As amorphous materials get jammed, both geometric and dynamic heterogeneity are observed. We investigate the correlation between the local geometric heterogeneity and local rearrangements in a slowly compressed bidisperse quasi-two-dimensional emulsion system. The compression is driven by evaporation of the continuous phase and causes the area packing fraction to increase from 0.88 to 0.99. We quantify the structural heterogeneity of the system using the radical Voronoi tessellation following the method of Rieser et al. [Phys. Rev. Lett. 116, 088001 (2016)]. We define two structural quantities characterizing local structure, the first of which considers nearest neighbors and the second of which includes information from second-nearest neighbors. We find that droplets in heterogeneous local regions are more likely to have local rearrangements. These rearrangements are generally T1 events where two droplets converge toward a void, and two droplets move away from the void to make room for the converging droplets. Thus, the presence of the voids tends to orient the T1 events. The presence of a correlation between the structural quantities and the rearrangement dynamics remains qualitatively unchanged over the entire range of packing fractions observed.

Resetting is a renewal mechanism in which a process is intermittently repeated after a random or fixed time. This simple act of stop and repeat profoundly influences the behavior of a system as exemplified by the emergence of nonequilibrium properties and expedition of search processes. Herein we explore the ramifications of stochastic resetting in the context of a single-file system called random average process (RAP) in one dimension. In particular, we focus on the dynamics of tracer particles and analytically compute the variance, equal time correlation, autocorrelation, and unequal time correlation between the positions of different tracer particles. Our study unveils that resetting gives rise to rather different behaviors depending on whether the particles move symmetrically or asymmetrically. For the asymmetric case, the system for instance exhibits a long-range correlation which is not seen in absence of the resetting. Similarly, in contrast to the reset-free RAP, the variance shows distinct scalings for symmetric and asymmetric cases. While for the symmetric case, it decays (towards its steady value) as $\sim e^{-rt}/\sqrt{t}$, we find $\sim t{e}^{-rt}$ decay for the asymmetric case ($r$ being the resetting rate). Finally, we examine the autocorrelation and unequal time correlation in the steady state and demonstrate that they obey interesting scaling forms at late times. All our analytical results are substantiated by extensive numerical simulations.

In quantum systems, entropy production is typically defined as the quantum relative entropy between two states. This definition provides an upper bound for any flux (of particles, energy, entropy, etc.) of bounded observables, which proves especially useful near equilibrium. However, this bound tends to be irrelevant in general nonequilibrium situations. We propose a new upper bound for such fluxes in terms of quantum relative entropy, applicable even far from equilibrium and in the strong coupling regime. Additionally, we compare this bound with Monte Carlo simulations of random qubits with coherence, as well as with a model of two interacting nuclear spins.

We extend the $N$-intertwined mean-field approximation (NIMFA) for the susceptible-infectious-susceptible (SIS) epidemiological process to time-varying networks. Processes on time-varying networks are often analyzed under the assumption that the process and network evolution happen on different timescales. This approximation is called timescale separation. We investigate timescale separation between disease spreading and topology updates of the network. We introduce the transition times $\underline{\mathrm{T}}\left(r\right)$ and $\overline{\mathrm{T}}\left(r\right)$ as the boundaries between the intermediate regime and the annealed (fast changing network) and quenched (static network) regimes, respectively, for a fixed accuracy tolerance $r$. By analyzing the convergence of static NIMFA processes, we analytically derive upper and lower bounds for $\overline{\mathrm{T}}\left(r\right)$. Our results provide insights and bounds on the time of convergence to the steady state of the static NIMFA SIS process. We show that, under our assumptions, the upper-transition time $\overline{\mathrm{T}}\left(r\right)$ is almost entirely determined by the basic reproduction number $R_0$ of the network. The value of the upper-transition time $\overline{\mathrm{T}}\left(r\right)$ around the epidemic threshold is large, which agrees with the current understanding that some real-world epidemics cannot be approximated with the aforementioned timescale separation.

In recent years hypergraphs have emerged as a powerful tool to study systems with multibody interactions which cannot be trivially reduced to pairs. While highly structured methods to generate synthetic data have proved fundamental for the standardized evaluation of algorithms and the statistical study of real-world networked data, these are scarcely available in the context of hypergraphs. Here we propose a flexible and efficient framework for the generation of hypergraphs with many nodes and large hyperedges, which allows specifying general community structures and tune different local statistics. We illustrate how to use our model to sample synthetic data with desired features (assortative or disassortative communities, mixed or hard community assignments, etc.), analyze community detection algorithms, and generate hypergraphs structurally similar to real-world data. Overcoming previous limitations on the generation of synthetic hypergraphs, our work constitutes a substantial advancement in the statistical modeling of higher-order systems.

From colloid suspension to particle aggregation in protoplanetary formation, electrostatic attraction and repulsion between particles is a key mechanism behind the aggregation and clustering of particles. Although most studies have focused on canonical spherical particles, it remains unclear how nonspherical and rough dielectric particles interact and whether the complicated interplay between roughness and charge distribution affects their force couplings. Here a boundary-element method model was leveraged to study electrostatic interactions between charged dielectric particles with modular, axisymmetric surface features. Charge accumulation at convex surface asperities decreases the strength of electrostatic interactions between particles, and the sensitivity of the electrostatic force to the particle surface roughness and orientation is especially apparent at small particle separations. Surface interactions between the particle near-contact regions were isolated to determine the degree that near-contact interactions dictate the relationship between the net electrostatic force and the particle roughness and orientation. A correction factor $\mathrm{\Delta }F$ is introduced to recover higher order dielectric effects from a low order analytical model. Finally, implications of surface charge asymmetries produced for different particle orientations and surface roughnesses on the long-standing problem of triboelectrification are discussed.

In this work we propose a modified Chord Length Sampling (CLS) algorithm, endowed with two layers of “memory effects,” aimed at solving particle transport problems in one-dimensional spatially nonhomogeneous Markov media. CLS algorithms are a family of Monte Carlo methods which account for the stochastic nature of the media by sampling on-the-fly the random interfaces between material phases during the particle propagation. The possibility for the particles to remember the last crossed interfaces increases the accuracy of these models with respect to reference solutions obtained by solving the Boltzmann equation on a large number of realizations of the Markov media. In previous investigations, CLS models with memory have been tested exclusively for spatially uniform stochastic media: in this paper we extend this class of Monte Carlo methods to the case of spatially nonhomogeneous configurations. The effectiveness and the robustness of the modified CLS are probed considering several benchmark problems with varying material cross sections and Markov media densities. The obtained results are a stepping stone towards a generalization to three-dimensional models.

An information engine based on a two-level system in contact with a thermal reservoir is studied analytically. The model incorporates delay time between the measurement of the state of the system and the feedback. The engine efficiency and work extracted per cycle are studied as a function of delay time and energy spacing between the two levels. It is found that the range of delay time over which one can extract work from the information engine increases with temperature. For delay times comparable to the relaxation time, efficiency and work per cycle are maxima when $k_{B}T\approx 2U_0$, the energy difference between the levels. The generalized Jarzynski equality and the generalized integral fluctuation theorem are explicitly verified for the model. The results from the model are compared with the simulation results for a feedback engine based on a particle moving in a one-dimensional square potential. The variation of efficiency, work per cycle, and efficacy with the delay time is compared using relaxation time in the two-level model as the fitting parameter, leading to a good fit.

Our understanding of the three basic states of matter (solids, liquids, and gases) is based on temperature and pressure phase diagrams with three phase transition lines: solid-gas, liquid-gas, and solid-liquid lines. There are analytical expressions $P\left(T\right)$ for the first two lines derived on a purely general-theoretical thermodynamic basis. In contrast, there exists no similar function for the third, melting, line (ML). Here, we develop a general two-phase theory of MLs and their analytical form. This theory predicts the parabolic form of the MLs for normal melting, relates the MLs to thermal and elastic properties of liquid and solid phases, and quantitatively agrees with experimental MLs in different system types. We show that the parameters of the ML parabola are governed by fundamental physical constants. In this sense, parabolic MLs possess universality across different systems.

We consider a general class of limit cycle oscillators driven by an additive Gaussian white noise. Based on the separation of timescales, we construct the equation of motion for slow dynamics after appropriate averaging over the fast motion. The equation for slow motion whose coefficients are modified by noise characteristics is solved to obtain the analytic solution in the long time limit. We show that with increase of noise strength, the loop area of the limit cycle decreases until a critical value is reached, beyond which the limit cycle collapses. We determine the noise threshold from the condition for removal of secular divergence of the perturbation series and work out two explicit examples of Van der Pol and Duffing-Van der Pol oscillators for corroboration between the theory and numerics.

We consider the system of the Rosenzweig-MacArthur equations with one consumer and two resources. Recently, the model has been generalized by including an optimization of the consumption rates ${\beta }_i$ [P. Gawroński et al., Chaos 32, 093121 (2022)]. Also, we have assumed that ${\beta }_1+{\beta }_2=1$, which reflects the limited amount of time that can be devoted to a given type of resource. Here we investigate the transition to the phase where one of the resources becomes extinct. The goal is to show that the stability of the phase with two resources strongly depends on the initial value of ${\beta }_i$. Our second goal is to demonstrate signatures of transient chaos in the time evolution.

The effect of phase-lag in pairwise interactions has been a topic of great interest for a while. However, real-world systems often have interactions that are beyond pairwise and can be modeled using simplicial complexes. We show that the inclusion of higher-order interactions in phase-lagged coupled Kuramoto oscillators shifts the critical point at which first-order transition from a cluster synchronized state to an incoherent state takes place. Considering the polar coordinates, we obtain the rotation frequency of the clusters, which turns out to be a function of the phase-lag parameter. In turn, the phase- lag can be used as a control parameter to achieve a desired cluster frequency. Moreover, in the thermodynamic limit, by employing the Ott-Antonsen approach we derive a reduced equation for the order parameter measuring cluster synchronization and progress further through the self-consistency method to obtain a closed form of the order parameter measuring global synchronization which was lacking in the Ott-Antonsen approach.

Previous studies have shown that the interiors of proteins are densely packed, reaching packing fractions that are as large as those found for static packings of individual amino-acid-shaped particles. How can the interiors of proteins take on such high packing fractions given that amino acids are connected by peptide bonds and many amino acids are hydrophobic with attractive interactions? We investigate this question by comparing the structural and mechanical properties of collapsed attractive disk-shaped bead-spring polymers to those of three reference systems: static packings of repulsive disks, of attractive disks, and of repulsive disk-shaped bead-spring polymers. We show that the attractive systems quenched to temperatures below the glass transition $T\ll T_g$ and static packings of both repulsive disks and bead-spring polymers possess similar interior packing fractions. Previous studies have shown that static packings of repulsive disks are isostatic at jamming onset, i.e., the number of interparticle contacts $N_c$ matches the number of degrees of freedom, which strongly influences their mechanical properties. We find that repulsive polymer packings are hypostatic at jamming onset (i.e., with fewer contacts than degrees of freedom) but are effectively isostatic when including stabilizing quartic modes, which give rise to quartic scaling of the potential energy with displacements along these modes. While attractive disk and polymer packings are often considered hyperstatic with excess contacts over the isostatic number, we identify a definition for interparticle contacts for which they can also be considered as effectively isostatic. As a result, we show that the mechanical properties (e.g., scaling of the potential energy with excess contact number and low-frequency contribution to the density of vibrational modes) of weakly attractive disk and polymer packings are similar to those of isostatic repulsive disk and polymer packings. Our results demonstrate that static packings generated via attractive collapse or compression of repulsive particles possess similar structural and mechanical properties.

Island nucleation and growth play an important role in thin-film growth. One quantity of particular interest is the exponent $\chi$, which describes the dependence of the saturation island density $N_{\text{sat}}\sim {(D_h/F)}^{-\chi }$ on the ratio $D_h/F$ of the monomer hopping rate $D_h$ to the deposition rate $F$. While standard rate equation (RE) theory predicts that $\chi =i/(i+2)$ (where $i$ is the critical island size), more recently it has been predicted that in the presence of a strong barrier to the attachment of monomers to islands, a significantly larger value $\chi =2i/(i+3)$ may be observed. While this prediction has recently been tested using kinetic Monte Carlo simulations for the case of irreversible growth corresponding to $i=1$, it has not been tested for the case of reversible island growth corresponding to $i>1$. Here we present a mean-field self-consistent RE method which we have used to study the dependence of the effective value of $\chi$ on $D_h/F$ and barrier-strength for $i=1,2,3$, and 6. Both the no-nucleation-barrier case in which there exists a barrier for monomers to attach to islands larger than the critical island size (but not to smaller islands) and the nucleation-barrier case in which there is a barrier for monomers to attach to islands of all sizes are studied. In all cases, we find that the existence of attachment barriers significantly increases the effective value of $\chi$ for a given barrier strength. In addition, for $i=1$ we find good agreement between our extrapolated asymptotic value of $\chi$ and the theoretical strong-barrier prediction both with and without a nucleation barrier. In contrast, for $i>1$ the value of $\chi$ is significantly larger in the presence of a nucleation barrier than in its absence. In particular, while an asymptotic analysis of our results for $i>1$ also leads to excellent agreement with the strong barrier prediction in the presence of a nucleation barrier, in the absence of a nucleation barrier the asymptotic values are significantly lower.

We study spectral correlations in many-body quantum mixtures of fermions, bosons, and qubits with periodically kicked spreading and mixing of species. We take two types of mixing, namely, Jaynes-Cummings and Rabi, respectively, satisfying and breaking the conservation of a total number of species. We analytically derive the generating Hamiltonians whose spectral properties determine the spectral form factor in the leading order. We further analyze the system-size $\left(L\right)$ scaling of Thouless time $t^{*}$, beyond which the spectral form factor follows the prediction of random matrix theory. The $L$ dependence of $t^{*}$ crosses over from $lnL$ to $L^2$ with an increasing Jaynes-Cummings mixing between qubits and fermions or bosons in a finite-size chain, and it finally settles to $t^{*}\propto \mathcal{O}\left(L^2\right)$ in the thermodynamic limit for any mixing strength. The Rabi mixing between qubits and fermions leads to $t^{*}\propto \mathcal{O}(lnL)$, previously predicted for single species of qubits or fermions without total-number conservation.

We study collective dynamics of networks of mutually coupled identical Lorenz oscillators near a subcritical Hopf bifurcation. Such systems exhibit induced multistable behavior with interesting spatiotemporal dynamics including synchronization, desynchronization, and chimera states. For analysis, we first consider a ring topology with nearest-neighbor coupling and find that the system may exhibit intermittent behavior due to the complex basin structures and dynamical frustration, where temporal dynamics of the oscillators in the ensemble switches between different attractors. Consequently, different oscillators may show a dynamics that is intermittently synchronized (or desynchronized), giving rise to intermittent chimera states. The behavior of the intermittent laminar phases is characterized by the characteristic time spent in the synchronization manifold, which decays as a power law. Such intermittent dynamics is quite general and is also observed in an ensemble of a large number of oscillators arranged in variety of network topologies including nonlocal, scale-free, random, and small-world networks.

Because of its plasticity, a densely packed colloidal suspension, called a paste, remembers directions of its motion, such as vibration and flow. When it dries, primary desiccation cracks propagate in a direction perpendicular to the direction of its vibrational motion and parallel to the direction of its flow motion, which are memory effects of paste. Application of an oscillatory shear strain to a paste using a rheometer reveals that the transition from memory of vibration to that of flow is induced when the amplitude of the oscillatory shear strain exceeds a threshold value. Findings also demonstrate that oscillatory motion is unnecessary, i.e., merely a large shear deformation is sufficient for the memory of flow. Therefore, only oscillatory shear strain with a small amplitude is necessary for memory of vibration; large shear deformation is sufficient for memory of flow.