Alternative Implementations of Expanding Algorithm for Multi-Commodity Spatial Price Equilibrium

This thesis presents an algorithm based on the expanding algorithm to solve spatial price equilibrium problems for three different models: perfect competition, monopoly, oligopoly. The expanding algorithm is used to solve the linear single commodity spatial price equilibrium problem for perfectly competitive markets. In this thesis, we consider the general multi-commodity spatial price equilibrium problems with all nonlinear functions, and variable shipping cost. We also show that more commodities in total are shipped, and there is more congestion, especially in oligopoly model

A fully relativistic lattice Boltzmann algorithm

Starting from the Maxwell-Juettner equilibrium distribution, we develop a relativistic lattice Boltzmann (LB) algorithm capable of handling ultrarelativistic systems with flat, but expanding, spacetimes. The algorithm is validated through simulations of quark-gluon plasma, yielding excellent agreement with hydrodynamic simulations. The present scheme opens the possibility of transferring the recognized computational advantages of lattice kinetic theory to the context of both weakly and ultra-relativistic systems.Comment: 12 pages, 8 figure

Monte Carlo study of the random-field Ising model

Using a cluster-flipping Monte Carlo algorithm combined with a generalization of the histogram reweighting scheme of Ferrenberg and Swendsen, we have studied the equilibrium properties of the thermal random-field Ising model on a cubic lattice in three dimensions. We have equilibrated systems of LxLxL spins, with values of L up to 32, and for these systems the cluster-flipping method appears to a large extent to overcome the slow equilibration seen in single-spin-flip methods. From the results of our simulations we have extracted values for the critical exponents and the critical temperature and randomness of the model by finite size scaling. For the exponents we find nu = 1.02 +/- 0.06, beta = 0.06 +/- 0.07, gamma = 1.9 +/- 0.2, and gammabar = 2.9 +/- 0.2.Comment: 12 pages, 6 figures, self-expanding uuencoded compressed PostScript fil

Estimating Relevant Portion of Stability Region using Lyapunov Approach and Sum of Squares

Traditional Lyapunov based transient stability assessment approaches focus on identifying the stability region (SR) of the equilibrium point under study. When trying to estimate this region using Lyapunov functions, the shape of the final estimate is often limited by the degree of the function chosen, a limitation that results in conservativeness in the estimate of the SR. More conservative the estimate is in a particular region of state space, smaller is the estimate of the critical clearing time for disturbances that drive the system towards that region. In order to reduce this conservativeness, we propose a methodology that uses the disturbance trajectory data to skew the shape of the final Lyapunov based SR estimate. We exploit the advances made in the theory of sum of squares decomposition to algorithmically estimate this region. The effectiveness of this technique is demonstrated on a power systems classical model.Comment: Under review as a conference paper at IEEE PESGM 201

An elementary way to rigorously estimate convergence to equilibrium and escape rates

We show an elementary method to have (finite time and asymptotic) computer assisted explicit upper bounds on convergence to equilibrium (decay of correlations) and escape rate for systems satisfying a Lasota Yorke inequality. The bounds are deduced by the ones of suitable approximations of the system's transfer operator. We also present some rigorous experiment showing the approach and some concrete result.Comment: 14 pages, 6 figure

Non equilibrium effects in fragmentation

We study, using molecular dynamics techniques, how boundary conditions affect the process of fragmentation of finite, highly excited, Lennard-Jones systems. We analyze the behavior of the caloric curves (CC), the associated thermal response functions (TRF) and cluster mass distributions for constrained and unconstrained hot drops. It is shown that the resulting CC's for the constrained case differ from the one in the unconstrained case, mainly in the presence of a ``vapor branch''. This branch is absent in the free expanding case even at high energies . This effect is traced to the role played by the collective expansion motion. On the other hand, we found that the recently proposed characteristic features of a first order phase transition taking place in a finite isolated system, i.e. abnormally large kinetic energy fluctuations and a negative branch in the TRF, are present for the constrained (dilute) as well the unconstrained case. The microscopic origin of this behavior is also analyzed.Comment: 21 pages, 11 figure

Smoothing Method for Approximate Extensive-Form Perfect Equilibrium

Nash equilibrium is a popular solution concept for solving imperfect-information games in practice. However, it has a major drawback: it does not preclude suboptimal play in branches of the game tree that are not reached in equilibrium. Equilibrium refinements can mend this issue, but have experienced little practical adoption. This is largely due to a lack of scalable algorithms. Sparse iterative methods, in particular first-order methods, are known to be among the most effective algorithms for computing Nash equilibria in large-scale two-player zero-sum extensive-form games. In this paper, we provide, to our knowledge, the first extension of these methods to equilibrium refinements. We develop a smoothing approach for behavioral perturbations of the convex polytope that encompasses the strategy spaces of players in an extensive-form game. This enables one to compute an approximate variant of extensive-form perfect equilibria. Experiments show that our smoothing approach leads to solutions with dramatically stronger strategies at information sets that are reached with low probability in approximate Nash equilibria, while retaining the overall convergence rate associated with fast algorithms for Nash equilibrium. This has benefits both in approximate equilibrium finding (such approximation is necessary in practice in large games) where some probabilities are low while possibly heading toward zero in the limit, and exact equilibrium computation where the low probabilities are actually zero.Comment: Published at IJCAI 1