Random geometry and the Kardar-Parisi-Zhang universality class

We consider a model of a quenched disordered geometry in which a random metric is defined on R-2, which is flat on average and presents short-range correlations. We focus on the statistical properties of balls and geodesics, i.e., circles and straight lines. We show numerically that the roughness of a ball of radius R scales as R-x, with a fluctuation exponent x similar or equal to 1/3, while the lateral spread of the minimizing geodesic between two points at a distance L grows as L-zeta, with wandering exponent value zeta similar or equal to 2/3. Results on related first-passage percolation problems lead us to postulate that the statistics of balls in these random metrics belong to the Kardar-Parisi-Zhang universality class of surface kinetic roughening, with. and. relating to critical exponents characterizing a corresponding interface growth process. Moreover, we check that the one-point and two-point correlators converge to the behavior expected for the Airy-2 process characterized by the Tracy-Widom (TW) probability distribution function of the largest eigenvalue of large random matrices in the Gaussian unitary ensemble (GUE). Nevertheless extreme-value statistics of ball coordinates are given by the TW distribution associated with random matrices in the Gaussian orthogonal ensemble. Furthermore, we also find TW-GUE statistics with good accuracy in arrival times.We want to acknowledge very useful discussions with K Takeuchi and S Ferreira. This work has been supported by the Spanish government (MINECO) through grant FIS2012-38866-C05-01. JR-L also acknowledges MINECO grants FIS2012-33642, TOQATA and ERC grant QUAGATUA. TLʼs research and travel was supported in part by NSF PIRE grant OISE-07-30136

Geodesics of Random Riemannian Metrics

We analyze the disordered Riemannian geometry resulting from random perturbations of the Euclidean metric. We focus on geodesics, the paths traced out by a particle traveling in this quenched random environment. By taking the point of the view of the particle, we show that the law of its observed environment is absolutely continuous with respect to the law of the random metric, and we provide an explicit form for its Radon-Nikodym derivative. We use this result to prove a "local Markov property" along an unbounded geodesic, demonstrating that it eventually encounters any type of geometric phenomenon. We also develop in this paper some general results on conditional Gaussian measures. Our Main Theorem states that a geodesic chosen with random initial conditions (chosen independently of the metric) is almost surely not minimizing. To demonstrate this, we show that a minimizing geodesic is guaranteed to eventually pass over a certain "bump surface," which locally has constant positive curvature. By using Jacobi fields, we show that this is sufficient to destabilize the minimizing property.Comment: 55 pages. Supplementary material at arXiv:1206.494

Group Incentives and Rational Voting

Our model describes competition between groups driven by the choices of self-interested voters within groups. Within a Poisson voting environment, parties observe aggregate support from groups and can allocate prizes or punishments to them. In a tournament style analysis, the model characterizes how contingent allocation of prizes based on relative levels of support affects equilibrium voting behavior. In addition to standard notions of pivotality, voters influence the distribution of prizes across groups. Such prize pivotality supports positive voter turnout even in non-competitive electoral settings. The analysis shows that competition for a prize awarded to the most supportive group is only stable when two groups actively support a party. However, competition among groups to avoid punishment is stable in environments with any number of groups. We conclude by examining implications for endogenous group formation and how politicians structure the allocation of rewards and punishments.Comment: 34 pages, 1 figur

Geodesics of Random Riemannian Metrics

We introduce Riemannian First-Passage Percolation (Riemannian FPP) as a new model of random differential geometry, by considering a random, smooth Riemannian metric on R^d . We are motivated in our study by the random geometry of first-passage percolation (FPP), a lattice model which was developed to model fluid flow through porous media. By adapting techniques from standard FPP, we prove a shape theorem for our model, which says that large balls under this metric converge to a deterministic shape under rescaling. As a consequence, we show that smooth random Riemannian metrics are geodesically complete with probability one.In differential geometry, geodesics are curves which locally minimize length. They need not do so globally: consider great circles on a sphere. For lattice models of FPP, there are many open questions related to minimizing geodesics; similarly, it is interesting from a geometric perspective when geodesics are globally minimizing. In the present study, we show that for any fixed starting direction v, the geodesic starting from the origin in the direction v is not minimizing with probability one. This is a new result which uses the infinitesimal structure of the continuum, and for which there is no equivalent in discrete lattice models of FPP

The Mathematics of Evolution: The Price Equation, Natural Selection, and Environmental Change

We extend George Price's evolutionary framework to the measure-theoretic and quantum cases, decomposing all processes into selective and environmental components. We further quantify selection and environmental change using entropy functionals: selective entropy is non-positive, representing biological negentropy, and environmental entropy is non-negative, representing physical entropy. We prove four Laws of Natural Selection, showing that selection consistently acts in a manner to increase selection, but which can be disrupted by environmental change.Comment: 64 pages, appendix 11 page