NC of this model as well.

Single-file diffusion refers to the motion of diffusive particles in narrow channels, so that they cannot bypass each other. This constraint leads to the subdiffusion of a tagged particle, called the tracer. This anomalous behavior results from the strong correlations that arise in this geometry between the tracer and the surrounding bath particles. Despite their importance, these bath-tracer correlations have long remained elusive, because their determination is a complex many-body problem. Recently, we have shown that, for several paradigmatic models of single-file diffusion such as the simple exclusion process, these bath-tracer correlations obey a simple exact closed equation. In this paper, we provide the full derivation of this equation, as well as an extension to another model of single-file transport: the double exclusion process. We also make the connection between our results and the ones obtained very recently by several other groups and which rely on the exact solution of different models obtained by the inverse scattering method.

Bose-Einstein condensates (BECs) in periodic potentials generate interesting physics on the instabilities of Bloch states. The lowest-energy Bloch states of BECs in pure nonlinear lattices are dynamically and Landau unstable, which breaks down BEC superfluidity. In this paper we propose to use an out-of-phase linear lattice to stabilize them. The stabilization mechanism is revealed by the averaged interaction. We further incorporate a constant interaction into BECs with mixed nonlinear and linear lattices and reveal its effect on the instabilities of Bloch states in the lowest band.

Inferring the coupling direction from measured time series of complex systems is challenging. We propose a state-space-based causality measure obtained from cross-distance vectors for quantifying interaction strength. It is a model-free noise-robust approach that requires only a few parameters. The approach is applicable to bivariate time series and is resilient to artefacts and missing values. The result is two coupling indices that quantify coupling strength in each direction more accurately than the already established state-space measures. We test the proposed method on different dynamical systems and analyze numerical stability. As a result, a procedure for optimal parameter selection is proposed, circumventing the challenge of determining the optimal embedding parameters. We show it is robust to noise and reliable in shorter time series. Moreover, we show that it can detect cardiorespiratory interaction in measured data. A numerically efficient implementation is available at https://repo.ijs.si/e2pub/cd-vec.

Cell migration is frequently modeled using on-lattice agent-based models (ABMs) that employ the excluded volume interaction. However, cells are also capable of exhibiting more complex cell-cell interactions, such as adhesion, repulsion, pulling, pushing, and swapping. Although the first four of these have already been incorporated into mathematical models for cell migration, swapping has not been well studied in this context. In this paper, we develop an ABM for cell movement in which an active agent can “swap” its position with another agent in its neighborhood with a given swapping probability. We consider a two-species system for which we derive the corresponding macroscopic model and compare it with the average behavior of the ABM. We see good agreement between the ABM and the macroscopic density. We also analyze the movement of agents at an individual level in the single-species as well as two-species scenarios to quantify the effects of swapping on an agent's motility.

Large-scale data on single-cell gene expression have the potential to unravel the specific transcriptional programs of different cell types. The structure of these expression datasets suggests a similarity with several other complex systems that can be analogously described through the statistics of their basic building blocks. Transcriptomes of single cells are collections of messenger RNA abundances transcribed from a common set of genes just as books are different collections of words from a shared vocabulary, genomes of different species are specific compositions of genes belonging to evolutionary families, and ecological niches can be described by their species abundances. Following this analogy, we identify several emergent statistical laws in single-cell transcriptomic data closely similar to regularities found in linguistics, ecology, or genomics. A simple mathematical framework can be used to analyze the relations between different laws and the possible mechanisms behind their ubiquity. Importantly, treatable statistical models can be useful tools in transcriptomics to disentangle the actual biological variability from general statistical effects present in most component systems and from the consequences of the sampling process inherent to the experimental technique.

The dynamics of a two-dimensional autophoretic disk is quantified as a minimal model for the chaotic trajectories undertaken by active droplets. Via direct numerical simulations, we show that the mean-square displacement of the disk in a quiescent fluid is linear at long times. Surprisingly, however, this apparently diffusive behavior is non-Brownian, owing to strong cross correlations in the displacement tensor. The effect of a shear flow field on the chaotic motion of an autophoretic disk is examined. Here, the stresslet on the disk is chaotic for weak shear flows; a dilute suspension of such disks would exhibit a chaotic shear rheology. This chaotic rheology is quenched first into a periodic state and ultimately a steady state as the flow strength is increased.

This paper complements a previous study of the isotropic and nematic phases of the Gay-Berne liquid-crystal model [Mehri et al., Phys. Rev. E 105, 064703 (2022)] with a study of its smectic-$B$ phase found at high density and low temperatures. We find also in this phase strong correlations between the virial and potential-energy thermal fluctuations, reflecting hidden scale invariance and implying the existence of isomorphs. The predicted approximate isomorph invariance of the physics is confirmed by simulations of the standard and orientational radial distribution functions, the mean-square displacement as a function of time, and the force, torque, velocity, angular velocity, and orientational time-autocorrelation functions. The regions of the Gay-Berne model that are relevant for liquid-crystal experiments can thus fully be simplified via the isomorph theory.

Evaporation of a liquid layer on a substrate is examined without the often-used isothermality assumption, i.e., temperature variations are accounted for. Qualitative estimates show that nonisothermality makes the evaporation rate depend on the conditions at which the substrate is maintained. If it is thermally insulated, evaporative cooling dramatically slows evaporation down; the evaporation rate tends to zero with time and cannot be determined by measuring the external parameters only. If, however, the substrate is maintained at a fixed temperature, the heat flux coming from below sustains evaporation at a finite rate, deducible from the fluid's characteristics, relative humidity, and the layer's depth. The qualitative predictions are quantified using the diffuse-interface model applied to a liquid evaporating into its own vapor.

A parametric instability of an incompressible, viscous, and Boussinesq fluid layer bounded between two parallel planes is investigated numerically. The layer is assumed to be inclined at an angle with the horizontal. The planes bounding the layer are subjected to a time-periodic heating. Above a threshold value, the temperature gradient across the layer leads to an instability of an initially quiescent state or a parallel flow, depending upon the angle of inclination. Floquet analysis of the underlying system reveals that under modulation, the instability sets in as a convective-roll pattern executing harmonic or subharmonic temporal oscillations, depending upon the modulation, the angle of inclination, and the Prandtl number of the fluid. Under modulation, the onset of the instability is in the form of one of two spatial modes: the longitudinal mode and the transverse mode. The value of the angle of inclination for the codimension-2 point is found to be a function of the amplitude and the frequency of modulation. Furthermore, the temporal response is harmonic, or subharmonic, or bicritical depending upon the modulation. The temperature modulation offers good control of time-periodic heat and mass transfer in the inclined layer convection.

We have performed the modal and nonmodal stability analyses of a gravity-driven three-dimensional viscous incompressible fluid flowing over an inclined plane in the presence of a uniform electric field acting normal to the plane at infinity. The time evolution equations are derived for normal velocity, normal vorticity, and fluid surface deformation, respectively, and solved numerically by using the Chebyshev spectral collocation method. The modal stability analysis demonstrates the existence of three unstable regions for the surface mode in the wave number plane at the lower value of the electric Weber number. However, these unstable regions coalesce and magnify as the electric Weber number rises. By contrast, there exists only one unstable region for the shear mode in the wave number plane, which attenuates slightly with an increase in the value of the electric Weber number. But both the surface and shear modes are stabilized in the presence of the spanwise wave number, where the long-wave instability shifts towards the finite wavelength instability as the spanwise wave number rises. On the other hand, the nonmodal stability analysis reveals the existence of transient disturbance energy growth, the maximum value of which intensifies slightly with an increase in the value of the electric Weber number.

The numerical instability of the lattice Boltzmann method (LBM) at high Mach or high Reynolds number flow is well identified, and it remains a major barrier to its application in more complex configurations such as moving geometries. This work combines the compressible lattice Boltzmann model with rotating overset grids (the so-called Chimera method, sliding mesh, or moving reference frame) for high Mach flows. This paper proposes to use the compressible hybrid recursive regularized collision model with fictitious forces (or inertial forces) in a noninertial rotating reference frame. Also, polynomial interpolations are investigated, which allow fixed inertial and rotating noninertial grids to communicate with each other. We suggest a way to effectively couple the LBM with the MUSCL-Hancock scheme in the rotating grid, which is needed to account for thermal effect of compressible flow. As a result, this approach is demonstrated to have an extended Mach stability limit for the rotating grid. It also demonstrates that this complex LBM scheme can maintain the second-order accuracy of the classic LBM by appropriately using numerical methods like polynomial interpolations and the MUSCL-Hancock scheme. Furthermore, the method shows a very good agreement on aerodynamic coefficients compared to experiments and the conventional finite-volume scheme. This work presents a thorough academic validation and error analysis of the LBM for simulating moving geometries in high Mach compressible flows.

Recently the phase-field crystal method has attracted considerable attention because it can simulate the atomic behavior of a system on a diffusive timescale. In this study an atomistic simulation model is proposed, which is an extension of the cluster-activation method (CAM) from discrete to continuous space. This approach, called the continuous CAM, can simulate various physical phenomena of atomistic systems on diffusive timescales and employs well-defined atomistic properties, such as interatomic interaction energies, as the main input parameters. The versatility of the continuous CAM was investigated by performing simulations of crystal growth in an undercooled melt, homogeneous nucleation during solidification, and formation of grain boundaries in pure metal.

F. Ferretti et al. [Phys. Rev. E 105, 044133 (2022)] show that time discretization of linear Gaussian continuous-time stochastic processes are either first-order Markov processes or non-Markovian ones. Specializing to ARMA(2,1) processes, they propose a general redundantly parametrized form for a stochastic differential equation giving rise to this dynamics as well as a candidate nonredundant parametrization. However, the latter does not give rise to the full range of possible dynamics allowed by the former. I propose an alternative nonredundant parametrization which does.

Several types of stochastic dynamics can be modeled as a continuous-time Markov jump process among a finite number of sites. Within such framework, we face the problem of getting an upper bound on the average residence time of the system in a given site $\beta$ (i.e., the average lifetime of the site) if what we can observe is only the permanence of the system in an adjacent site $\alpha$ and the occurrence of the transitions $\alpha \to \beta$. Supposing to have a long time record of this partial monitoring of the network under steady-state conditions, we show that an upper bound on the average time spent in the unobserved site can indeed be given. The bound is formally proved, tested by means of simulations, and illustrated for a multicyclic enzymatic reaction scheme.