Transmission measurements through three-port microwave graphs are performed, in analogy to three-terminal voltage drop devices with orthogonal, unitary, and symplectic symmetry. The terminal used as a probe is symmetrically located between two chaotic subgraphs, and each graph is connected to one port, the input and the output, respectively. The analysis of the experimental data clearly exhibits the weak localization and antilocalization phenomena. We find a good agreement with theoretical predictions, provided that the effects of dissipation and imperfect coupling to the ports are taken into account.

The existing concept of the “fitness value of information” provides a theoretical upper bound on the fitness advantage of using information concerning a fluctuating environment. Using concepts from rate-distortion theory, we develop a theoretical framework to answer a different pair of questions: What is the minimal amount of information needed for a population to achieve a certain growth rate? What is the minimal amount of information gain needed for one subpopulation to achieve a certain average selection coefficient over another? We introduce a correspondence between fitness and distortion and solve for the rate-distortion functions of several systems using analytical and numerical methods. Because accurate information processing is energetically costly, our approach provides a theoretical basis for understanding evolutionary “design principles” underlying information-cost trade-offs.

Phonon spectra of a two-dimensional (2D) solid dusty plasma modulated by 2D square and triangular periodic substrates are investigated using Langevin dynamical simulations. The commensurability ratio, i.e., the ratio of the number of particles to the number of potential well minima, is set to 1 or 2. The resulting phonon spectra show that propagation of waves is always suppressed due to the confinement of particles by the applied 2D periodic substrates. For a commensurability ratio of 1, the spectra indicate that all particles mainly oscillate at one specific frequency, corresponding to the harmonic oscillation frequency of one single particle inside one potential well. At a commensurability ratio of 2, the substrate allows two particles to sit inside the bottom of each potential well, and the resulting longitudinal and transverse spectra exhibit four branches in total. We find that the two moderate branches come from the harmonic oscillations of one single particle and two combined particles in the potential well. The other two branches correspond to the relative motion of the two-body structure in each potential well in the radial and azimuthal directions. The difference in the spectra between the square and triangular substrates is attributed to the anisotropy of the substrates and the resulting alignment directions of the two-body structure in each potential well.

The work is a concept of fundamental importance in thermodynamics. An open question is how to describe the work fluctuation for quantum coherent processes in the presence of initial quantum coherence in the energy basis. With the aim of giving a unified description, here we introduce and study a class of quasiprobability distributions of work, which give an average work equal to the average energy change of the system and reduce to the two-projective-measurement scheme for an initial incoherent state. Moreover, we characterize the work with the help of fluctuation relations. In particular, by considering the joint distribution of work and initial quantum coherence, we find a fluctuation theorem involving quantum coherence, from which follows a second law of thermodynamics in the case of initial thermal populations.

Heat-bath Monte Carlo simulations have been used to study a 12-state discretized Heisenberg model with a type of random field on simple cubic lattices of size $128\times 128\times 128$. The 12 states correspond to the [110] directions of a cube. The model has the standard nonrandom two-spin exchange term with coupling energy $J$ and a random field which consists of adding an energy $h_R$ to two of the 12 spin states, chosen randomly and independently at each site. We report on the case $h_R/J=3$, which has a sharp phase transition at about $T_c/J=1.40625$. Below $T_c$, the model has long-range ferroelectric order oriented along one of the eight [111] directions. At $T_c$, the behavior of the peak in the structure factor, $S\left(\mathbf{k}\right)$, at small $\left|\mathbf{k}\right|$ is a straight line on a log-log plot, which gives the result $\overline{\eta }=1.214\pm 0.014$. The onset of orientational order below $T_c$ is very rapid for this value of $h_R$. There are peaks in the specific heat and longitudinal susceptibility at $T_c$. Below $T_c$ there is a strong correction to ordinary scaling, which is probably caused by the cubic anisotropy, which is a dangerous irrelevant variable.

The interaction between individuals in biological populations, dilute components of chemical systems, or particles transported by turbulent flows depends critically on their contact statistics. This work clarifies those statistics under the simplifying assumptions that the underlying motions approximate a Brownian random walk and that the particles can be treated as noninteracting. We measure the contact-interval (also called the waiting-time or interarrival-time), contact-count, and contact-duration distributions in populations of individuals undergoing noninteracting continuous-space-time random walks on a periodic two-dimensional plane (a torus) as functions of the population number density, walker radius, and random-walk step size. The contact-interval is exponentially distributed for times longer than the ballistic mean-free-collision time but not for times shorter than that, and the contact duration distribution is strongly peaked at the ballistic-crossing time for head-on collisions when the ballistic-crossing time is short compared to the mean step duration. While successive contacts between individuals are independent, the probability of repeat contact decreases with time after a previous contact. This leads to a negative duration dependence of the waiting-time interval and overdispersion of the contact-count probability density function for all time intervals. The paper demonstrates that for populations of small particles (with a walker radius that is small compared to the mean-separation or random-walk step size), the ballistic mean-free-collision interval, the ballistic-crossing time, and the random-walk-step duration can be used to construct temporal scalings which allow for common waiting-time, contact-count, and contact-duration distributions across different populations. Semi-analytic approximations for both the waiting-time and contact-duration distributions are also presented.

The present paper proposes an adaptive control law for inducing in-phase and antiphase synchronization in a pair of relaxation oscillators. We analytically show that the phase dynamics of the oscillators coupled by the control law is equivalent to that of Kuramoto phase oscillators and then extend the results for a pair of oscillators to three or more oscillators. We also provide a systematic procedure for designing the controller parameters for oscillator networks with all-to-all and ring topologies. Our numerical simulations demonstrate that these analytical results can be used to solve a dispatching problem encountered by automated guided vehicles (AGVs) in factories. AGV congestion can be avoided and the peak value of the amount of materials or parts in buffers can be suppressed.

The hierarchical organization and self-similarity in river basins have been topics of extensive research in hydrology and geomorphology starting with the pioneering work of Horton in 1945. Despite significant theoretical and applied advances, however, the mathematical origin of and relation among Horton's laws for different stream attributes remain unsettled. Here we capitalize on a recently developed theory of random self-similar trees to elucidate the origin of Horton's laws, Hack's laws, basin fractal dimensions, power-law distributions of link attributes, and power-law relations between distinct attributes. In particular, we introduce a one-parametric family of self-similar critical Tokunaga trees that includes the celebrated Shreve's random topology model and extends to trees that approximate the observed river networks with realistic exponents. The results offer tools to increase our understanding of landscape organization under different hydroclimatic forcings, and to extend scaling relationships useful for hydrologic prediction to resolutions higher than those observed.

Refractoriness is a fundamental property of excitable elements, such as neurons, indicating the probability for re-excitation in a given time lag, and is typically linked to the neuronal hyperpolarization following an evoked spike. Here we measured the refractory periods (RPs) in neuronal cultures and observed that an average anisotropic absolute RP could exceed 10 ms and its tail is 20 ms, independent of a large stimulation frequency range. It is an order of magnitude longer than anticipated and comparable with the decaying membrane potential time scale. It is followed by a sharp rise-time (relative RP) of merely ∼1 md to complete responsiveness. Extracellular stimulations result in longer absolute RPs than solely intracellular ones, and a pair of extracellular stimulations from two different routes exhibits distinct absolute RPs, depending on their order. Our results indicate that a neuron is an accurate excitable element, where the diverse RPs cannot be attributed solely to the soma and imply fast mutual interactions between different stimulation routes and dendrites. Further elucidation of neuronal computational capabilities and their interplay with adaptation mechanisms is warranted.

In biofluids containing various proteins, nanoparticles rapidly come to be surrounded by a nanometer-thick protein layer referred to as a protein corona. The late stage of this process occurs via replacement of proteins already bound to a nanoparticle by new ones. In the available kinetic models, this process is considered to include independent acts of protein detachment and attachment. It can, however, occur also at the level of protein pairs via exchange, i.e., concerted replacement of an attached protein by a newly arrived one. I argue that the exchange channel can be more important than the conventional one. To illustrate the likely specifics of the exchange channel, I present a kinetic model focused exclusively on this channel and based on the Evans-Polanyi-type relation between the activation energies of the protein-exchange steps and the protein binding energies. The corresponding kinetics were calculated for three qualitatively different distributions of proteins in solution over binding energy (with a maximum or monotonously decreasing or increasing, respectively) and are found to be similar, with relatively rapid replacement of weakly bound proteins and slow redistribution of strongly bound proteins. The ratio of the timescales characterizing the evolution of weakly and strongly bound proteins is found to depend on the type of the binding-energy distribution.

We investigate modifications of a stochastic polymer picture through a shift in the boundary between the system and an external environment. A conventional bead-and-spring model serving as the coarse-graining model is given by the Langevin equation for all the monomers subject to white noise. However, stochastic motion for only a tagged monomer is observed to occur in the presence of colored noise. The qualitative change in the observations arises from the boundary shift decided by the observer. The Langevin dynamics analyses interpret the colored noise as the emergence of the polymeric elastic force, resulting in additional heat in the tagged monomer observation. Being distinguished from coarse-graining based on scale separation, the projection of comparable internal degrees of freedom is also discussed in light of the fluctuation theorem and the stochastic polymer thermodynamics.

This article focuses on a preaveraging description of polymer nonequilibrium stretching, where a single polymer undergoes a transient process from equilibrium to nonequilibrium steady state by pulling one chain end. The preaveraging method combined with mode analysis reduces the original Langevin equation to a simplified form for both a stretched steady state and an equilibrium state, even in the presence of self-avoiding repulsive interactions spanning a long range. However, the transient stretching process exhibits evolution of a hierarchal regime structure, which means a qualitative temporal change in probabilistic distributions assumed in preaveraging. We investigate the preaveraging method for evolution of the regime structure with consideration of the nonequilibrium work relations and deviations from the fluctuation-dissipation relation.

We investigated the specific properties of magnetically induced transparency (MIT) and magnetically induced absorption (MIA) in helically structured periodic crystals (HSPCs). We showed that for the wavelength of MIT we have an ideal optical diode: The forward signal passes fully, while the backward signal is completely absorbed and not reflected. A formula for the wavelength ${\lambda }_t$ of MIT and MIA resonance based on the numerical simulations was analytically obtained. The influence of HSPC parameters on the wavelength ${\lambda }_t$ and on $\mathrm{\Delta }{\lambda }_t$, the transparency line half width, was investigated by numerical simulations. The specific properties of light energy density, the ellipticity $e_{\mathrm{in}}$, and azimuth ${\phi }_{\mathrm{in}}$ of the total wave excited in the HSPC layer for MIT and MIA modes were investigated, too.

The effect of polydispersity on foam permeability is investigated by numerical simulations. Foam structures are first generated by Laguerre tessellations via the Neper software and relaxed to minimize the surface energy via the Surface Evolver software. The fluid flow and permeability are then calculated by means of pore-network simulations, by considering either fully open-cell foams or foams with randomly selected closed windows. Different configurations of window aperture are used, including identical window aperture size, identical window aperture ratio, or random window aperture ratio. The main results are obtained for the case of foams having identical and uniform window aperture ratios. For such foams and at constant mean pore size, foam permeability is found to strongly increase with the polydispersity degree. The numerical results are employed to discuss the validity of the mean pressure field assumption used to calculate the foam permeability, the effect of small pores, and the definition of an equivalent Kelvin foam size. We show that as long as the fluctuations of the window aperture ratio remain low, foam permeability can be estimated by using the mean pressure field hypothesis. The weak effect of small pores on permeability is related to their small contribution to the overall fluid volume fraction. Finally, various estimations of the equivalent Kelvin foam size based on pore-size distribution are proposed.

Transport properties of mixtures in the warm dense matter (WDM) regime play an important role in natural astrophysics. However, a physical understanding of ionic transport properties in quasisymmetric liquid mixtures has remained elusive. Here, we present extensive ab initio molecular dynamics (AIMD) simulations on the ionic diffusion and viscosity of a quasisymmetric binary nitrogen-oxygen (N-O) mixture in a wide warm dense regime of 8–120 kK and 4.5–8.0 g/${\mathrm{cm}}^3$. Diffusion and viscosity of N-O mixtures with different compositions are obtained by using the Green–Kubo formula. Unlike asymmetric mixtures, the change of proportions in N-O mixtures slightly affects the viscosity and diffusion in the strong-coupling region. Furthermore, the AIMD results are used to build and verify a global pseudo-ion in jellium (PIJ) model for ionic transport calculations. The PIJ model succeeds in reproducing the transport properties of N-O mixtures where ionization has occurred, and provides a promising alternative approach to obtaining comparable results to AIMD simulations with relatively small computational costs. Our current results highlight the characteristic features of the quasisymmetric binary mixtures and demonstrate the applicability of the PIJ model in the WDM regime.

We demonstrate that the multiphase Shan-Chen lattice Boltzmann method (LBM) yields a curvature dependent surface tension $\sigma$ as computed from three-dimensional hydrostatic droplets and bubbles simulations. Such curvature dependence is routinely characterized, at first order, by the so-called Tolman length $\delta$. LBM allows one to precisely compute $\sigma$ at the surface of tension $R_s$ and determine the Tolman length from the coefficient of the first order correction. The corresponding values of $\delta$ display universality for different equations of state, following a power-law scaling near the critical temperature. The Tolman length has been studied so far mainly via computationally demanding Molecular Dynamics simulations or by means of Density Functional Theory approaches playing a pivotal role in extending Classical Nucleation Theory. The present results open a hydrodynamic-compliant mesoscale arena, in which the fundamental role of the Tolman length, alongside real-world applications to cavitation phenomena, can be effectively tackled. All the results can be independently reproduced through the “idea.deploy” framework.

A universal large $\mathcal{N}$ theory of nonequilibrium fluctuations emerges in the limit of fast jump rates and large occupancies. We use this theory to derive a set of coarse-grained thermodynamic uncertainty relations—one of them being an activity bound. Importantly, the activity serves as a tighter bound for the entropy production in 1D systems. These results are particularly useful in the many-body regime, where typically a coarse-grained approach is required to handle the large microscopic state space.

The inverse current, i.e., one induced current is opposite to both applied forces, has recently been found in a classical one-dimensional interacting Hamiltonian system [Phys. Rev. Lett. 124, 110607 (2020)]. In this paper, we show that the inverse current also exists in quantum system. Based on Coulomb-coupled quantum dots system, we find that the inverse current will appear when Coulomb interaction increases. This does not violate the second law of thermodynamics, since entropy reduction caused by the inverse current is compensated by entropy increase caused by the forward current, which ensures that total entropy increase of the system is always greater than zero.

We investigate the charging process of open quantum battery in the weak system-environment coupling regime. A method to improve the performance of open quantum battery in a reservoir environment, which described by a band-gap environment model or a two-Lorentzian environment model, is proposed by manipulating the spectral density of environment. We find that the optimal quantum battery, characterized by fast charging time and large ergotropy, in the band-gap environment can be obtained by increasing the weights of two Lorentzians and the spectral width of the second Lorentzian, which is in sharp contrast to the quantum battery in two-Lorentzian environment. Then we extend our discussion to multiple coupled reservoir environments, which are composed of $N$ coupled dissipative cavities. We show that, the performance of quantum battery can be enhanced by increasing the coupling strength between the nearest-neighbor environments and decreasing the size of the environments. In particular, to fully charge and extract the total stored energy as work for quantum battery can be achieved by manipulating the coupling strength between the nearest-neighbor environments. Our results provide a practical approach for the realization of the optimal quantum batteries in future experiments.

Physical demixing on large scales of embryonic cell populations is fundamental to metazoan development, but whether a rigidity disparity alone is sufficient to driving large-scale demixing in a binary mixture of cell tissues is still an open question. To answer this question, we study mixing and demixing in a binary mixture of rigidity disparity cell tissues without heterotypic interactions using the Voronoi-based cellular model. Under suitable system parameters, the solid-like cells in the mixture can aggregate into a large cluster and the large-scale demixing occurs, which addresses that a rigidity disparity alone is sufficient to drive large-scale demixing. Remarkably, there exists an optimal temperature or rigidity disparity at which the binary mixture can be separated to the maximum extent. The necessary condition for the separation of mixtures is that the two types of cells are solid-like and liquid-like, respectively. The observation of robust demixing on large scales suggests that the sorting of progenitor cells may occur very early in the development process before robust heterotypic interfacial tensions are established. Our findings are relevant to understanding the mechanisms that drive cell sorting in confluent tissues.