401 research outputs found

    Universal statistical properties of poker tournaments

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    We present a simple model of Texas hold'em poker tournaments which retains the two main aspects of the game: i. the minimal bet grows exponentially with time; ii. players have a finite probability to bet all their money. The distribution of the fortunes of players not yet eliminated is found to be independent of time during most of the tournament, and reproduces accurately data obtained from Internet tournaments and world championship events. This model also makes the connection between poker and the persistence problem widely studied in physics, as well as some recent physical models of biological evolution, and extreme value statistics.Comment: Final longer version including data from Internet and WPT tournament

    Self-gravitating Brownian particles in two dimensions: the case of N=2 particles

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    We study the motion of N=2 overdamped Brownian particles in gravitational interaction in a space of dimension d=2. This is equivalent to the simplified motion of two biological entities interacting via chemotaxis when time delay and degradation of the chemical are ignored. This problem also bears some similarities with the stochastic motion of two point vortices in viscous hydrodynamics [Agullo & Verga, Phys. Rev. E, 63, 056304 (2001)]. We analytically obtain the density probability of finding the particles at a distance r from each other at time t. We also determine the probability that the particles have coalesced and formed a Dirac peak at time t (i.e. the probability that the reduced particle has reached r=0 at time t). Finally, we investigate the variance of the distribution and discuss the proper form of the virial theorem for this system. The reduced particle has a normal diffusion behaviour for small times with a gravity-modified diffusion coefficient =r_0^2+(4k_B/\xi\mu)(T-T_*)t, where k_BT_{*}=Gm_1m_2/2 is a critical temperature, and an anomalous diffusion for large times ~t^(1-T_*/T). As a by-product, our solution also describes the growth of the Dirac peak (condensate) that forms in the post-collapse regime of the Smoluchowski-Poisson system (or Keller-Segel model) for T<T_c=GMm/(4k_B). We find that the saturation of the mass of the condensate to the total mass is algebraic in an infinite domain and exponential in a bounded domain.Comment: Revised version (20/5/2010) accepted for publication in EPJ

    Finite mass self-similar blowing-up solutions of a chemotaxis system with non-linear diffusion

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    For a specific choice of the diffusion, the parabolic-elliptic Patlak-Keller-Segel system with non-linear diffusion (also referred to as the quasi-linear Smoluchowski-Poisson equation) exhibits an interesting threshold phenomenon: there is a critical mass Mc>0M_c>0 such that all the solutions with initial data of mass smaller or equal to McM_c exist globally while the solution blows up in finite time for a large class of initial data with mass greater than McM_c. Unlike in space dimension 2, finite mass self-similar blowing-up solutions are shown to exist in space dimension d?3d?3

    The spatial correlations in the velocities arising from a random distribution of point vortices

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    This paper is devoted to a statistical analysis of the velocity fluctuations arising from a random distribution of point vortices in two-dimensional turbulence. Exact results are derived for the correlations in the velocities occurring at two points separated by an arbitrary distance. We find that the spatial correlation function decays extremely slowly with the distance. We discuss the analogy with the statistics of the gravitational field in stellar systems.Comment: 37 pages in RevTeX format (no figure); submitted to Physics of Fluid

    Evolutionary dynamics of the most populated genotype on rugged fitness landscapes

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    We consider an asexual population evolving on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local optima. We track the most populated genotype as it changes when the population jumps from a fitness peak to a better one during the process of adaptation. This is done using the dynamics of the shell model which is a simplified version of the quasispecies model for infinite populations and standard Wright-Fisher dynamics for large finite populations. We show that the population fraction of a genotype obtained within the quasispecies model and the shell model match for fit genotypes and at short times, but the dynamics of the two models are identical for questions related to the most populated genotype. We calculate exactly several properties of the jumps in infinite populations some of which were obtained numerically in previous works. We also present our preliminary simulation results for finite populations. In particular, we measure the jump distribution in time and find that it decays as t2t^{-2} as in the quasispecies problem.Comment: Minor changes. To appear in Phys Rev

    Data-driven discovery of stochastic dynamical equations of collective motion

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    Coarse-grained descriptions of collective motion of flocking systems are often derived for the macroscopic or the thermodynamic limit. However, many real flocks are small sized (10 to 100 individuals), called the mesoscopic scales, where stochasticity arising from the finite flock sizes is important. Developing mesoscopic scale equations, typically in the form of stochastic differential equations, can be challenging even for the simplest of the collective motion models. Here, we take a novel data-driven equation learning approach to construct the stochastic mesoscopic descriptions of a simple self-propelled particle (SPP) model of collective motion. In our SPP model, a focal individual can interact with k randomly chosen neighbours within an interaction radius. We consider k = 1 (called stochastic pairwise interactions), k = 2 (stochastic ternary interactions), and k equalling all available neighbours within the interaction radius (equivalent to Vicsek-like local averaging). The data-driven mesoscopic equations reveal that the stochastic pairwise interaction model produces a novel form of collective motion driven by a multiplicative noise term (hence termed, noise-induced flocking). In contrast, for higher order interactions (k > 1), including Vicsek-like averaging interactions, yield collective motion driven primarily by the deterministic forces. We find that the relation between the parameters of the mesoscopic equations describing the dynamics and the population size are sensitive to the density and to the interaction radius, exhibiting deviations from mean-field theoretical expectations. We provide semi-analytic arguments potentially explaining these observed deviations. In summary, our study emphasizes the importance of mesoscopic descriptions of flocking systems and demonstrates the potential of the data-driven equation discovery methods for complex systems studies

    On War: The Dynamics of Vicious Civilizations

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    The dynamics of ``vicious'', continuously growing civilizations (domains), which engage in ``war'' whenever two domains meet, is investigated. In the war event, the smaller domain is annihilated, while the larger domain is reduced in size by a fraction \e of the casualties of the loser. Here \e quantifies the fairness of the war, with \e=1 corresponding to a fair war with equal casualties on both side, and \e=0 corresponding to a completely unfair war where the winner suffers no casualties. In the heterogeneous version of the model, evolution begins from a specified initial distribution of domains, while in the homogeneous system, there is a continuous and spatially uniform input of point domains, in addition to the growth and warfare. For the heterogeneous case, the rate equations are derived and solved, and comparisons with numerical simulations are made. An exact solution is also derived for the case of equal size domains in one dimension. The heterogeneous system is found to coarsen, with the typical cluster size growing linearly in time tt and the number density of domains decreases as 1/t1/t. For the homogeneous system, two different long-time behaviors arise as a function of \e. When 1/2<\e\leq 1 (relatively fair wars), a steady state arises which is characterized by egalitarian competition between domains of comparable size. In the limiting case of \e=1, rate equations which simultaneously account for the distribution of domains and that of the intervening gaps are derived and solved. The steady state is characterized by domains whose age is typically much larger than their size. When 0\leq\e<1/2 (unfair wars), a few ``superpowers'' ultimately dominate. Simulations indicate that this coarsening process is characterized by power-law temporal behavior, with non-universalComment: 43 pages, plain TeX, 12 figures included, gzipped and uuencode

    Exponents appearing in heterogeneous reaction-diffusion models in one dimension

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    We study the following 1D two-species reaction diffusion model : there is a small concentration of B-particles with diffusion constant DBD_B in an homogenous background of W-particles with diffusion constant DWD_W; two W-particles of the majority species either coagulate (W+WWW+W \longrightarrow W) or annihilate (W+WW+W \longrightarrow \emptyset) with the respective probabilities pc=(q2)/(q1) p_c=(q-2)/(q-1) and pa=1/(q1)p_a=1/(q-1); a B-particle and a W-particle annihilate (W+BW+B \longrightarrow \emptyset) with probability 1. The exponent θ(q,λ=DB/DW)\theta(q,\lambda=D_B/D_W) describing the asymptotic time decay of the minority B-species concentration can be viewed as a generalization of the exponent of persistent spins in the zero-temperature Glauber dynamics of the 1D qq-state Potts model starting from a random initial condition : the W-particles represent domain walls, and the exponent θ(q,λ)\theta(q,\lambda) characterizes the time decay of the probability that a diffusive "spectator" does not meet a domain wall up to time tt. We extend the methods introduced by Derrida, Hakim and Pasquier ({\em Phys. Rev. Lett.} {\bf 75} 751 (1995); Saclay preprint T96/013, to appear in {\em J. Stat. Phys.} (1996)) for the problem of persistent spins, to compute the exponent θ(q,λ)\theta(q,\lambda) in perturbation at first order in (q1)(q-1) for arbitrary λ\lambda and at first order in λ\lambda for arbitrary qq.Comment: 29 pages. The three figures are not included, but are available upon reques

    Topological correlations in soap froths

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    Correlation in two-dimensional soap froth is analysed with an effective potential for the first time. Cells with equal number of sides repel (with linear correlation) while cells with different number of sides attract (with NON-bilinear) for nearest neighbours, which cannot be explained by the maximum entropy argument. Also, the analysis indicates that froth is correlated up to the third shell neighbours at least, contradicting the conventional ideas that froth is not strongly correlated.Comment: 10 Pages LaTeX, 6 Postscript figure

    Analytical results for random walk persistence

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    In this paper, we present the detailed calculation of the persistence exponent θ\theta for a nearly-Markovian Gaussian process X(t)X(t), a problem initially introduced in [Phys. Rev. Lett. 77, 1420 (1996)], describing the probability that the walker never crosses the origin. New resummed perturbative and non-perturbative expressions for θ\theta are obtained, which suggest a connection with the result of the alternative independent interval approximation (IIA). The perturbation theory is extended to the calculation of θ\theta for non-Gaussian processes, by making a strong connection between the problem of persistence and the calculation of the energy eigenfunctions of a quantum mechanical problem. Finally, we give perturbative and non-perturbative expressions for the persistence exponent θ(X0)\theta(X_0), describing the probability that the process remains bigger than X0X_0\sqrt{}.Comment: 23 pages; accepted for publication to Phys. Rev. E (Dec. 98
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