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Dietrich Stauffer

Publications and source records attributed to Dietrich Stauffer.

At least 55 records · Page 3Linked to original sources
arXiv2005

Diffusion in scale-free networks with annealed disorder

The scale-free (SF) networks that have been studied so far contained quenched disorder generated by random dilution which does not vary with the time. In practice, if a SF network is to represent, for example, the worldwide web, then the links between its various nodes may temporarily be lost, and re-established again later on. This gives rise to SF networks with annealed disorder. Even if the disorder is quenched, it may be more realistic to generate it by a dynamical process that is happening in the network. In this paper, we study diffusion in SF networks with annealed disorder generated by various scenarios, as well as in SF networks with quenched disorder which, however, is generated by the diffusion process itself. Several quantities of the diffusion process are computed, including the mean number of distinct sites visited, the mean number of returns to the origin, and the mean number of connected nodes that are accessible to the random walkers at any given time. The results including, (1) greatly reduced growth with the time of the mean number of distinct sites visited; (2) blocking of the random walkers; (3) the existence of a phase diagram that separates the region in which diffusion is possible from one in which diffusion is impossible, and (4) a transition in the structure of the networks at which the mean number of distinct sites visited vanishes, indicate completely different behavior for the computed quantities than those in SF networks with quenched disorder generated by simple random dilution.

cond-mat.dis-nn↗
arXiv2005

Discrete Simulation of the Dynamics of Opinions about Extremism

We propose a discrete model for how opinion about a given phenomenon, about which various groups of a population have different degrees of enthusiasm, such as fanaticism and extreme social and political positions, including terrorism, may spread. The model, in a certain limit, is the discrete analogue of a deterministic continuum model suggested by others. We carry out extensive computer simulation of the model by utilizing it on lattices with infinite- or short-range interactions, and on (directed) Barabasi-Albert scale-free networks. Several interesting features of the model are demonstrated, and comparison is made with the continuum model.

physics.soc-ph↗
arXiv2005

Simulation of geographical trends in Chowdhury ecosystem model

A computer simulation based on individual births and deaths gives a biodiversity increasing from cold to warm climates, in agreement with reality. Complexity of foodwebs increases with time and at a higher rate at low latitudes, and there is a higher rate of species creation at low latitudes. Keeping many niches empty makes the results correspond more closely to natural gradients.

q-bio.PE↗
arXiv2005

Evolutionary ecology in-silico: Does mathematical modelling help in understanding the "generic" trends?

Motivated by the results of recent laboratory experiments (Yoshida et al. Nature, 424, 303-306 (2003)) as well as many earlier field observations that evolutionary changes can take place in ecosystems over relatively short ecological time scales, several ``unified'' mathematical models of evolutionary ecology have been developed over the last few years with the aim of describing the statistical properties of data related to the evolution of ecosystems. Moreover, because of the availability of sufficiently fast computers, it has become possible to carry out detailed computer simulations of these models. For the sake of completeness and to put these recent developments in the proper perspective, we begin with a brief summary of some older models of ecological phenomena and evolutionary processes. However, the main aim of this article is to review critically these ``unified'' models, particularly those published in the physics literature, in simple language that makes the new theories accessible to wider audience.

q-bio.PE↗
arXiv2005

Sociophysics Simulations IV: Hierarchies of Bonabeau et al

The model of Bonabeau et al explains social hierarchies as random: People keep a memory of recent fights, and winners have a higher probability to win again. The question of phase transition and the generalization from square lattices to networks is reviewed here.

physics.soc-ph↗
arXiv2005

Sociophysics Simulations II: Opinion Dynamics

Individuals have opinions but can change them under the influence of others. The recent models of Sznajd (missionaries), of Deffuant et al. (negotiators), and of Krause and Hegselmann (opportunists) are reviewed here, while the voter and Ising models, Galam's majority rule and the Axelrod multicultural model were dealt with by other lecturers at this 8th Granada Seminar.

physics.soc-ph↗
arXiv2005

Microscopic and Macroscopic Simulation of Competition between Languages

The similarity of the evolution of human languages (or alphabets, bird songs, >...) to biological evolution of species is utilized to study with up to $10^9$ people the rise and fall of languages either by macroscopic differential equations similar to biological Lotka-Volterra equation, or by microscopic Monte Carlo simulations of bit-strings incorporating the birth, maturity, and death of every individual. For our bit-string model, depending on parameters either one language comprises the majority of speakers (dominance), or the population splits into many languages having in order of magnitude the same number of speakers (fragmentation); in the latter case the size distribution is log-normal, with upward deviations for small sizes, just as in reality for human languages. On a lattice two different dominating languages can coexist in neighbouring regions, without being favoured or disfavoured by different status. We deal with modifications and competition for existing languages, not with the evolution or learning of one language.

physics.soc-ph↗
arXiv2005

Sociophysics Simulations I: Language Competition

Using a bit-string model similar to biological simulations, the competition between different languages is simulated both without and with spatial structure. We compare our agent-based work with differential equations and the competing bit-string model of Kosmidis et al.

physics.soc-ph↗
arXiv2005

Computer Simulations of Opinions

We review the opinion dynamics in the computer models of Deffuant et al. (D), of Krause and Hegselmann (KH), and of Sznajd (S). All these models allow for consensus (one final opinion), polarization (two final opinions), and fragmentation (more than two final opinions), depending on how tolerant people are to different opinions. We then simulate the reactions of people to ex treme events, in that we modify the opinion of an individual and investigate how the dynamics of a consensus model diffuses this perturbation among the other members of a community. It often happens that the original shock induced by the extreme event influences the opinion of a big part of the society.

cond-mat.dis-nn↗
arXiv2005

Are Barabasi-Albert networks self-averaging?

Yes and no. The size of the largest neighbourhood in a Barabasi-Albert scale-free entwork has string fluctuations of the order of the average value. The number of sites having exactly ten neighbours increases linearly in the network size while its relative fluctuations decrease towards zero if the number of sites in the network increases from 1000 to ten million.

cond-mat.dis-nn↗
arXiv2004

Monte Carlo simulation of the rise and the fall of languages

Similar to biological evolution and speciation we define a language through a string of 8 or 16 bits. The parent gives its language to its children, apart from a random mutation from zero to one or from one to zero; initially all bits are zero. The Verhulst deaths are taken as proportional to the total number of people, while in addition languages spoken by many people are preferred over small languages. For a fixed population size, a sharp phase transition is observed: For low mutation rates, one language contains nearly all people; for high mutation rates, no language dominates and the size distribution of languages is roughly log-normal as for present human languages. A simple scaling law is valid.

cond-mat.dis-nn↗
arXiv2004

Number of spanning clusters at the high-dimensional percolation thresholds

A scaling theory is used to derive the dependence of the average number of spanning clusters at threshold on the lattice size L. This number should become independent of L for dimensions d<6, and vary as log L at d=6. The predictions for d>6 depend on the boundary conditions, and the results there may vary between L^{d-6} and L^0. While simulations in six dimensions are consistent with this prediction (after including corrections of order loglog L), in five dimensions the average number of spanning clusters still increases as log L even up to L = 201. However, the histogram P(k) of the spanning cluster multiplicity does scale as a function of kX(L), with X(L)=1+const/L, indicating that for sufficiently large L the average will approach a finite value: a fit of the 5D multiplicity data with a constant plus a simple linear correction to scaling reproduces the data very well. Numerical simulations for d>6 and for d=4 are also presented.

cond-mat.stat-mech↗
arXiv2004

Altruism and Antagonistic Pleiotropy in Penna Ageing Model

The Penna ageing model is based on mutation accumulation theory. We show that it also allows for self-organization of antagonistic pleiotropy which helps at young age at the expense of old age. This can be interpreted as emergence of altruism.

q-bio.PE↗
arXiv2004

Phase diagram in Bonabeau social hierarchy model with individually different abilities

The 1995 model of Bonabeau et al is generalized by giving each individual a different ability to win or lose a fight. We also introduce different groups such that the losers of fights between different groups are eliminated. The overall phase diagram for the first-order transition between egalitarian and hierarchical societies does not change much by these generalizations.

cond-mat.dis-nn↗
arXiv2004

Evolving eco-system: a network of networks

Ecology and evolution are inseparable. Motivated by some recent experiments, we have developed models of evolutionary ecology from the perspective of dynamic networks. In these models, in addition to the intra-node dynamics, which corresponds to an individual-based population dynamics of species, the entire network itself changes slowly with time to capture evolutionary processes. After a brief summary of our recent published works on these network models of eco-systems, we extend the most recent version of the model incorporating predators that wander into neighbouring spatial patches for food.

q-bio.PE↗
arXiv2004

Evolutionary ecology in-silico:evolving foodwebs, migrating population and speciation

We have generalized our ``unified'' model of evolutionary ecology by taking into account the possible movements of the organisms from one ``patch'' to another within the same eco-system. We model the spatial extension of the eco-system (i.e., the geography) by a square lattice where each site corresponds to a distinct ``patch''. A self-organizing hierarchical food web describes the prey-predator relations in the eco-system. The same species at different patches have identical food habits but differ from each other in their reproductive characteristic features. By carrying out computer simulations up to $10^9$ time steps, we found that, depending on the values of the set of parameters, the distribution of the lifetimes of the species can be either exponential or a combination of power laws. Some of the other features of our ``unified'' model turn out to be robust against migration of the organisms.

q-bio.PE↗