We're sorry but this page doesn't work properly without JavaScript enabled. Please enable it to continue.
Feedback

Using Modern Dynamical Systems Theory to Interpret Your Data

Formal Metadata

Title
Using Modern Dynamical Systems Theory to Interpret Your Data
Title of Series
Number of Parts
21
Author
License
CC Attribution - NonCommercial - NoDerivatives 4.0 International:
You are free to use, copy, distribute and transmit the work or content in unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
Identifiers
Publisher
Release Date
Language

Content Metadata

Subject Area
Genre
Abstract
Ending up with a lot of dynamics data ( be it trajectories or wavefunctions) is a common situation we face whenever we are working with real (and sometimes, evenmodel) systems. How can we make sense of these massive data in terms of concepts we understand? In the past two decades I and my team have been using modern dynamical systems theory to uncover simple structures buried under massive trajectory calculations. The power of this tool is due to a very simple property: It allows you to focus on collective behavior of families of trajectories rather than individual ones, thereby helping you to isolate generic behavior. I will give you specific examples from our research which illustrate the use of this powerful tool.