Mean-field Type Approximation Research Articles

Stochastic Process Leading to Catalan Number Recurrence

Motivated by a simple model of earthquake statistics, a finite random discrete dynamical system is defined in order to obtain Catalan number recurrence by describing the stationary state of the system in the limit of its infinite size. Equations describing dynamics of the system, represented by partitions of a subset of {1,2,…,N}, are derived using basic combinatorics. The existence and uniqueness of a stationary state are shown using Markov chains terminology. A well-defined mean-field type approximation is used to obtain block size distribution and the consistency of the approach is verified. It is shown that this recurrence asymptotically takes the form of Catalan number recurrence for particular dynamics parameters of the system.

New approaches to epidemic modeling on networks

In this article, we develop two independent and new approaches to model epidemic spread in a network. Contrary to the most studied models, those developed here allow for contacts with different probabilities of transmitting the disease (transmissibilities). We then examine each of these models using some mean field type approximations. The first model looks at the late-stage effects of an epidemic outbreak and allows for the computation of the probability that a given vertex was infected. This computation is based on a mean field approximation and only depends on the number of contacts and their transmissibilities. This approach shares many similarities with percolation models in networks. The second model we develop is a dynamic model which we analyze using a mean field approximation which highly reduces the dimensionality of the system. In particular, the original system which individually analyses each vertex of the network is reduced to one with as many equations as different transmissibilities. Perhaps the greatest contribution of this article is the observation that, in both these models, the existence and size of an epidemic outbreak are linked to the properties of a matrix which we call the {mathcal {R}}-matrix. This is a generalization of the basic reproduction number which more precisely characterizes the main routes of infection.

Spin-diffusions and diffusive molecular dynamics

Metastable configurations in condensed matter typically fluctuate about local energy minima at the femtosecond time scale before transitioning between local minima after nanoseconds or microseconds. This vast scale separation limits the applicability of classical molecular dynamics (MD) methods and has spurned the development of a host of approximate algorithms. One recently proposed method is diffusive MD which aims at integrating a system of ordinary differential equations describing the likelihood of occupancy by one of two species, in the case of a binary alloy, while quasistatically evolving the locations of the atoms. While diffusive MD has shown itself to be efficient and provide agreement with observations, it is fundamentally a model, with unclear connections to classical MD. In this work, we formulate a spin-diffusion stochastic process and show how it can be connected to diffusive MD. The spin-diffusion model couples a classical overdamped Langevin equation to a kinetic Monte Carlo model for exchange amongst the species of a binary alloy. Under suitable assumptions and approximations, spin-diffusion can be shown to lead to diffusive MD type models. The key assumptions and approximations include a well-defined time scale separation, a choice of spin-exchange rates, a low temperature approximation, and a mean field type approximation. We derive several models from different assumptions and show their relationship to diffusive MD. Differences and similarities amongst the models are explored in a simple test problem.

Generalized Epidemic Mean-Field Model for Spreading Processes Over Multilayer Complex Networks

Mean-field deterministic epidemic models have been successful in uncovering several important dynamic properties of stochastic epidemic spreading processes over complex networks. In particular, individual-based epidemic models isolate the impact of the network topology on spreading dynamics. In this paper, the existing models are generalized to develop a class of models that includes the spreading process in multilayer complex networks. We provide a detailed description of the stochastic process at the agent level where the agents interact through different layers, each represented by a graph. The set of differential equations that describes the time evolution of the state occupancy probabilities has an exponentially growing state-space size in terms of the number of the agents. Based on a mean-field type approximation, we developed a set of nonlinear differential equations that has linearly growing state-space size. We find that the latter system, referred to as the generalized epidemic mean-field (GEMF) model, has a simple structure characterized by the elements of the adjacency matrices of the network layers and the Laplacian matrices of the transition rate graphs. Finally, we present several examples of epidemic models, including spreading of virus and information in computer networks and spreading of multiple pathogens in a host population .

Rigorous derivation of the rate equations for epitaxial growth

In the framework of the second quantization representation of the master equation governing irreversible epitaxial growth, exact equations describing the evolution of the island densities have been obtained. Their decoupling within a mean field-type approximation with the unknown correlation functions replaced by capture numbers (CNs) has been used to derive a closed set of rate equations. The latter have been compared with the exact equations to obtain rigorous definitions of the CNs. The CN that describes the nucleation of dimer islands from two mobile monomers has been measured in exact kinetic Monte Carlo simulations with the use of the rigorous definition. Strong disagreement with the literature values calculated within alternative techniques has been found, especially at low surface coverage. Plausible causes for the discrepancies are suggested. Another important result of the rigorous approach is the rate equation with the term describing the monomer diffusion. This equation significantly differs from the widely used equations of this kind known from the literature. Arguments in favour of our approach are given.

Schloegl’s Second Model for Autocatalysis on a Cubic Lattice: Mean-Field-Type Discrete Reaction-Diffusion Equation Analysis

Schloegl’s second model for autocatalysis on a hypercubic lattice of dimension d≥2 involves: (i) spontaneous annihilation of particles at lattice sites with rate p; and (ii) autocatalytic creation of particles at vacant sites at a rate proportional to the number of diagonal pairs of particles on neighboring sites. Kinetic Monte Carlo simulations for a d=3 cubic lattice reveal a discontinuous transition from a populated state to a vacuum state as p increases above p=p e . However, stationary points, p=p eq (≤p e ), for planar interfaces separating these states depend on interface orientation. Our focus is on analysis of interface dynamics via discrete reaction-diffusion equations (dRDE’s) obtained from mean-field type approximations to the exact master equations for spatially inhomogeneous states. These dRDE can display propagation failure absent due to fluctuations in the stochastic model. However, accounting for this anomaly, dRDE analysis elucidates exact behavior with quantitative accuracy for higher-level approximations.

Charge correlations in polaron hopping through molecules

In many organic molecules the strong coupling of excess charges to vibrational modes leads to the formation of polarons, i.e., a localized state of a charge carrier and a molecular deformation. Incoherent hopping of polarons along the molecule is the dominant mechanism of transport at room temperature. We study the far-from-equilibrium situation where, due to the applied bias, the induced number of charge carriers on the molecule is high enough such that charge correlations become relevant. We develop a diagrammatic theory that exactly accounts for all many-particle correlations functions for incoherent transport through a finite system. We compute the transport properties of short sequences of DNA by expanding the diagrammatic theory up to second order in the hopping parameters. The correlations qualitatively modify the I-V characteristics as compared to those approaches where correlations are dealt with in a mean-field type approximation only.

Towards far-from-equilibrium quantum field dynamics: A functional renormalisation-group approach

Dynamic equations for quantum fields far from equilibrium are derived by use of functional renormalisation group techniques. The obtained equations are non-perturbative and lead substantially beyond mean-field and quantum Boltzmann type approximations. The approach is based on a regularised version of the generating functional for correlation functions where times greater than a chosen cutoff time are suppressed. As a central result, a time evolution equation for the non-equilibrium effective action is derived, and the time evolution of the Green functions is computed within a vertex expansion. It is shown that this agrees with the dynamics derived from the 1 / N -expansion of the two-particle irreducible effective action.

A generating functional approach to the Hubbard model

The method of generating functional is generalized to the case of strongly correlated systems, and applied to the Hubbard model. For the electronic Green's function constructed for Hubbard operators, an equation using variational derivatives with respect to the fluctuating fields has been derived and its multiplicative form has been determined. Corrections for the electronic self-energy are calculated up to the second order with respect to the parameter W/U (W width of the band), and a mean field type approximation was formulated, including both charge and spin static fluctuations. The equations for the Bose-like Green's functions have been derived, describing the collective modes: the magnons and doublons. The properties of the poles of the doublon Green's functions depend on electronic filling. The investigation of the special case n=1 demonstrates that the doublon Green's function has a soft mode at the wave vector Q=(pi,pi,...), indicating possible instability of the uniform paramagnetic phase relatively to the two sublattices charge ordering. However this instability should compete with an instability to antiferromagnetic ordering.

Nature of phase transitions in a generalized complex∣ψ∣4model

We employ Monte Carlo simulations to study a generalized three-dimensional complex $psi|^4 theory of Ginzburg-Landau form and compare our numerical results with a recent quasi-analytical mean-field type approximation, which predicts first-order phase transitions in parts of the phase diagram. As we have shown earlier, this approximation does not apply to the standard formulation of the model. This motivated us to introduce a generalized Hamiltonian with an additional fugacity term controlling implicitly the vortex density. With this modification we find that the complex |psi|^4 theory can, in fact, be tuned to undergo strong first-order phase transitions. The standard model is confirmed to exhibit continuous transitions which can be characterized by XY model exponents, as expected by universality arguments. A few remarks on the two-dimensional case are also made.

Separability conditions and limit temperatures for entanglement detection in two-qubit HeisenbergXYZmodels

We examine the entanglement of general mixed states of a two qubit Heisenberg XYZ chain in the presence of a magnetic field, and its detection by means of different criteria. Both the exact separability conditions and the weaker conditions implied by the disorder and the von Neumann entropic criteria are analyzed. The ensuing limit temperatures for entanglement in thermal states of different XYZ models are then examined and compared with the limit temperature of the symmetry-breaking solution in a mean field type approximation. The latter, though generally lower, can also be higher than the exact limit temperature for entanglement in certain cases, indicating that symmetry-breaking does not necessarily entail entanglement. The reentry of entanglement for increasing temperatures is also discussed.

Brownian dynamics simulations of ion atmospheres around polyalanine and B-DNA: effects of biomolecular dielectric.

We have extended an earlier Brownian dynamics simulation algorithm for simulating the structural dynamics of ions around biomolecules to accommodate dielectric inhomogeneity. The electrostatic environment of a biomolecule immersed in water was obtained by numerically solving the Poisson equation with the biomolecule treated as a low dielectric region and the solvent treated as a high dielectric region. Instead of using the mean-field type approximations of ion interactions as in the Poisson-Boltzmann model, the ions were treated explicitly by allowing them to evolve dynamically under the electrostatic field of the biomolecule. This model thus accounts for ion-ion correlations and the finite-size effects of the ions. For a 13-residue alpha-helical polyalanine and a 12-base-pair bp B-form DNA, we found that the choice of the dielectric constant of the biomolecule has much larger effects on the mean ionic structure around the biomolecule than on the fluctuational and dynamical properties of the ions surrounding the biomolecule.

Fluctuating pulled fronts: The origin and the effects of a finite particle cutoff.

Recently, it has been shown that when an equation that allows the so-called pulled fronts in the mean-field limit is modeled with a stochastic model with a finite number N of particles per correlation volume, the convergence to the speed v(*) for N--> infinity is extremely slow-going only as ln(-2)N. Pulled fronts are fronts that propagate into an unstable state, and the asymptotic front speed is equal to the linear spreading speed v(*) of small linear perturbations about the unstable state. In this paper, we study the front propagation in a simple stochastic lattice model. A detailed analysis of the microscopic picture of the front dynamics shows that for the description of the far tip of the front, one has to abandon the idea of a uniformly translating front solution. The lattice and finite particle effects lead to a "stop-and-go" type dynamics at the far tip of the front, while the average front behind it "crosses over" to a uniformly translating solution. In this formulation, the effect of stochasticity on the asymptotic front speed is coded in the probability distribution of the times required for the advancement of the "foremost bin." We derive expressions of these probability distributions by matching the solution of the far tip with the uniformly translating solution behind. This matching includes various correlation effects in a mean-field type approximation. Our results for the probability distributions compare well to the results of stochastic numerical simulations. This approach also allows us to deal with much smaller values of N than it is required to have the ln(-2)N asymptotics to be valid. Furthermore, we show that if one insists on using a uniformly translating solution for the entire front ignoring its breakdown at the far tip, then one can obtain a simple expression for the corrections to the front speed for finite values of N, in which various subdominant contributions have a clear physical interpretation.

SOC in a population model with global control

We study a plant population model introduced recently by Wallinga (OIKOS 74 (1995) 377). It is similar to the contact process (‘simple epidemic’, ‘directed percolation’), but instead of using an infection or recovery rate as control parameter, the population size is controlled directly and globally by removing excess plants. We show that the model is very closely related to directed percolation (DP). Anomalous scaling laws appear in the limit of large populations, small densities, and long times. These laws, associated critical exponents, and even some non-universal parameters, can be related to those of DP. As in invasion percolation and in other models where the rôles of control and order parameters are interchanged, the critical value p c of the wetting probability p is obtained in the scaling limit as singular point in the distribution of removal rates. We show that a mean field type approximation leads to a model studied by Zhang et al. (J. Stat. Phys. 58 (1990) 849). Finally, we verify the claim of Wallinga that family extinction in a marginally surviving population is governed by DP scaling laws, and speculate on applications to human mitochondrial DNA.

Interplay between superconductivity and flux phase in thet−Jmodel

We study the phase diagram of the t-J model using a mean field type approximation within the Baym-Kadanoff perturbation expansion for Hubbard $X$-operators. The line separating the normal state from a d-wave flux or bond-order state starts near optimal doping at T=0 and rises quickly with decreasing doping. The transition temperature $T_c$ for d-wave superconductivity increases monotonically in the overdoped region towards optimal doping. Near optimaldoping a strong competition between the two d-wave order parameters sets in leading to a strong suppression of $T_c$ in the underdoped region. Treating for simplicity the flux phase as commensurate the superconducting and flux phases coexist in the underdoped region below $T_c$, whereas a pure flux phase exists above $T_c$ with a pseudo-gap of d-wave symmetry in the excitation spectrum. We also find that incommensurate charge-density-wave ground states due to Coulomb interactions do not modify strongly the above phase diagram near the superconducting phase, at least, as long as the latter exists at all.

Transport phenomena at a critical point: Thermal conduction in the Creutz cellular automaton

Nature of energy transport around a critical point is studied in the Creutz cellular automaton. Fourier heat law is confirmed to hold in this model by a direct measurement of heat flow under a temperature gradient. The thermal conductivity is carefully investigated near the phase transition by the use of the Kubo formula. As the result, the thermal conductivity is found to take a finite value at the critical point contrary to some previous works. Equal-time correlation of the heat flow is also analyzed by a mean-field type approximation to investigate the temperature dependence of thermal conductivity. A variant of the Creutz cellular automaton called the Q2R is also investigated and similar results are obtained.

From Solid State Diffusion to Configurational Kinetics

ABSTRACTA single model is proposed to describe the cohesive energy and the vacancy jump frequencies as a function of the alloy configuration at the atomic level. The very same model therefore yields both equilibrium and kinetic properties, close and far away from equilibrium. The model is handled at two levels of approximation: Monte Carlo techniques and mean-field type approximations. The model yields equilibrium properties (including the transport coefficients and complex diffusion mechanisms in ordered compounds close to equilibrium) as well as the kinetic path for phase separation, with or without ordering. This allows to identify specific effects of the vacancy diffusion mechanism on the kinetic path for alloy decomposition. Here, we summarise the main results of the above approach.

Collective low-energy excitations of two-level tunnelling defects in mixed crystals

The dynamics of strongly interacting two-level tunnelling defects in mixed crystals as KCl: Li is investigated in the framework of Mori's projection method. Applying a mode-coupling scheme on the memory functions and performing the average over the random defect configuration in a mean-field type approximation, the ensueing self-consistent equations can be solved analytically. At low concentration this solution coincides with the exact dynamics of the pair model, whereas for higher concentration the motional spectrum shows several novel features. In particular we find a strong relaxation peak and a characteristic two-peak structure for the density of states; there is an additional feature at energies far below the bare tunnelling amplitude e which accounts well for several experiments indicating the existence of such low-energy states.

Accurate estimates of 3D Ising critical exponents using the coherent-anomaly method

An analysis of the critical behavior of the three-dimensional Ising model using the coherent-anomaly method (CAM) is presented. Various sources of errors in CAM estimates of critical exponents are discussed, and an improved scheme for the CAM data analysis is tested. Using a set of mean-field type approximations based on the variational series expansion approach, accuracy comparable to the most precise conventional methods has been achieved. Our results for the critical exponents are given by α = 0.108(5), β = 0.327(4), γ = 1.237(4) and δ = 4.77(5).

Percolative phase separation: Mean-field calculations of spin polarized states in CuO2 planes

We investigate the appearance of spin polarized states (magnetic polarons) in hole doped CuO 2 layers in the high- T c systems. Starting from a three-band Hubbard model which is treated in mean-field type approximation, the spin disturbed structure around a single hole is studied in detail. The change of the spin cluster polarisation towards metalisation in dependence of the hole concentration is discussed. In addition the influence of the structure of single hole clusters onto the behaviour of the phase separation is shown.