The random-field $XY$ model is studied in spatial dimensions $d=3$ and 4, and in between, as the limit $q\to \infty$ of the $q$-state clock models, by the exact renormalization-group solution of the hierarchical lattice or, equivalently, the Migdal-Kadanoff approximation to the hypercubic lattices. The lower critical dimension is determined between $3.81<d_c<4$. When the random field is scaled with $q$, a line segment of zero-temperature criticality is found in $d=3$. When the random field is scaled with $q^2$, a universal phase diagram is found at intermediate temperatures in $d=3$.

Recently, a hypothesis on the complexity growth of unitarily evolving operators was presented. This hypothesis states that in generic, nonintegrable many-body systems, the so-called Lanczos coefficients associated with an autocorrelation function grow asymptotically linear, with a logarithmic correction in one-dimensional systems. In contrast, the growth is expected to be slower in integrable or free models. In this paper, we numerically test this hypothesis for a variety of exemplary systems, including one-dimensional and two-dimensional Ising models as well as one-dimensional Heisenberg models. While we find the hypothesis to be practically fulfilled for all considered Ising models, the onset of the hypothesized universal behavior could not be observed in the attainable numerical data for the Heisenberg model. The proposed linear bound on operator growth associated with the hypothesis eventually stems from geometric arguments involving the locality of the Hamiltonian as well as the lattice configuration. We derive and investigate a related geometric bound, and we find that while the bound itself is not sharply achieved for any considered model, the hypothesis is nonetheless fulfilled in most cases.

Biochemistry, ecology, and neuroscience are examples of prominent fields aiming at describing interacting systems that exhibit nontrivial couplings to complex, ever-changing environments. We have recently shown that linear interactions and a switching environment are encoded separately in the mutual information of the overall system. Here we first generalize these findings to a broad class of nonlinear interacting models. We find that a new term in the mutual information appears, quantifying the interplay between nonlinear interactions and environmental changes, and leading to either constructive or destructive information interference. Furthermore, we show that a higher mutual information emerges in out-of-equilibrium environments with respect to an equilibrium scenario. Finally, we generalize our framework to the case of continuously varying environments. We find that environmental changes can be mapped exactly into an effective spatially varying diffusion coefficient, shedding light on modeling of biophysical systems in inhomogeneous media.

We provide a detailed investigation of the fluctuations of the currents in the discrete model of Feynman's ratchet proposed by Jarzynski and Mazonka in 1999. Two macroscopic currents are identified, with the corresponding affinities determined using Schnakenberg's graph analysis. We also investigate full counting statistics of the two currents and show that fluctuation theorem holds for their joint probability distribution. Moreover, fluctuation-dissipation relation, Onsager reciprocal relation and their nonlinear generalizations are numerically shown to be satisfied in this model.

We developed a computationally efficient approach to approximate near-wall diffusion coefficients of arbitrarily shaped rigid macromolecules. The proposed method relies on extremum principles for Stokes flows produced by the motion of rigid bodies. In the presence of the wall, the rate of energy dissipation is decreased relative to the unbounded fluid. In our approach, the position- and orientation-dependent mobility matrix of a body suspended near a no-slip plane is calculated numerically using a coarse-grained molecular model and the Rotne-Prager-Yamakawa description of hydrodynamics. Effects of the boundary are accounted for via Blake's image construction. The matrix components are scaled using ratios of the corresponding bulk values evaluated for the detailed representation of the molecule and its coarse-grained model, leading to accurate values of the near-wall diffusion coefficients. We assess the performance of the approach for two biomolecules at different levels of coarse-graining.

A theoretical picture describing the tensile strength ${\sigma }_T$ of elastomers is developed. ${\sigma }_T$ is composed of three factors: (1) the tensile strength of individual polymer load-bearing chains (LBCs) according to Eyring's theory, (2) an occupation number of LBC states using Fermi statistics, and (3) an excluded volume factor reducing the number of possible LBCs due to the presence of filler particles or crosslinks between polymers. This description is compared to experimental tensile strengths of carbon black (N339)-filled EPDM (Keltan 4450) as well as to other experiments in the literature studying the effects of temperature, filler concentration, and particle size as well as crosslink density.

The glass transition temperature ($T_g$) is one of the most fundamental properties of polymers. $T_g$ is predicted by some theories as a sudden change in a “macroscopic” quantity (e.g., compressibility). However, for systems with “soft” glass transitions where the change is gradual it becomes hard to pinpoint precisely the transition temperature as well as the set of molecular changes occurring during this transition. Here, we introduce two new molecular signatures for the glass transition of polymers that exhibit clear changes as one approaches $T_g$: (i) differential change of the probability distribution of dihedral angles as a function of temperature and (ii) the distribution of fractional of the time spent in the different torsional states. These new signatures provide insights into the glass transition in polymers by directly exhibiting the concept of spatial heterogeneity and dynamical ergodicity breaking in such systems, as well as provide a key step to quantitatively obtain the transition temperature from molecular characteristics of the polymeric systems.

We consider a rigid assembly of two active Brownian particles, forming an active colloidal dimer, in a gradient of activity. We show analytically that depending on the relative orientation of the two particles the active dimer accumulates in regions of either high or low activity, corresponding to, respectively, chemotaxis and antichemotaxis. Certain active dimers show both chemotactic and antichemotactic behavior, depending on the strength of the activity. Our coarse-grained Fokker-Planck approach yields an effective potential, which we use to construct a nonequilibrium phase diagram that classifies the dimers according to their tactic behavior. Moreover, we show that for certain dimers a higher persistence of the motion is achieved similar to the effect of a steering wheel in macroscopic devices. This work could be useful for designing autonomous active colloidal structures which adjust their motion depending on the local activity gradients.

It is well known that surface tension is dependent on temperature, and thus a nonuniform temperature may cause thermocapillary flow which is referred to as the Marangoni effect. For a thin liquid-air film confined between a flat hot plate and a topographical cold template, it undergoes deformation due to thermocapillary flow. This phenomenon is termed as thermocapillary patterning, and has been used to fabricate micro- and nanostructure in polymer films. In most cases, the obtained structure conforms to the template; i.e., it can be considered as a replication technique. In this paper, we developed a two-phase flow numerical model based on the phase field to study the dynamic process of thermocapillary patterning. As a remeshing-free method, the phase field enables the incorporation of thermal field and multiphase flow with free surface deformation. The numerical model was employed to study the dynamic process of thermocapillary patterning. Meanwhile, the effects of some parameters, e.g., temperature, geometry parameters, and contact angle, were also investigated.

High energy density (HED) matter exists extensively in the Universe, and it can be created with extreme conditions in laboratory facilities such as x-ray free-electron lasers (XFEL). In HED matter, the electronic structure of individual atomic ions is influenced by a dense plasma environment, and one of the most significant phenomena is the ionization potential depression (IPD). Incorporation of the IPD effects is of great importance in accurate modeling of dense plasmas. All theoretical treatments of IPD so far have been based on the assumption of local thermodynamic equilibrium, but its validity is questionable in ultrafast formation dynamics of dense plasmas, particularly when interacting with intense XFEL pulses. A treatment of transient IPD, based on an electronic-structure calculation of an atom in the presence of a plasma environment described by classical particles, has recently been proposed [Phys. Rev. E 103, 023203 (2021)], but its application to and impact on plasma dynamics simulations have not been investigated yet. In this work, we extend XMDYN, a hybrid quantum-classical approach combining Monte Carlo and molecular dynamics, by incorporating the proposed IPD treatment into plasma dynamics simulations. We demonstrate the importance of the IPD effects in theoretical modeling of aluminum dense plasmas by comparing two XMDYN simulations: one with electronic-structure calculations of isolated atoms (without IPD) and the other with those of atoms embedded in a plasma (with IPD). At equilibrium, the mean charge obtained in the plasma simulation with IPD is in good agreement with the full quantum-mechanical average-atom model. The present approach promises to be a reliable tool to simulate the creation and nonequilibrium evolution of dense plasmas induced by ultraintense and ultrashort XFEL pulses.

The violation of the Pauli principle has been surmised in several models of the fractional exclusion statistics and successfully applied to several quantum systems. In this paper, a classical alternative of the exclusion statistics is studied using the maximum entropy methods. The difference between the Bose-Einstein statistics and the Maxwell-Boltzmann statistics is understood in terms of a separable quantity, namely the degree of indistinguishability. Starting from the usual Maxwell-Boltzmann microstate counting formula, a special restriction related to the degree of indistinguishability is incorporated using Lagrange multipliers to derive the probability distribution function at equilibrium under NVE conditions. It is found that the resulting probability distribution function generates real positive values within the permissible range of parameters. For a dilute system, the probability distribution function is intermediate between the Fermi-Dirac and Bose-Einstein statistics and follows the exclusion principle. Properties of various variables of this novel statistical model are studied and possible application to classical thermodynamics is discussed.

We develop a model, called the “random-walk shielding-potential viscosity model” (RWSP-VM) that introduces the statistics of random-walk ions and the Debye shielding effect to describe the viscosities of warm dense metals. The viscosities of several metals with low to high atomic numbers (Be, Al, Fe, and U) are calculated using the analytical expression of RWSP-VM. Additionally, we simulate the viscosities of Fe and Be by employing the Langevin molecular dynamics (MD) and classical MD, while the MD data for Al and U are obtained from a previous work. The results of the RWSP-VM are in good agreement with the MD results, which validates the proposed model. Furthermore, we compare the RWSP-VM with the one-component plasma model and Yukawa viscosity model and show that the three models yield results in excellent agreement with each other in the regime where the RWSP-VM is applicable. These results indicate that the RWSP-VM is a universal, accurate, and highly efficient model for calculating the viscosity of metals in the warm dense state. The code of the proposed RWSP-VM is provided, and it is envisaged that it will have broad application prospects in numerous fields.

Convection is a key transport phenomenon important in many different areas, from hydrodynamics and ocean circulation to planetary atmospheres or stellar physics. However, its microscopic understanding still remains challenging. Here we numerically investigate the onset of convective flow in a compressible (non-Oberbeck-Boussinesq) hard disk fluid under a temperature gradient in a gravitational field. We uncover a surprising two-step transition scenario with two different critical temperatures. When the bottom plate temperature reaches a first threshold, convection kicks in (as shown by a structured velocity field) but gravity results in hindered heat transport as compared to the gravity-free case. It is at a second (higher) temperature that a percolation transition of advection zones connecting the hot and cold plates triggers efficient convective heat transport. Interestingly, this picture for the convection instability opens the door to unknown piecewise-continuous solutions to the Navier-Stokes equations.

The systematic expansion method of the solution of the Fokker-Planck equation is developed by generalizing the formulation proposed in [J. Phys. A: Math. Theor. 50, 325001 (2017)]. Using this method, we obtain an alternative formula to calculate the mean work perturbatively which is applicable to systems with degeneracy in the eigenvalues of the Fokker-Planck operator. This method enables us to study how the geometrical symmetry affects thermodynamic description of a Brownian particle. To illustrate the application of the derived theory, we consider the Fokker-Planck equation with a two-dimensional harmonic potential. To investigate the effect of symmetry of the potential, we study thermodynamic properties in symmetric and asymmetric deformation processes of the potential: the rotational symmetry of the harmonic potential is held in the former, but it is broken in the latter. Optimized deformations in these processes are defined by minimizing mean work. Comparing these optimized processes, we find that the difference between the symmetric and asymmetric processes is maximized when the deformation time of the potential is given by a critical time which is characterized by the relaxation time of the Fokker-Planck equation. This critical time in the mean work is smaller than that of the change of the mean energy because of the hysteresis effect in the irreversible processes.

A random matrix representation is proposed for the two-dimensional (2D) Coulomb gas at inverse temperature $\beta$. For $2\times 2$ matrices with Gaussian distribution we analytically compute the nearest-neighbor spacing distribution of complex eigenvalues in radial distance. Because it does not provide such a good approximation as the Wigner surmise in 1D, we introduce an effective ${\beta }_{\mathrm{eff}}\left(\beta \right)$ in our analytic formula that describes the spacing obtained numerically from the 2D Coulomb gas well for small values of $\beta$. It reproduces the 2D Poisson distribution at $\beta =0$ exactly, that is valid for a large particle number. The surmise is used to fit data in two examples, from open quantum spin chains and ecology. The spacing distributions of complex symmetric and complex quaternion self-dual ensembles of non-Hermitian random matrices, that are only known numerically, are very well fitted by noninteger values $\beta =1.4$ and $\beta =2.6$ from a 2D Coulomb gas, respectively. These two ensembles have been suggested as the only two symmetry classes, where the 2D bulk statistics is different from the Ginibre ensemble.

In this paper we introduce a general stochastic representation for an important class of processes with resetting. It allows to describe any stochastic process intermittently terminated and restarted from a predefined random or nonrandom point. Our approach is based on stochastic differential equations called jump-diffusion models. It allows to analyze processes with resetting both, analytically and using Monte Carlo simulation methods. To depict the strength of our approach, we derive a number of fundamental properties of Brownian motion with Poissonian resetting, such as the Itô lemma, the moment-generating function, the characteristic function, the explicit form of the probability density function, moments of all orders, various forms of the Fokker-Planck equation, infinitesimal generator of the process, and its adjoint operator. Additionally, we extend the above results to the case of time-nonhomogeneous Poissonian resetting. This way we build a general framework for the analysis of any stochastic process with intermittent random resetting.

We examine probability distribution for avalanche sizes observed in self-organized critical systems. While a power-law distribution with a cutoff because of finite system size is typical behavior, a systematic investigation reveals that it may also decrease with increasing the system size at a fixed avalanche size. We implement the scaling method and identify scaling functions. The data collapse ensures a correct estimation of the critical exponents and distinguishes two exponents related to avalanche size and system size. Our simple analysis provides striking implications. While the exact value for avalanches size exponent remains elusive for the prototype sandpile on a square lattice, we suggest the exponent should be 1. The simulation results represent that the distribution shows a logarithmic system size dependence, consistent with the normalization condition. We also argue that for the train or Oslo sandpile model with bulk drive, the avalanche size exponent is slightly less than 1, which differs significantly from the previous estimate of 1.11.

In this paper, transmission of a monochromatic wave through a counterpropagating electron beam under the condition of cyclotron resonance absorption is studied by theoretical analysis and numerical simulation. Conditions of the modulation instability (MI) are analyzed. The MI strongly affects the regimes of transmission. We also derive explicit periodic stationary solutions expressed in terms of elliptic Jacobi functions, as well as bright- and dark-soliton solutions. Analysis of these solutions allows obtaining threshold values of the driving power and frequency for the different regimes of transmission, such as cyclotron absorption, multifrequency self-modulation oscillations, and stationary single-frequency propagation. The theoretical predictions are verified by numerical simulation. In this way, we obtain the conditions at which a continuous-wave driving signal disintegrates into a close-to-periodic train of microwave soliton pulses.

Inspired by how the shape deformations in active organisms help them to migrate through disordered porous environments, we simulate active ring polymers in two-dimensional random porous media. Flexible and inextensible active ring polymers navigate smoothly through the disordered media. In contrast, semiflexible rings undergo transient trapping inside the pore space; the degree of trapping is inversely correlated with the increase in activity. We discover that flexible rings swell while inextensible and semiflexible rings monotonically shrink upon increasing the activity. Together, our findings identify the optimal migration of active ring polymers through porous media.