Gel Electrophoresis of DNA Knots in Weak and Strong Electric Fields

Gel electrophoresis allows to separate knotted DNA (nicked circular) of equal length according to the knot type. At low electric fields, complex knots being more compact, drift faster than simpler knots. Recent experiments have shown that the drift velocity dependence on the knot type is inverted when changing from low to high electric fields. We present a computer simulation on a lattice of a closed, knotted, charged DNA chain drifting in an external electric field in a topologically restricted medium. Using a simple Monte Carlo algorithm, the dependence of the electrophoretic migration of the DNA molecules on the type of knot and on the electric field intensity was investigated. The results are in qualitative agreement with electrophoretic experiments done under conditions of low and high electric fields: especially the inversion of the behavior from low to high electric field could be reproduced. The knot topology imposes on the problem the constrain of self-avoidance, which is the final cause of the observed behavior in strong electric field.Comment: 17 pages, 5 figure

The role of the Berry Phase in Dynamical Jahn-Teller Systems

The presence/absence of a Berry phase depends on the topology of the manifold of dynamical Jahn-Teller potential minima. We describe in detail the relation between these topological properties and the way the lowest two adiabatic potential surfaces get locally degenerate. We illustrate our arguments through spherical generalizations of the linear T x h and H x h cases, relevant for the physics of fullerene ions. Our analysis allows us to classify all the spherical Jahn-Teller systems with respect to the Berry phase. Its absence can, but does not necessarily, lead to a nondegenerate ground state.Comment: revtex 7 pages, 2 eps figures include

Statistical Analysis of Genealogical Trees for Polygamic Species

Repetitions within a given genealogical tree provides some information about the degree of consanguineity of a population. They can be analyzed with techniques usually employed in statistical physics when dealing with fixed point transformations. In particular we show that the tree features strongly depend on the fractions of males and females in the population, and also on the offspring probability distribution. We check different possibilities, some of them relevant to human groups, and compare them with simulations.Comment: 2 eps figs, Fig.2 changed to meet cond-mat size criteri

Levy-Nearest-Neighbors Bak-Sneppen Model

We study a random neighbor version of the Bak-Sneppen model, where "nearest neighbors" are chosen according to a probability distribution decaying as a power-law of the distance from the active site, P(x) \sim |x-x_{ac }|^{-\omega}. All the exponents characterizing the self-organized critical state of this model depend on the exponent \omega. As \omega tends to 1 we recover the usual random nearest neighbor version of the model. The pattern of results obtained for a range of values of \omega is also compatible with the results of simulations of the original BS model in high dimensions. Moreover, our results suggest a critical dimension d_c=6 for the Bak-Sneppen model, in contrast with previous claims.Comment: To appear on Phys. Rev. E, Rapid Communication

Critical exponents of the anisotropic Bak-Sneppen model

We analyze the behavior of spatially anisotropic Bak-Sneppen model. We demonstrate that a nontrivial relation between critical exponents tau and mu=d/D, recently derived for the isotropic Bak-Sneppen model, holds for its anisotropic version as well. For one-dimensional anisotropic Bak-Sneppen model we derive a novel exact equation for the distribution of avalanche spatial sizes, and extract the value gamma=2 for one of the critical exponents of the model. Other critical exponents are then determined from previously known exponent relations. Our results are in excellent agreement with Monte Carlo simulations of the model as well as with direct numerical integration of the new equation.Comment: 8 pages, three figures included with psfig, some rewriting, + extra figure and table of exponent

Uncovering the topology of configuration space networks

The configuration space network (CSN) of a dynamical system is an effective approach to represent the ensemble of configurations sampled during a simulation and their dynamic connectivity. To elucidate the connection between the CSN topology and the underlying free-energy landscape governing the system dynamics and thermodynamics, an analytical soluti on is provided to explain the heavy tail of the degree distribution, neighbor co nnectivity and clustering coefficient. This derivation allows to understand the universal CSN network topology observed in systems ranging from a simple quadratic well to the native state of the beta3s peptide and a 2D lattice heteropolymer. Moreover CSN are shown to fall in the general class of complex networks describe d by the fitness model.Comment: 6 figure

Finding instabilities in the community structure of complex networks

The problem of finding clusters in complex networks has been extensively studied by mathematicians, computer scientists and, more recently, by physicists. Many of the existing algorithms partition a network into clear clusters, without overlap. We here introduce a method to identify the nodes lying ``between clusters'' and that allows for a general measure of the stability of the clusters. This is done by adding noise over the weights of the edges of the network. Our method can in principle be applied with any clustering algorithm, provided that it works on weighted networks. We present several applications on real-world networks using the Markov Clustering Algorithm (MCL).Comment: 4 pages, 5 figure

The Anisotropic Bak-Sneppen model

The Bak-Sneppen model is shown to fall into a different universality class with the introduction of a preferred direction, mirroring the situation in spin systems. This is first demonstrated by numerical simulations and subsequently confirmed by analysis of the multitrait version of the model, which admits exact solutions in the extremes of zero and maximal anisotropy. For intermediate anisotropies, we show that the spatiotemporal evolution of the avalanche has a power law `tail' which passes through the system for any non-zero anisotropy but remains fixed for the isotropic case, thus explaining the crossover in behaviour. Finally, we identify the maximally anisotropic model which is more tractable and yet more generally applicable than the isotropic system