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At least 73 records · Page 4Linked to original sources
arXiv2007

The Sznajd dynamics on a directed clustered network

The Sznajd model is investigated in the directed Erdos--Renyi network with the clusterization coefficient enhanced to 0.3 by the method of Holme and Kim (Phys. Rev. E65 (2002) 026107). Within additional triangles, all six links are present. In this network, some nodes preserve the minority opinion. The time tau of getting equilibrium is found to follow the log-normal distribution and it increases linearly with the system size. Its dependence on the initial opinion distribution is different from the analytical results for fully connected networks.

physics.soc-ph↗
arXiv2007

Least Squares Importance Sampling for Libor Market Models

A recently introduced Importance Sampling strategy based on a least squares optimization is applied to the Monte Carlo simulation of Libor Market Models. Such Least Squares Importance Sampling (LSIS) allows the automatic optimization of the sampling distribution within a trial class by means of a quick presimulation algorithm of straightforward implementation. With several numerical examples we show that LSIS can be extremely effective in reducing the variance of Monte Carlo estimators often resulting, especially when combined with stratified sampling, in computational speed-ups of orders of magnitude.

q-fin.PR↗
arXiv2007

Empirics versus RMT in financial cross-correlations

In order to pursue the issue of the relation between the financial cross-correlations and the conventional Random Matrix Theory we analyse several characteristics of the stock market correlation matrices like the distribution of eigenvalues, the cross-correlations among signs of the returns, the volatility cross-correlations, and the multifractal characteristics of the principal values. The results indicate that the stock market dynamics is not simply decomposable into 'market', 'sectors', and the Wishart random bulk. This clearly is seen when the time series used to construct the correlation matrices are sufficiently long and thus the measurement noise suppressed. Instead, a hierarchically convoluted and highly nonlinear organization of the market emerges and indicates that the relevant information about the whole market is encoded already in its constituents.

q-fin.ST↗
arXiv2007

Proceedings of the first Congress on North-South collaboration in Physics research

The first Congress on North-South collaboration in Physics research was held in Oujda Morocco, between April 9th and 13th, 2007. The congress was based on talks giving an overview of relevant subjects both from experiments and theory in all fields of physics. They focused on projects which could bring fruitful collaborations between Europe and under developed countries. The congress was meant to bring experience and skills to these countries in research and teaching at the doctoral level.

physics.soc-ph↗
arXiv2009

Optimized network clustering by jumping sub-optimal dendrograms

We propose a method to improve community division techniques in networks that are based on agglomeration by introducing dendrogram jumping. The method is based on iterations of sub-optimal dendrograms instead of optimization of each agglomeration step. We find the algorithm to exhibit excellent scaling behavior of its computational complexity. In its present form the algorithm scales as $\mathcal{O} (N^{2})$, but by using more efficient data structures it is possible to achieve a scaling of $\mathcal{O} (N \log^{2} N)$. We compare our results with other methods such as the greedy algorithm and the extremal optimization method. We find modularity values larger than the greedy algorithm and values comparable to the extremal optimization method.

physics.soc-ph↗
arXiv2007

Finite size effects and symmetry breaking in the evolution of networks of competing Boolean nodes

The effects of the finite size of the network on the evolutionary dynamics of a Boolean network are analyzed. In the model considered, Boolean networks evolve via a competition between nodes that punishes those in the majority. It is found that finite size networks evolve in a fundamentally different way than infinitely large networks do. The symmetry of the evolutionary dynamics of infinitely large networks that selects for canalizing Boolean functions is broken in the evolutionary dynamics of finite size networks. In finite size networks there is an additional selection for input inverting Boolean functions that output a value opposite to the majority of input values. These results are revealed through an empirical study of the model that calculates the frequency of occurrence of the different possible Boolean functions. Classes of functions are found to occur with the same frequency. Those classes depend on the symmetry of the evolutionary dynamics and correspond to orbits of the relevant symmetry group. The empirical results match analytic results, determined by utilizing Polya's theorem, for the number of orbits expected in both finite size and infinitely large networks. The reason for the symmetry breaking in the evolutionary dynamics is found to be due to the need for nodes in finite size networks to behave differently in order to cooperate so that the system collectively performs as well as possible. The results suggest that both finite size effects and symmetry are important for understanding the evolution of real-world complex networks, including genetic regulatory networks.

cond-mat.stat-mech↗
arXiv2008

Equilibria of culture contact derived from ingroup and outgroup attitudes

Modern societies feature an increasing contact between cultures, yet we have a poor understanding of what the outcomes might be. Here we consider a mathematical model of contact between social groups, grounded in social psychology and analyzed using tools from statistical physics. We use the model to study how a culture might be affected by immigration. We find that in some cases residents' culture is relatively unchanged, but in other cases residents may adopt the opinions and beliefs of immigrants. The decisive factors are each group's cultural legacy and its attitudes towards in- and out-groups. The model can also predict how social policies may influence the outcome of culture contact.

physics.soc-ph↗
arXiv2007

Features of Traffic Congestion caused by bad Weather Conditions or Accident

Spatiotemporal features and physics of vehicular traffic congestion occurring due to heavy freeway bottlenecks caused by bad weather conditions or accidents are found based on simulations in the framework of three-phase traffic theory. A model of a heavy bottleneck is presented. Under a continuous non-limited increase in bottleneck strength, i.e., when the average flow rate within a congested pattern allowed by the heavy bottleneck decreases continuously up to zero, the evolution of the traffic phases in congested traffic, synchronized flow and wide moving jams, is studied.

physics.soc-ph↗
arXiv2007

Co-occurrence Network of Reuters News

Networks describe various complex natural systems including social systems. We investigate the social network of co-occurrence in Reuters-21578 corpus, which consists of news articles that appeared in the Reuters newswire in 1987. People are represented as vertices and two persons are connected if they co-occur in the same article. The network has small-world features with power-law degree distribution. The network is disconnected and the component size distribution has power law characteristics. Community detection on a degree-reduced network provides meaningful communities. An edge-reduced network, which contains only the strong ties has a star topology. "Importance" of persons are investigated. The network is the situation in 1987. After 20 years, a better judgment on the importance of the people can be done. A number of ranking algorithms, including Citation count, PageRank, are used to assign ranks to vertices. The ranks given by the algorithms are compared against how well a person is represented in Wikipedia. We find up to medium level Spearman's rank correlations. A noteworthy finding is that PageRank consistently performed worse than the other algorithms. We analyze this further and find reasons.

physics.soc-ph↗
arXiv2007

An Economic Model of Coupled Exponential Maps

In this work, an ensemble of economic interacting agents is considered. The agents are arranged in a linear array where only local couplings are allowed. The deterministic dynamics of each agent is given by a map. This map is expressed by two factors. The first one is a linear term that models the expansion of the agent's economy and that is controlled by the {\it growth capacity parameter}. The second one is an inhibition exponential term that is regulated by the {\it local environmental pressure}. Depending on the parameter setting, the system can display Pareto or Boltzmann-Gibbs behavior in the asymptotic dynamical regime. The regions of parameter space where the system exhibits one of these two statistical behaviors are delimited. Other properties of the system, such as the mean wealth, the standard deviation and the Gini coefficient, are also calculated.

q-fin.GN↗
arXiv2007

The value of information in financial markets: An agent-based simulation

We present results on simulations of a stock market with heterogeneous, cumulative information setup. We find a non-monotonic behaviour of traders' returns as a function of their information level. Particularly, the average informed agents underperform random traders; only the most informed agents are able to beat the market. We also study the effect of a strategy updating mechanism, when traders have the possibility of using other pieces of information than the fundamental value. These results corroborate the latter ones: it is only for the most informed player that it is rewarding to stay fundamentalist. The simulations reproduce some stylized facts of tick-by-tick stock-exchange data and globally show informational efficiency.

q-fin.TR↗
arXiv2007

On Algebraic Graph Theory and the Dynamics of Innovation Networks

We investigate some of the properties and extensions of a dynamic innovation network model recently introduced in \citep{koenig07:_effic_stabil_dynam_innov_networ}. In the model, the set of efficient graphs ranges, depending on the cost for maintaining a link, from the complete graph to the (quasi-) star, varying within a well defined class of graphs. However, the interplay between dynamics on the nodes and topology of the network leads to equilibrium networks which are typically not efficient and are characterized, as observed in empirical studies of R&D networks, by sparseness, presence of clusters and heterogeneity of degree. In this paper, we analyze the relation between the growth rate of the knowledge stock of the agents from R&D collaborations and the properties of the adjacency matrix associated with the network of collaborations. By means of computer simulations we further investigate how the equilibrium network is affected by increasing the evaluation time $τ$ over which agents evaluate whether to maintain a link or not. We show that only if $τ$ is long enough, efficient networks can be obtained by the selfish link formation process of agents, otherwise the equilibrium network is inefficient. This work should assist in building a theoretical framework of R&D networks from which policies can be derived that aim at fostering efficient innovation networks.

physics.soc-ph↗
arXiv2007

Two Fractal Overlap Time Series: Earthquakes and Market Crashes

We find prominent similarities in the features of the time series for the (model earthquakes or) overlap of two Cantor sets when one set moves with uniform relative velocity over the other and time series of stock prices. An anticipation method for some of the crashes have been proposed here, based on these observations.

physics.soc-ph↗
arXiv2008

Opinion Dynamics with Hopfield Neural Networks

In Hopfield neural networks with up to 10^8 nodes we store two patterns through Hebb couplings. Then we start with a third random pattern which is supposed to evolve into one of the two stored patterns, simulating the cognitive process of associative memory leading to one of two possible opinions. With probability p each neuron independently, instead of following the Hopfield rule, takes over the corresponding value of another network, thus simulating how different people can convince each other. A consensus is achieved for high p.

physics.soc-ph↗
arXiv2010

Funnelling related phase transitions in networks

Funnelling effect, in the context of searching on networks, precisely indicates that the search takes place through a few specific nodes. We define the funnelling capacity $f$ of a node as the fraction of successful dynamic paths through it with a fixed target. We claim that there is a funnelling effect if the distribution $D(f)$ of the fraction of nodes with funnelling capacity $f$ shows a power law behaviour. We find that a transition from a search with funnelling effect to that without any such effect can exist and is driven by the parameters defining the network.

cond-mat.dis-nn↗
arXiv2008

Neighborhood Chance and Neighborhood Change

WITHDRAWAL NOTICE This paper has been withdrawn by the authors as required by the American Journal of Sociology, which has accepted the paper for publication. AJS will not publish papers if the preprint remains posted on arXiv.

nlin.AO↗
arXiv2008

Towards the understanding of human dynamics

Quantitative understanding of human behaviors provides elementary comprehension of the complexity of many human-initiated systems. A basic assumption embedded in the previous analyses on human dynamics is that its temporal statistics are uniform and stationary, which can be properly described by a Poisson process. Accordingly, the interevent time distribution should have an exponential tail. However, recently, this assumption is challenged by the extensive evidence, ranging from communication to entertainment and work patterns, that the human dynamics obeys non-Poisson statistics with heavy-tailed interevent time distribution. This review article summarizes the recent empirical explorations on human activity pattern, as well as the corresponding theoretical models for both task-driven and interest-driven systems. Finally, we outline some future open questions in the studies of the statistical mechanics of human dynamics.

physics.soc-ph↗