Georgia Institute of Technology College of Sciences

The Kadomtsev-Petviashvili (KP) equation is a two-dimensional dispersivewave equation which was proposed to study the stability of one solitonsolution of the KdV equation under the influence of weak transversalperturbations. It is well know that some closed-form solutions can beobtained by function which have a Wronskian determinant form. It is ofinterest to study KP with an arbitrary initial condition and see whetherthe solution converges to any closed-form solution asymptotically. Toreveal the answer to this question both numerically and theoretically, weconsider different types of initial conditions, including one-linesoliton, V-shape wave and cross-shape wave, and investigate the behaviorof solutions asymptotically. We provides a detail description ofclassification on the results. The challenge of numerical approach comes from the unbounded domain andunvanished solutions in the infinity. In order to do numerical computationon the finite domain, boundary conditions need to be imposed carefully.Due to the non-periodic boundary conditions, the standard spectral methodwith Fourier methods involving trigonometric polynomials cannot be used.We proposed a new spectral method with a window technique which will makethe boundary condition periodic and allow the usage of the classicalapproach. We demonstrate the robustness and efficiency of our methodsthrough numerous simulations.

To come to grips with consciousness, I postulate that living entities in general, and human beings in particular, are mechanisms... marvelous mechanisms to be sure but not magical ones... just mechanisms. On this basis, I look to explain some of the paradoxes of consciousness such as Samuel Johnson's "All theory is against the freedom of the will; all experience is for it." I will explain concepts of self-awareness and free will from a mechanistic view. My explanations make use of computer science and suggest why these phenomena would exist even in a completely deterministic world. This is particularly striking for free will. The impressions of our senses, like the sense of the color blue, the sound of a tone, etc. are to be expected of a mechanism with enormously many inputs categorized into similarity classes of sight, sound, etc. Other phenomena such as the "bite" of pain are works in progress. I show the direction that my thinking takes and say something about what I've found and what I'm still looking for. Fortunately, the sciences are discovering a great deal about the brain, and their discoveries help enormously in guiding and verifying the results of this work.

Many models from a variety of areas involve the computation of an equilibrium or fixed point of some kind. Examples include Nash equilibria in games; price equilibria in markets; optimal strategies and the values of competitive games (stochastic and other games); stable configurations of neural networks; analysis of the evolution of various types of dynamic stochastic models. It is not known whether these problems can be solved in polynomial time. Despite their broad diversity, there are certain common computational principles that underlie different types of equilibria and connect many of these problems to each other. In this talk we will discuss some of these common principles and the corresponding complexity classes that capture them; the effect on the complexity of the underlying computational framework; and the relationship with other open questions in computation.

The talk is based on a 1992 paper by Yakov Sinai. He proves a localization property for random walks in the random potential known as Nechaev's model.