Slowly moving matter--wave gap soliton propagation in weak random nonlinear potential

We systematically investigate the motion of slowly moving matter--wave gap solitons in a nonlinear potential, produced by the weak random spatial variation of the atomic scattering length. With the weak randomness, we construct an effective-particle theory to study the motion of gap solitons. Based on the effective-particle theory, the effect of the randomness on gap solitons is obtained, and the motion of gap solitons is finally solved. Moreover, the analytic results for the general behaviours of gap soliton motion, such as the ensemble-average speed and the reflection probability depending on the weak randomness are obtained. We find that with the increase of the random strength the ensemble-average speed of gap solitons decreases slowly where the reduction is proportional to the variance of the weak randomness, and the reflection probability becomes larger. The theoretical results are in good agreement with the numerical simulations based on the Gross--Pitaevskii equation.     

Slowly moving matter-wave gap soliton propagation in weak random optical lattices

We systematically investigate slowly moving matter-wave gap soliton propagation in weak random optical lattices. With the weak randomness, an effective-particle theory is constructed to show that the motion of a gap soliton is similar to a particle moving in random potentials. Based on the effective-particle theory, the effects of the randomness on gap solitons are obtained and the trajectories of gap solitons are well predicted. Moreover, the general laws that describe the movement depending on the weak randomness are obtained. We find that with an increase of the random strength, the ensemble-average velocity reduces slowly and the reflection probability becomes larger. The theoretical results based on the effective-particle theory are confirmed by the numerical simulations based on the Gross-Pitaevskii equation.     

Prequantum Classical Statistical Field Theory: Schrödinger Dynamics of Entangled Systems as a Classical Stochastic Process

The idea that quantum randomness can be reduced to randomness of classical fields (fluctuating at time and space scales which are essentially finer than scales approachable in modern quantum experiments) is rather old. Various models have been proposed, e.g., stochastic electrodynamics or the semiclassical model. Recently a new model, so called prequantum classical statistical field theory (PCSFT), was developed. By this model a “quantum system” is just a label for (so to say “prequantum”) classical random field. Quantum averages can be represented as classical field averages. Correlations between observables on subsystems of a composite system can be as well represented as classical correlations. In particular, it can be done for entangled systems. Creation of such classical field representation demystifies quantum entanglement. In this paper we show that quantum dynamics (given by Schrödinger’s equation) of entangled systems can be represented as the stochastic dynamics of classical random fields. The “effect of entanglement” is produced by classical correlations which were present at the initial moment of time, cf. views of Albert Einstein.     

McKean-Vlasov limit for interacting random processes in random media

We apply large-deviation theory to particle systems with a random mean-field interaction in the McKean-Vlasov limit. In particular, we describe large deviations and normal fluctuations around the McKean-Vlasov equation. Due to the randomness in the interaction, the McKean-Vlasov equation is a collection of coupled PDEs indexed by the state space of the single components in the medium. As a result, the study of its solution and of the finite-size fluctuation around this solution requires some new ingredient as compared to existing techniques for nonrandom interaction.     

Transport theory of dissipative heavy-ion collisions

The non-perturbative quantum-statistical theory of dissipative heavy-ion collisions introduced earlier, is generalized by including explicitly the relative motion of the colliding nuclei. We start from the Liouville equation in the Wigner representation which allows for useful and illustrative interpretations of the resulting quantities and equations. Using the randomness of the coupling matrix elements and the semi-classical approximation for the relative motion we derive a general time-dependent transport equation for the macroscopic Wigner functions (phase-space distribution functions). The limits of weak and strong coupling are discussed.     

The diffusion equation of random genetic drift – biology’s analogue of the Schrödinger equation?

This work is a self-contained introduction to some basic aspects of the dynamics that occurs in biological populations. It focusses on the proportion (or frequency) of a population that carries a particular gene. We make use of the notion of a force, in the context of genetics and evolution, to describe the dynamics of the frequency in an effectively infinite population. We then show how randomness enters into the dynamics of populations with a finite size, a randomness known as random genetic drift. We derive an equation, involving random numbers, which describes how the frequency behaves in a population of finite size. It is shown that in some situations this equation exhibits irreversible absorption phenomena. These phenomena are associated with the extinction (or loss) of the gene, or the complete takeover by the gene (termed fixation), where 100% of the population carries the gene. Taking the theory further, we show how an approximation leads to a stochastic differential equation for the frequency, where random genetic drift takes the form of an additional contribution to the force, that randomly fluctuates. The stochastic differential equation is, in turn, related to a diffusion equation, which encompasses many fundamental phenomena. Because of this, the diffusion equation plausibly has a similar status in biology to the Schrödinger equation in physics. It is notable that both the Schrödinger equation and the diffusion equation have a somewhat similar mathematical structure: they both involve first order derivatives of time and second order derivatives of space (or the analogue of space). There are, however, some significant mathematical differences. In contrast to the Schrödinger equation, the diffusion equation can routinely have solutions which are singular, in that the solutions contain Dirac delta functions. The delta functions are not, however, problematic, and have an explicit biological significance. We illustrate results with some basic calculations and computer simulations.     

Convergence to SPDEs in Stratonovich Form

We consider the perturbation of parabolic operators of the form ∂ _t  + P(x, D) by large-amplitude highly oscillatory spatially dependent potentials modeled as Gaussian random fields. The amplitude of the potential is chosen so that the solution to the random equation is affected by the randomness at the leading order. We show that, when the dimension is smaller than the order of the elliptic pseudo-differential operator P(x, D), the perturbed parabolic equation admits a solution given by a Duhamel expansion. Moreover, as the correlation length of the potential vanishes, we show that the latter solution converges in distribution to the solution of a stochastic parabolic equation with multiplicative noise that should be interpreted in the Stratonovich sense. The theory of mild solutions for such stochastic partial differential equations is developed. The behavior described above should be contrasted to the case of dimensions larger than or equal to the order of the elliptic pseudo-differential operator P(x, D). In the latter case, the solution to the random equation converges strongly to the solution of a homogenized (deterministic) parabolic equation as is shown in [2]. A stochastic limit is obtained only for sufficiently small space dimensions in this class of parabolic problems.     

Variance and Entropy Assignment for Continuous-Time Stochastic Nonlinear Systems

This paper investigates the randomness assignment problem for a class of continuous-time stochastic nonlinear systems, where variance and entropy are employed to describe the investigated systems. In particular, the system model is formulated by a stochastic differential equation. Due to the nonlinearities of the systems, the probability density functions of the system state and system output cannot be characterised as Gaussian even if the system is subjected to Brownian motion. To deal with the non-Gaussian randomness, we present a novel backstepping-based design approach to convert the stochastic nonlinear system to a linear stochastic process, thus the variance and entropy of the system variables can be formulated analytically by the solving Fokker–Planck–Kolmogorov equation. In this way, the design parameter of the backstepping procedure can be then obtained to achieve the variance and entropy assignment. In addition, the stability of the proposed design scheme can be guaranteed and the multi-variate case is also discussed. In order to validate the design approach, the simulation results are provided to show the effectiveness of the proposed algorithm.     

Mathematical modeling of randomness and fuzziness phenomena in scientific studies: I. Mathematical and empirical foundations

The possibility theory as a mathematical model of randomness and fuzziness phenomena is considered in a variant that enables the modeling of both probabilistic randomness, including that inherent in unpredictably evolving stochastic objects whose probabilistic models cannot be empirically reconstructed and nonprobabilistic randomness (fuzziness) inherent in real physical, technical, and economical objects, human–machine and expert systems, etc. Some principal distinctions between the considered variant and the known possibility theory variants, in particular, in mathematical formalism and its relationship with probability theory, substantive interpretation, and applications exemplified by solving the problems of identification and estimation optimization, empirical reconstruction of a fuzzy model for a studied object, measurement data analysis and interpretation, etc. (in the paper “Mathematical Modeling of Randomness and Fuzziness Phenomena in Scientific Studies. II. Applications”) are shown.     

Lamellar pattern formation in small-world media

Numerical and analytical techniques are used to investigate the effects of quenched disorder of small-world networks on the phase ordering dynamics of lamellar patterns as modeled by the Swift-Hohenberg equation. Morphologies for small and large values of the network randomness are quite different. It is found that addition of shortcuts to an underlying regular lattice makes the growth of domains evolving from random initial conditions much slower at late times. As the randomness increases, the evolution is eventually frozen.     

The hierarchy of correlations in random binary sequences

The meaning of randomness is studied for the simple case of binary sequences. Ensemble theory is used, together with correlation coefficients of any order. Conservation laws for the total amount of correlation are obtained. They imply that true randomness is an ensemble property and can never be achieved in a single sequence. The relation with entropy is discussed for different ensembles. Well-tempered pseudorandom sequences turn out to be suitable sources of random numbers, and practical recipes to generate them for use in large-scale Monte Carlo simulations are found.     

Discrete asymptotic deterministic randomness for the generation of pseudorandom bits

The deterministic randomness not only can become a dominant approach in exploring the relationship between chaos and randomness, but also can be associated with some famous number theoretical concepts and open problems in number theory. Compared with chaotic sequences, asymptotic deterministic randomness sequences have the characteristic of multi-value correspondence, which makes those sequences unpredictable in short steps. In this Letter, we will propose the definition of the discrete asymptotic deterministic randomness, and then analyze the dynamical characteristics such as maximum-period and multi-value correspondence. Referring to the NIST800-22 statistical test suite, we will present and discuss two examples of PRBGs based on DADR, from the point of view of FPGA design and randomness quality.     

The Einstein-Smoluchowski promeasure versus the Boltzmann(-Peierls) equation

Beginning from the specific model of the Boltzmann-Peierls equation for the distribution function f(k, t), the time-dependent theory of fluctuations is developed from Einstein's inversion of Boltzmann's relation. The distribution function f(k, t) that satisfies the Boltzmann-Peierls equation is to be viewed as a random variable characterizing the macro-state of a gas of quasiparticles (phonons, magnons, rotons, etc.). The crucial assumption entering into the present approach is simply that the randomness in the statistical distribution of the initial values of f(k, t) can be characterized by the Einstein-Smoluchowski promeasure μ_ε. It is convenient to think of μ_ε as being the infinite-dimensional analog of Einstein's distribution law in the Gaussian approximation. The equilibrium promeasure μ_ε is used to study the correlations in time of fluctuations in the moments of f(k, t). Some problems associated with a kinetic version of the Green-Kubo approach to transport processes are carefully studied. The exact formula for the thermal conductivity coefficient _T, which is derived in this paper, emerges as a portion of the general formalism.     

A vectorizable random lattice

We describe a family of random lattices in which the connectivity is determined by the Voronoi construction while the vectorizability is not lost. We can continuously vary the degree of randomness so in a certain limit a regular lattice is recovered. Several statistical properties of the cells and bonds of these lattices are measured. We also study anisotropy effects on the numerical solution of the Laplace equation for varying degrees of randomness.     

Single-site theory for the random Hubbard alloy

A new theory for the random system with electron correlation is presented, which is an extension of the Hubbard's theory for the random system and also an extension of the CPA for the interacting electron system. The equation of motion for the Green function is solved by the same decoupling method used by Hubbard. The self-consistent relations for the Green function, the self-energy and the effective occupation number are derived. It is predicted in the binary alloy system that tails or satellites of the state density are produced by the combined effect of the randomness and electron correlation. The origin of the tail is the inelastic scattering of the electron byA — B atomic pairs, whose electronic configuration is changed during the scattering. Numerical calculations are reported for a simple model.     

Quaternionic quantum field theory

We show that a quaternionic quantum field theory can be formulated when the numbers of bosonic and fermionic degrees of freedom are equal and the fermions, as well as the bosons, obey a second order wave equation. The theory takes the form of either a functional integral with quaternion-imaginary Lagrangian, or a Schrödinger equation and transformation theory for quaternion-valued wave functions, with a quaternion-imaginary Hamiltonian. The connection between the two formulations is developed in detail, and many related issues, including the breakdown of the correspondence principle and the Hilbert space structure, are discussed.     

Structure of Hamiltonian Matrix and the Shape of Eigenfunctions：Nuclear Octupole Deformation Model

The structure of a Hamiltonian matrix for a quantum chaotic system,the nuclear octupole deformation model,has been discussed in detail.The distribution of the eigenfunctions of this system expanded by the eigenstates of a quantum integrable system is studied with the help of generalized Brillouin-Wigner perturbation theory.The results show that a significant randomness in this distribution can be observed when its classical counterpart is under the strong chaotic condition.The averaged shape of the eigenfunctions fits with the Gaussian distribution only when the effects of the symmetry have been removed.     

Stability of the Haldane state against the antiferromagnetic-bond randomness

Ground-state phase diagram of the one-dimensional bond-random S=1 Heisenberg antiferromagnet is investigated by means of the loop-cluster-update quantum Monte-Carlo method. The random couplings are drawn from a rectangular uniform distribution. We found that even in the case of extremely broad bond distribution, the magnetic correlation decays exponentially, and the correlation length is hardly changed; namely, the Haldane phase continues to be realized. This result is accordant with that of the exact-diagonalization study, whereas it might contradict the conclusion of an analytic theory founded in a power-law bond distribution instead. The latter theory predicts that a second-order phase transition occurs at a certain critical randomness, and the correlation length diverges for sufficiently strong randomness. Received: 31 March 1998 / Revised and Accepted: 7 July 1998     

位错密度的演化动力学方程

 将位错的增殖、淹没与相互反应看作化学反应，位错在热激活作用下具有扩散性质。因此，位错系统是一个反应-扩散系统。依据自组织理论，给出了两个位错密度演化动力学方程，当系统发生结构失稳之后，第一个方程变成第二个方程；第一个方程含有对称性破缺，按Higgs机制将发射偶极子。     

Random solution of the Burgers equation in the inviscid case

The structure of solutions of the Burgers equation in the inviscid case is investigated numerically by computing the space-time behavior of the asymptotic solutions expressed as sequences of triangular shock waves. They are sensitively dependent on initial conditions and can display intrinsic randomness, depending on the number of zeros of the initial velocity fields.