The statistical analysis of data stemming from dynamical systems, including, but not limited to, time series, routinely relies on the estimation of information theoretical quantities, most notably Shannon entropy. To this purpose, possibly the most widespread tool is provided by the so-called plug-in estimator, whose statistical properties in terms of bias and variance were investigated since the first decade after the publication of Shannon's seminal works. In the case of an underlying multinomial distribution, while the bias can be evaluated by knowing support and data set size, variance is far more elusive. The aim of the present work is to investigate, in the multinomial case, the statistical properties of an estimator of a parameter that describes the variance of the plug-in estimator of Shannon entropy. We then exactly determine the probability distributions that maximize that parameter. The results presented here allow one to set upper limits to the uncertainty of entropy assessments under the hypothesis of memoryless underlying stochastic processes.

Mutation and drift play opposite roles in genetics. While mutation creates diversity, drift can cause gene variants to disappear, especially when they are rare. In the absence of natural selection and migration, the balance between the drift and mutation in a well-mixed population defines its diversity. The Moran model captures the effects of these two evolutionary forces and has a counterpart in social dynamics, known as the voter model with external opinion influencers. Two extreme outcomes of the voter model dynamics are consensus and coexistence of opinions, which correspond to low and high diversity in the Moran model. Here we use a Shannon's information-theoretic approach to characterize the smooth transition between the states of consensus and coexistence of opinions in the voter model. Mapping the Moran into the voter model, we extend the results to the mutation-drift balance and characterize the transition between low and high diversity in finite populations. Describing the population as a network of connected individuals, we show that the transition between the two regimes depends on the network topology of the population and on the possible asymmetries in the mutation rates.

A broad range of dynamical systems involve multibody interactions, or group interactions, which may not be encoded in traditional graphical structures. In this work, we focus on a canonical example from opinion dynamics, namely the majority rule, and we investigate the possibility to represent and analyze the system by means of hypergraphs. We explore the formation of consensus, and we restrict our attention to interaction groups of size 3 in order to simplify our analysis from a combinatorial perspective. We propose different types of hypergraph models, incorporating modular structure or mean-field heterogeneity, and we recast the dynamics in terms of Fokker-Planck equations, which allows us to predict the transient dynamics toward consensus. Numerical simulations show a very good agreement between the stochastic dynamics and theoretical predictions for large population sizes.

Olfactory systems use a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. We propose a method of decoding such distributed representations by exploiting a statistical fact: Receptors that do not respond to an odor carry more information than receptors that do because they signal the absence of all odorants that bind to them. Thus, it is easier to identify what the odor is not rather than what the odor is. For realistic numbers of receptors, response functions, and odor complexity, this method of elimination turns an underconstrained decoding problem into a solvable one, allowing accurate determination of odorants in a mixture and their concentrations. We construct a neural network realization of our algorithm based on the structure of the olfactory pathway.

It is generally thought that persistent firing of neurons in the prefrontal cortex underlies working memory. Previous studies have focused on the influence of recurrent synaptic connectivity in local circuits on memory storage. Given neurons in the neocortex are extensively connected, individual neural circuits should receive synaptic inputs from other areas. Here we explore how background synaptic inputs (BSIs) modulate the visuospatial working memory in an oculomotor delayed response task. In a local recurrent network composed of pyramidal cells and interneurons, a bump attractor persists across the delay period, encoding the cue location. Under independent BSIs, the spontaneous network state before the cue presentation can be classified as inactive, active, or overactive, occurring successively with increasing the BSI strength, and the active state facilitates the memory storage. Under spatially correlated BSIs, optimal scenarios, in terms of accuracy of representation and resistance to distraction, involve the BSIs with intermediate strength and low correlation or high strength and moderate correlation. Our results demonstrate how the memory storage is regulated via tuning the balance between local excitation and global inhibition in the network. The current work reveals the functional importance of background input and suggests that robust memory storage could be accomplished over a variety of network states.

We study strain-controlled plastic deformation of crystalline solids via two-dimensional discrete dislocation dynamics simulations. To this end, we characterize the average stress-strain curves as well as the statistical properties of strain bursts and the related stress drops as a function of the imposed strain rate and the stiffness of the specimen-machine system. The dislocation system exhibits strain-rate sensitivity such that a larger imposed strain rate results in a higher average stress at a given strain. In the limit of small strain rate and driving spring stiffness, the sizes and durations of the dislocation avalanches are power law distributed up to a cutoff scale, and exhibit temporally asymmetric average shapes. We discuss the dependence of the results on the driving parameters and compare our results to those from previous simulations where quasistatic stress-controlled loading was used.

We use a nonrelativistic average-atom model to calculate carbon ionization at megabar and gigabar pressures. The pressure is calculated using the stress-tensor method. The electronic electrical conductivity is also considered using the Kubo-Greenwood approach. Comparisons are made with quantum molecular dynamic simulations. A good agreement is obtained for the pressure between the average-atom model and the quantum molecular dynamic simulations in the regime of gigabar pressures. However, the discrepancy already seen with the PURGATORIO code for the average ionization deduced from the quantum molecular dynamic simulations is also observed here with the present average-atom model. Excellent agreement with the PURGATORIO code is found for the average ionization.

Based on a continuous internal energy state variable, we propose an explicit, fully nonlinear Boltzmann collision operator for the evolution of the distribution function describing a polyatomic gas with a constant heat capacity. The particle interaction is a polyatomic generalization of the variable hard-sphere model, used in a recent rigorous mathematical analysis, and includes frozen collisions. The model is consistent with the monatomic case and allows easy evaluations for moment equations and the Chapman-Enskog expansion. Using a publicly available computer algebra code we can explicitly compute nonlinear production terms for macroscopic systems of moments. The range of Prandtl number values recovers the Eucken formula for a specific choice of frozen collisions.

The application of existing semigrand canonical ensemble Monte Carlo algorithms to alloys requires the chemical potential difference values between pairs of atomic species in the alloys as inputs. However, finding the appropriate values for a target system at a desired temperature and bulk composition is a time-consuming task consisting of multiple test runs to determine the chemical potential differences. This problem becomes more serious when dealing with systems containing three or more atomic species, such as medium- and high-entropy alloys, due to the increase of the number of chemical potential differences that need to be calculated. Here we propose a method for sampling from the semigrand canonical ensemble that relies on energy databases acting as an external atomic reservoir at the desired temperature and composition. Given these energy databases, the desired bulk composition and corresponding chemical potential differences can be satisfied in a “single” Monte Carlo simulation. Moreover, the energy databases shed light on the underlying energetics of alloys, reflecting their local chemical ordering. We demonstrate the validity of this method using analyses of segregation isotherms at grain boundaries and dislocations in two alloy systems: Fe–1-at.-$\%$-Si and NiCoCr medium-entropy alloy. We also discuss the possibly relevant information contained in such energy databases.

Swimming bacteria in passive nematics in the form of lyotropic liquid crystals are defined as a new class of active matter known as living liquid crystals in recent studies. It has also been shown that liquid crystal solutions are promising candidates for trapping and detecting bacteria. We ask the question, can a similar class of matter be designed for background nematics which are also active? Hence, we developed a minimal model for the mixture of polar particles in active nematics. It is found that the active nematics in such a mixture are highly sensitive to the presence of polar particles and show the formation of large scale higher order structures for a relatively low polar particle density. Upon increasing the density of polar particles, different phases of active nematics are found and it is observed that the system shows two phase transitions. The first phase transition is a first order transition from quasi-long-ranged ordered active nematics to disordered active nematics with larger scale structures. On further increasing density of polar particles, the system transitions to a third phase, where polar particles form large, mutually aligned clusters. These clusters sweep the whole system and enforce local order in the nematics. The current study can be helpful for detecting the presence of very low densities of polar swimmers in active nematics and can be used to design and control different structures in active nematics.

We study the effect of gravity on the synchronization of two coupled buoyancy-induced turbulent flames by recurrence-based analysis and machine learning. A significant change from nearly complete synchronization in the near field to partial synchronization appears in the far field under low gravity. The synchronized state is gradually lost with increasing gravity level. These results are clearly identified from cross recurrence plots and symbolic recurrence plots and by reservoir computing.

We examine the linear and nonlinear modes of a one-dimensional nonlinear electrical lattice, where the usual discrete Laplacian is replaced by a fractional discrete Laplacian. This induces a long-range intersite coupling that, at long distances, decreases as a power law. In the linear regime, we compute both the spectrum of plane waves and the mean-square displacement (MSD) of an initially localized excitation, in closed form in terms of regularized hypergeometric functions and the fractional exponent. The MSD shows ballistic behavior at long times, $\mathrm{MSD}\sim t^2$ for all fractional exponents. When the fractional exponent is decreased from its standard integer value, the bandwidth decreases and the density of states shows a tendency towards degeneracy. In the limit of a vanishing exponent, the system becomes completely degenerate. For the nonlinear regime, we compute numerically the low-lying nonlinear modes, as a function of the fractional exponent. A modulational stability computation shows that, as the fractional exponent decreases, the number of electrical discrete solitons generated also decreases, eventually collapsing into a single soliton.

Amorphous solids appear to react elastically to small external strains, but in contrast to ideal elastic media, plastic responses abound immediately at any value of the strain. Such plastic responses are quasilocalized in nature, with the “cheapest” one being a quadrupolar source. The existence of such plastic responses results in screened elasticity in which strains and stresses can either quantitatively or qualitatively differ from the unscreened theory, depending on the specific screening mechanism. Here we offer a theory of such screening effects by plastic quadrupoles, dipoles, and monopoles, explain their natural appearance, and point out the analogy to electrostatic screening by electric charges and dipoles. For low density of quadrupoles the effect is to normalize the elastic moduli without a qualitative change compared to pure elasticity theory; for higher density of quadrupoles the screening effects result in qualitative changes. Predictions for the spatial dependence of displacement fields caused by local sources of strains are provided and compared to numerical simulations. We find that anomalous elasticity is richer than electrostatics in having a screening mode that does not appear in the electrostatic analog.

We present a link between the theory of deep water waves and that of bubble surface perturbations. Theory correspondence is shown analytically for small wavelengths in the linear regime and investigated numerically in the nonlinear regime. To do so, we develop the second-order spatial perturbation equations for the Rayleigh-Plesset equation and solve them numerically. Our code is publicly available. Studying capillary waves on stable bubbles, we recreate the Kolmogorov-Zakharov spectrum predicted by weak turbulence theory, putting wave turbulence theory to use for bubbles. In this investigation, it seems that curvature does not affect turbulent properties. The calculated bubble surface responds qualitatively to low gravity experiments. The link demonstrated opens new possibilities for studying several bubble phenomena, including sonoluminescence and cavitation, using the extensive tools developed in the wave turbulence framework.

We present detailed spatiotemporal measurements of rf magnetic fields and plasma conduction current as well as the corresponding plasma density profiles when very-high-frequency 100-MHz waves are introduced to a parallel plate plasma. The magnetic probe, optical emission, and plasma absorption probe measurements support a model in which the interaction of high-frequency waves with the moving plasma sheath at specific phases of the very high frequencies (VHF) period leads to local reversals in the vertical rf electric field which can lead to conduction current reversals and circulations. The presence of current reversals and circulation correlate with measured plasma uniformity. In particular, measured electric field and current reversals coincide with the strongly center-peaked plasma density profiles frequently observed in VHF plasma. The magnitude of the center peak increases with the number and magnitude of the current reversal cells. The scale length of the current reversal cells is on the order of what is expected for plasma surface waves. Measurements indicate that plasma conductivity is the common scaling factor for both plasma uniformity and the circulation. The propagation of high-frequency waves and the generation of rf current reversal in one phase of the rf cycle rather than another results in the appearance of harmonics in Fourier decomposed magnetic probe wave forms. These harmonics turn out not to be actual waves or evidence of standing waves at these frequencies but rather consequences of packets of wave propagation that occur periodically.

The interplanetary plasma is characterized by a high level of complexity over a broad range of spatial scales. Spacecraft have detected a large variety of embedded structures that have been identified as discontinuities in the magnetic field vector. They can be either generated within the solar corona and advected by the plasma flow or locally generated as a result of the turbulent cascade of the solar wind turbulence. Since magnetic field fluctuations and structures influence the energetic particle propagation, here we set up a numerical model to study the interaction between charged particles and an ideal magnetohydrodynamics rotational discontinuity. This interaction is strongly influenced by the model parameters, such as the rotation angle of the discontinuity, the orientation of the mean-field direction with respect to the normal to the discontinuity direction, the initial particle pitch angle, and the initial particle gyrophase. Numerical results clearly show that the motion of particles crossing the discontinuity is extremely complex and highly sensitive to the initial conditions of the system, with transitions to a chaotic behavior. We find that particles can be temporarily trapped in rotational discontinuity and that the trapping times have a nearly power-law distribution. Also, the separatrix in the initial conditions phase space between crossing and noncrossing trajectories has a fractal structure. Implications for energetic particle propagation in space plasmas are discussed.

The structural properties of additive binary hard-sphere mixtures are addressed as a follow-up of a previous paper [S. Pieprzyk et al., Phys. Rev. E 101, 012117 (2020)]. The so-called rational-function approximation method and an approach combining accurate molecular dynamics simulation data, the pole structure representation of the total correlation functions, and the Ornstein-Zernike equation are considered. The density, composition, and size-ratio dependencies of the leading poles of the Fourier transforms of the total correlation functions $h_{ij}\left(r\right)$ of such mixtures are presented, those poles accounting for the asymptotic decay of $h_{ij}\left(r\right)$ for large $r$. Structural crossovers, in which the asymptotic wavelength of the oscillations of the total correlation functions changes discontinuously, are investigated. The behavior of the structural crossover lines as the size ratio and densities of the two species are changed is also discussed.

Quantum battery works as a micro- or nanodevice to store and redistribute energy at the quantum level. Here we propose a spin-charger protocol, in which the battery cells are charged by a finite number of spins through a general Heisenberg $XY$ interaction. Under the isotropic interaction, the spin-charger protocol is endowed with a higher capacity in terms of the maximum stored energy than the conventional protocols, where the battery is charged by a continuous-variable system, e.g., a cavity mode. By tuning the charger size, a tradeoff between the maximum stored energy and the average charging power is found in comparison to the cavity-charger protocol in the Tavis-Cummings model. Quantum advantage of our protocol is manifested by the scaling behavior of the optimal average power with respect to the battery size, in comparing the collective charging scheme to its parallel counterpart. We also discuss the detrimental effect on the charging performance from the anisotropic interaction between the battery and the charger, the nonideal initial states for both of them, and the crosstalk among the charger spins. A strong charger-charger interaction can be used to decouple the battery and the charger. Our findings about the advantages of the spin-charger protocol over the conventional cavity-charger protocols, including the high capacity of energy storage and the superior power law in the collective charging, provide an insight to exploit an efficient quantum battery based on the spin-spin-environment model.

We use a low-order oscillator model to investigate the mutual synchronization of a thermoacoustic system consisting of two turbulent lean-premixed combustors coupled via a cross-talk tube. The model consists of two Van der Pol (VDP) oscillators coupled via dissipative and time-delay terms. We show that, despite its simplicity, the model can reproduce many of the synchronization phenomena observed experimentally, such as amplitude death, desynchronization (quasiperiodicity), synchronization (phase locking), and nonlinear energy pumping from a limit-cycle mode to a damped mode. This study shows that the mutual synchronization dynamics of a turbulent thermoacoustic system can be reproduced with just a simple coupled VDP model. This suggests that such a model could be used to identify new strategies for quenching limit-cycle oscillations in turbulent thermoacoustic systems, such as gas turbines and rocket engines.

Unlike classical systems, understanding ergodicity from phase space mixing remains unclear for interacting quantum systems due to the absence of phase space trajectories. By considering an interacting spin model known as kicked coupled top, we elucidate the manifestation of phase space dynamics on local ergodic behavior of its quantum counterpart and quantum scarring phenomena. A transition to chaos occurs by increasing the kicking strength, and in the mixed phase space, the islands of regular motions within the chaotic sea clearly exhibit deviation from ergodicity, which we quantify from entanglement entropy and survival probability. Interestingly, the reminiscence of unstable orbits and fixed points can be identified as scars in quantum states, exhibiting athermal behavior and violation of Berry's conjecture for ergodic states. We also discuss the detection of quantum scars by a recently developed method of “out-of-time-order correlators,” which has experimental relevance.