On the stochastic dynamics of Ising models

With the help of recent results in the mathematical theory of master equations, we present a rigorous derivation of the stochastic Glauber dynamics of Ising models from Hamiltonian quantum mechanics. A thermal bath is explicitly constructed and, as an illustration, the dynamics of the Ising-Weiss model is analyzed in the thermodynamic limit. We thus obtain an example of a nonequilibrium statistical mechanical system for which a link without mathematical gap can be established from microscopic quantum mechanics to a macroscopic irreversible thermodynamic process.     

Reduced Markov chains at stochastic spin models

From Glauber's stochastic spin model in discrete time, reduced Markov-chain models are constructed. The transition matrices of the reduced models utilize equilibrium correlation functions of the full N-spin system; however, the reduced models involve the time-dependent behavior of only a cluster of spins. The reduced models have as an invariant vector the exact marginal equilibrium probability for the spins in the cluster. In that sense, the reduced models have the same equilibrium as the N-spin Glauber model, but will, in general, display a different time dependence. One of the reduced models is solved exactly here for a one-dimensional lattice, a square lattice, and a simple-cubic lattice.     

Interface motion in models with stochastic dynamics

We derive the phenomenological dynamics of interfaces from stochastic microscopic models. The main emphasis is on models with a nonconserved order parameter. A slowly varying interface has then a local normal velocity proportional to the local mean curvature. We study bulk models and effective interface models and obtain Green-Kubo-like expressions for the mobility. Also discussed are interface motion in the case of a conserved order parameter, pure surface diffusion, and interface fluctuations. For the two-dimensional Ising model at zero temperature, motion by mean curvature is established rigorously.     

Reduced dynamics and the master equation of open quantum systems

An exact reduced density operator of a quantum system interacting with a bosonic thermal reservoir is derived by means of the simple algebraic method. The necessary and sufficient condition is found that the time-convolutionless master equation becomes exact up to the second order with respect to the system-reservoir interaction. The result is examined by means of the boson-detector model. The reduced dynamics of a quantum system interacting with a classical reservoir is also discussed.     

Cross-correlation markers in stochastic dynamics of complex systems

The neuromagnetic activity (magnetoencephalogram, MEG) from healthy human brain and from an epileptic patient against chromatic flickering stimuli has been earlier analyzed on the basis of a memory functions formalism (MFF). Information measures of memory as well as relaxation parameters revealed high individuality and unique features in the neuromagnetic brain responses of each subject. The current paper demonstrates new capabilities of MFF by studying cross-correlations between MEG signals obtained from multiple and distant brain regions. It is shown that the MEG signals of healthy subjects are characterized by well-defined effects of frequency synchronization and at the same time by the domination of low-frequency processes. On the contrary, the MEG of a patient is characterized by a sharp abnormality of frequency synchronization, and also by prevalence of high-frequency quasi-periodic processes. Modification of synchronization effects and dynamics of cross-correlations offer a promising method of detecting pathological abnormalities in brain responses.     

Quasi-gradient models of the dynamics of closed chemical systems

A new class of models of the chemical dynamics of closed systems, quasi-gradient models, is suggested. According to these models, the evolution of a chemically reacting system to the equilibrium state occurs along a thermodynamic potential gradient with an accuracy to a positive definite multiplier.     

The strong decay to equilibrium for the stochastic dynamics of unbounded spin systems on a lattice

Using a method based on the application of hypercontractivity we prove the strong exponential decay to equilibrium for a stochastic dynamics of unbounded spin system on a lattice.     

A mathematical framework for critical transitions: Bifurcations, fast-slow systems and stochastic dynamics

Bifurcations can cause dynamical systems with slowly varying parameters to transition to far-away attractors. The terms “critical transition” or “tipping point” have been used to describe this situation. Critical transitions have been observed in an astonishingly diverse set of applications from ecosystems and climate change to medicine and finance. The main goal of this paper is to give an overview which standard mathematical theories can be applied to critical transitions. We shall focus on early-warning signs that have been suggested to predict critical transitions and point out what mathematical theory can provide in this context. Starting from classical bifurcation theory and incorporating multiple time scale dynamics one can give a detailed analysis of local bifurcations that induce critical transitions. We suggest that the mathematical theory of fast-slow systems provides a natural definition of critical transitions. Since noise often plays a crucial role near critical transitions the next step is to consider stochastic fast-slow systems. The interplay between sample path techniques, partial differential equations and random dynamical systems is highlighted. Each viewpoint provides potential early-warning signs for critical transitions. Since increasing variance has been suggested as an early-warning sign we examine it in the context of normal forms analytically, numerically and geometrically; we also consider autocorrelation numerically. Hence we demonstrate the applicability of early-warning signs for generic models. We end with suggestions for future directions of the theory.     

Time-reversal test for stochastic quantum dynamics

The calculation of quantum dynamics is currently a central issue in theoretical physics, with diverse applications ranging from ultracold atomic Bose-Einstein condensates to condensed matter, biology, and even astrophysics. Here we demonstrate a conceptually simple method of determining the regime of validity of stochastic simulations of unitary quantum dynamics by employing a time-reversal test. We apply this test to a simulation of the evolution of a quantum anharmonic oscillator with up to 6.022x10(23) (Avogadro's number) of particles. This system is realizable as a Bose-Einstein condensate in an optical lattice, for which the time-reversal procedure could be implemented experimentally.     

Efficient numerical integrators for stochastic models

The efficient simulation of models defined in terms of stochastic differential equations (SDEs) depends critically on an efficient integration scheme. In this article, we investigate under which conditions the integration schemes for general SDEs can be derived using the Trotter expansion. It follows that, in the stochastic case, some care is required in splitting the stochastic generator. We test the Trotter integrators on an energy-conserving Brownian model and derive a new numerical scheme for dissipative particle dynamics. We find that the stochastic Trotter scheme provides a mathematically correct and easy-to-use method which should find wide applicability.     

Fluctuation theorem for stochastic systems

The fluctuation theorem describes the probability ratio of observing trajectories that satisfy or violate the second law of thermodynamics. It has been proved in a number of different ways for thermostatted deterministic nonequilibrium systems. In the present paper we show that the fluctuation theorem is also valid for a class of stochastic nonequilibrium systems. The theorem is therefore not reliant on the reversibility or the determinism of the underlying dynamics. Numerical tests verify the theoretical result.     

Non-traditional stochastic models for ocean waves

We present two flexible stochastic models for 2D and 3D ocean waves with potential to reproduce severe and non-homogeneous sea conditions. The first family consists of generalized Lagrange models for the movements of individual water particles. These models can generate crest-trough and front-back statistically asymmetric waves, with the same degree of asymmetry as measured ocean waves. They are still in the Gaussian family and it is possible to calculate different slope distributions exactly from a wave energy spectrum. The second model is a random field model that is generated by a system of nested stochastic partial differential equations. This model can be adapted to spatially non-homogeneous sea conditions and it can approximate standard wave spectra. One advantage with this model is that Hilbert space approximations can be used to obtain computationally efficient representations with Markov-type properties that facilitate the use of sparse matrix techniques in simulation and estimation.     

Vibrational analysis of structures with stochastic interfaces in the medium-frequency range: Experimental validation on a touch screen

This paper proposes a dedicated approach and its experimental validation when dealing with structures (including stochastic parameters, such as interface parameters) in medium-frequency vibrations. The first ingredient is the use of a dedicated approach – the Variational Theory of Complex Rays (VTCR) – to solve the medium-frequency problem. The VTCR, which uses two-scale shape functions verifying the dynamic equation and the constitutive relation, can be viewed as a means of expressing the power balance at the different interfaces between substructures. The second ingredient is the use of the Polynomial Chaos Expansion (PCE) to calculate the random response. Since the only uncertain parameters are those which appear in the interface equations (which, in this application, are the complex connection stiffness parameters), this approach leads to very low computation costs. This method is validated on a new kind of touch screen. The simulated mobilities are compared with experimental ones obtained with a laser vibrometer and a good agreement is founded on a large medium-frequency bandwidth.     

A stochastic model for microtubule length dynamics

In this paper, we use random walk theory to describe the length dynamics of microtubules, one of the principal components of the cytoskeleton. We present a simple two-state model (growing and shrinking) of microtubule length evolution that incorporates a variable rate of switching between the states. Using the generating function technique, we calculate the mean length of microtubule, its variance and diffusion coefficient. We also report analytical and computer simulation results for the mean number of positive monomers in microtubule, and find good qualitative agreement with experimental data.