Statistical Chaos — a new barrier in the prediction/simulation of physical systems

Abstract: It is well known that for systems exhibiting “sensitivity to initial conditions”, it is practically impossible to predict individual trajectories beyond a very limited time horizon. To overcome this difficulty, a statistical approach was developed -- while the computed trajectories are not individually meaningful, when regarded as an ensemble, their average represents a statistical distribution that can be used to make meaningful probabilistic predictions about the system. This statistical paradigm is ubiquitous in modern applications. In this talk we present a new obstacle in applying the statistical approach. We show that the statistical behavior of a parametrized system may exhibit “sensitivity to parameters”, and that this may lead to non computability of the limiting, meaningful, statistical distribution. We will explain all this in the simplest nonlinear class of systems: quadratic maps of the interval [0,1]. This is joint work with M. Yampolsky.

logic

Audience: researchers in the topic

Computability theory and applications

Series comments: Description: Computability theory, logic

The goal of this endeavor is to run a seminar on the platform Zoom on a weekly basis, perhaps with alternating time slots each of which covers at least three out of four of Europe, North America, Asia, and New Zealand/Australia. While the meetings are always scheduled for Tuesdays, the timezone varies, so please refer to the calendar on the website for details about individual seminars.