santa fe institute complex systems summer school 2003

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Santa Fe Institute Complex Systems Summer School 2003

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Page 1: Santa Fe Institute Complex Systems Summer School 2003

Santa Fe InstituteComplex Systems Summer School

2003

Page 2: Santa Fe Institute Complex Systems Summer School 2003

Summer school activities

• Lectures on ‘foundation’ topics: nonlinear dynamics, information theory, statistical mechanics, computational mechanics, agent-based modelling, adaptive computation

• Lectures on specific application areas: RNA folding, economic game theory, emergent engineering

• Experimental laboratory

Page 3: Santa Fe Institute Complex Systems Summer School 2003

A Belmonte et al (2001) Physical Review Letters, 87, 114301

A. Belmonte et al (1997) Journal de Physique II 7, 1425-1468.  

Belousov-Zhabotinsky Reaction

Motion of a shaken hanging chain

Page 4: Santa Fe Institute Complex Systems Summer School 2003

Faraday experiment

Foam coarsening

Page 5: Santa Fe Institute Complex Systems Summer School 2003

Chaos you can play in:the Malkus Waterwheel

Aaron Clauset, Nicky Grigg, May Tan Lim, Erin Miller

Santa Fe Institute Complex Systems Summer School

June 2003

Page 6: Santa Fe Institute Complex Systems Summer School 2003

Lorenz equations

Page 7: Santa Fe Institute Complex Systems Summer School 2003

Periodic and strange attractors

Page 8: Santa Fe Institute Complex Systems Summer School 2003

Malkus waterwheel

Page 9: Santa Fe Institute Complex Systems Summer School 2003

Equations of Motion

Mass change in each cup:

Torque balance for wheel:

Angle change for each cup:

Page 10: Santa Fe Institute Complex Systems Summer School 2003

Simulated mass time series

Page 11: Santa Fe Institute Complex Systems Summer School 2003

Angular velocity

Lorenz equations time series

Waterwheel equations time series

Page 12: Santa Fe Institute Complex Systems Summer School 2003

Model-data comparison

Page 13: Santa Fe Institute Complex Systems Summer School 2003

Phase space reconstruction

• Delay coordinate embedding requires a delay time () and an embedding dimension (dE)

• Delay time from first minimum in average mutual information function

• Embedding dimension from false nearest neighbours analysis

Page 14: Santa Fe Institute Complex Systems Summer School 2003

Reconstructed waterwheel attractors(simulation data)

Reconstructed Lorenz attractors

Page 15: Santa Fe Institute Complex Systems Summer School 2003

Reconstructed attractors from model and measured time series

Page 16: Santa Fe Institute Complex Systems Summer School 2003

Acknowledgments

• Andrew Belmonte, Department of Mathematics, Pennsylvania State University

• Ray Goldstein, Physics Department, University of Arizona