International Journal of Modern Physics C

In the study of QCD dynamics, C^⋆ boundary conditions are physically relevant in certain cases. In this paper, we study the implementation of these boundary conditions in the lattice formulation of full QCD with staggered fermions. In particular, we show that the usual even-odd partition trick to avoid the redoubling of the fermion matrix is still valid in this case. We give an explicit implementation of these boundary conditions for the Hybrid Monte Carlo algorithm.

A two-dimensional numerical model was developed^1–3 to simulate the sediment and pollutant transport in a shallow basin. The developed model consist of two modules: Hydrodynamic module and sediment/pollutant transport module. A numerical hydrodynamic module based on the Saint-Venant equations, is resolved by a MacCormack numerical scheme and is used to simulate the circulation pattern in the basin. The obtained flow circulation is used as an input to the sediment/pollutant transport module to simulate the transport and dispersion of a pollutant emitted into the basin. To calibrate the numerical model, the distorted scale model of the Windermere Basin⁴ was used. In this physical model, the flow visualization and pollutant transport experiments provide a good calibration. The simulated results were found to be in good agreement with the experimental measurements and the results in Ref. 4. With the aid of the validated model, the influence of the construction of dikes on the residence time distributions in the basin was examined.

Lately, the Local Iterative Monte Carlo technique was introduced for an efficient simulation of effects connected to sparsely populated regions in semiconductor devices like hot electron effects in silicon MOSFETs. This paper focuses on computational aspects of this new Monte Carlo technique, namely the reduction of the computation time by parallel computation and the reuse of drift information. The Local Iterative Monte Carlo technique combines short Monte Carlo particle flight simulations with an iteration process to a complete device simulation. The separation between short Monte Carlo simulations and the iteration process makes a simple parallelization strategy possible. The necessary data transfer is small and can be performed via the Network File System. An almost linear speed up could be achieved. Besides by parallelization, the computational expenses can be significantly reduced, when the results of the short Monte Carlo simulations are memorized in a drift table and used several times. A comparison between a bulk, a one-dimensional and the two-dimensional Local Iterative Monte Carlo simulation reveals that by using the drift information more than once, becomes increasingly efficient with increasing dimension of the simulation.

We have applied two methods (simulated annealing and genetic algorithms) to search the solution of a problem of optimization with constraints in order to determine the best way to fulfill different energy demands using a set of facilities of energy transformation and storage. We have introduced a computational efficiency factor that measures the efficiency of the optimization algorithm and, as a result, we can conclude that for short computation times, genetic algorithms are more efficient than simulated annealing when demand profiles are not very long, whereas the latter is more efficient than the former for long computation time or for big demand profiles.

Universality of ratios of cumulants depends on the minor changes in the definition of time.

The Social Percolation model recently proposed by Solomon et al. is studied on the Ising correlated inhomogeneous network. The dynamics in this is studied so as to understand the role of correlations in the social structure. Thus, the possible role of the structural social connectivity is examined.

The q = 8 state Potts model with varying amount of quenched bond randomness is simulated in two dimensions by using a cluster algorithm. It is shown that, by monitoring the autocorrelation times, one can trace down the threshold value of the introduced quenched bond randomness for the rounding of the first-order phase transition.

We present a simple and general result that the sign of the variations or increments of uncorrelated times series are predictable with a remarkably high success probability of 75% for symmetric sign distributions. The origin of this paradoxical result is explained in details. We also present some tests on synthetic, financial and global temperature time series.

Winding angle problem of two-dimensional self-avoiding walks (SAWs) on a square lattice is studied intensively by the scanning Monte Carlo simulation at high, theta (Θ), and low-temperatures. The winding angle distribution P_N(θ) and the even moments of winding angle are calculated for lengths of SAWs up to N = 300 and compared with the analytical prediction. At the infinite temperature (good solvent regime of linear polymers), P_N(θ) is well described by either a Gaussian function or a stretched exponential function which is close to Gaussian, so, it is not incompatible with an analytical prediction that it is a Gaussian function exp[-θ²/ln N] in terms of a variable and that . However, the results for SAWs at Θ and low-temperatures (Θ and bad solvent regime of linear polymers) significantly deviate from this analytical prediction. P_N(θ) is then described much better by a stretched exponential function exp[-|θ|^α/ln N] and with α = 1.54 and 1.51 which is far from being a Gaussian. We provide a consistent numerical evidence that the winding angle distribution for SAWs at the finite temperatures may not be a Gaussian function but a nontrivial distribution, possibly a stretched exponential function.

The winding angle problem of two-dimensional lattice trails on a square lattice is studied intensively by the scanning Monte Carlo simulation at infinite, tricritical, and low-temperatures. The winding angle distribution P_N(θ) and the even moments of winding angle are calculated for the lengths of trails up to N = 300. At infinite temperature, trails share the same universal winding angle distribution with self-avoiding walks (SAWs), which is a stretched exponential function close to a Gaussian function exp[-θ²/ln N] and . However, trails at tricritical and low-temperatures do not share the same winding angle distribution with SAWs. For trails, P_N(θ) is described well by a stretched exponential function exp[-|θ|^α/ln N] and with α ~ 1.69 which is far from being a Gaussian and also different from those of SAWs at Θ and low-temperatures with α ~ 1.54. We provide a consistent numerical evidence that the winding angle distribution for trails at finite temperatures may not be a Gaussian function, but, a nontrivial distribution, possibly a stretched exponential function. Our result also demonstrates that the universality argument between trails and SAWs at infinite and tricritical temperatures indeed persists to the distribution function of winding angle and its associated scaling behavior.

The structure of satisfiability problems is used to improve search algorithms for quantum computers and to reduce their required coherence times by using only a single coherent evaluation of problem properties. The structure of random k-SAT allows the determination of the asymptotic average behavior of these algorithms, showing they improve on the quantum algorithms, such as amplitude amplification, that ignore detailed problem structure but remain exponential for hard problem instances. Compared to good classical methods, the algorithm performs better, on average, for weakly and highly constrained problems, but worse for hard cases. The analytic techniques introduced here apply also to other quantum algorithms, supplementing the limited evaluation possible with classical simulations, and showing how quantum computing can use the ensemble properties of NP search problems.

The Penna model of aging predicts the accumulation of defective genes expressed after the organism reaches the minimum reproduction age in the genetic pool of the population. The accumulation of defects in the genomes implicates the specific age structure of the modeled populations. Nevertheless, the fraction of defective alleles at loci switched on before the reproduction period does not depend on exact age when precisely they are switched on, it may be just after conception or after birth. We have modeled the mortality of a population in the period before the minimum reproduction age, even before birth, assuming that sets of genes of different size are switched on in different periods of the life span.

Fourth order exponential and trigonometric fitted Runge–Kutta methods are developed in this paper. They are applied to problems involving the Schrödinger equation and to other related problems. Numerical results show the superiority of these methods over conventional fourth order Runge–Kutta methods. Based on the methods developed in this paper, a variable-step algorithm is proposed. Numerical experiments show the efficiency of the new algorithm.

Molecular self-assembly plays a crucial role as a structural and an organizational principle in supramolecular architecture. The key feature of this process is the generation of higher order molecular structures, and is solely determined by the dynamics of the individual molecular objects, characterized by an overall minimum free energy situation. Equally important as the constructional aspect of the formation process, these macromolecular assemblies carry novel functionalities which can be solely observed at the level of the supramolecular aggregates and not at any of the organizational levels below. This paper discusses the formation and successive self-reproduction of membraneous compartments in a polar environment in 2D using a lattice gas based simulation technique, the Lattice Molecular Automaton. This method describes realistic physico-chemical interactions as well as chemical reactivity between molecular units via discrete force fields propagated on the lattice. We investigate the formation dynamics of micelles, i.e., organized amphiphilic polymers in polar environment, as well as the kinetics of a concomittant micelle self-reproduction based on the formation of catalytic interfaces closely following in vitro experimental results: Micelle self-reproduction is a complex phenomenon based on concerted dynamics of the individual polymers within the many particle aggregate. All observables, i.e., micelle formation and autocatalytic micelle self-reproduction, are solely based on the properties of the individual chemical objects (amphiphilic polymers in polar environment), and are therefore emergent phenomena generated by the implicitly defined system dynamics. We introduce the formal concept of the emergence of novel functions in dynamical hierarchies and finally discuss these issues within the context of self-reproducing dynamical hierarchies.

We extend the Microscopic Representation approach to the quantitative study of religious and folk stories: A story encrypting symbolically the creation is deconstructed into its simplest conceptual elements and their relationships. We single out a particular kind of relationship which we call "diagonal (or transitive) link": given two relations between the couples of elements AB and respectively BC, the "diagonal link" is the (composite) relation AC. We find that the diagonal links are strongly and systematically correlated with the events in the story that are considered crucial by the experts. We further compare the number of diagonal links in the symbolic creation story with a folk tale, which ostensibly narrates the same overt succession of events (but without pretensions of encrypting additional meanings). We find that the density of diagonal links per word in the folk story is lower by a factor of two. We speculate that, as in other fields, the simple transitive operations acting on elementary objects are at the core of the emergence and recognition of macroscopic meaning and novelty in complex systems.

A few years ago Nagel and Schreckenberg introduced a model for traffic flow,¹ which, though quite simple, is able to reproduce the basic properties of traffic. Meanwhile many variations of the model have been developed, part of them concentrate on introducing an inhomogenous fleet of cars with different maximum velocities.

Here we also want to study the effect of introducing a certain fraction of vehicles with a lower maximum velocity ("trucks") to the Nagel–Schreckenberg-model. We give a detailed description of this effect and focus on the time development of the influence of trucks on traffic flow.

The distribution of site percolation thresholds for finite size lattices is a nonGaussian distribution. In this paper, we try to find out the real form of it.