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Simple%20Models%20of%20Complex%20%20%20Chaotic%20Systems

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AAPT Topical Conference on Computational Physics in Upper Level Courses. At Davidson College (NC) ... http://sprott.physics.wisc.edu/ lectures/davidson.ppt (this talk) ... – PowerPoint PPT presentation

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Title: Simple%20Models%20of%20Complex%20%20%20Chaotic%20Systems


1
Simple Models of Complex Chaotic Systems
  • J. C. Sprott
  • Department of Physics
  • University of Wisconsin - Madison
  • Presented at the
  • AAPT Topical Conference on Computational Physics
    in Upper Level Courses
  • At Davidson College (NC)
  • On July 28, 2007

2
Collaborators
  • David Albers, Univ California - Davis
  • Konstantinos Chlouverakis, Univ Athens (Greece)

3
Background
  • Grew out of an multi-disciplinary chaos course
    that I taught 3 times
  • Demands computation
  • Strongly motivates students
  • Used now for physics undergraduate research
    projects (20 over the past 10 years)

4
Minimal Chaotic Systems
  • 1-D map (quadratic map)
  • Dissipative map (Hénon)
  • Autonomous ODE (jerk equation)
  • Driven ODE (Ueda oscillator)
  • Delay differential equation (DDE)
  • Partial diff eqn (Kuramoto-Sivashinsky)

5
What is a complex system?
  • Complex ? complicated
  • Not real and imaginary parts
  • Not very well defined
  • Contains many interacting parts
  • Interactions are nonlinear
  • Contains feedback loops ( and -)
  • Cause and effect intermingled
  • Driven out of equilibrium
  • Evolves in time (not static)
  • Usually chaotic (perhaps weakly)
  • Can self-organize and adapt

6
A Physicists Neuron
N
inputs
tanh x
x
7
A General Model (artificial neural network)
N neurons
Universal approximator, N ? 8
8
Route to Chaos at Large N (101)
Quasi-periodic route to chaos
9
Strange Attractors
10
Sparse Circulant Network (N101)
11
(No Transcript)
12
Labyrinth Chaos
dx1/dt sin x2 dx2/dt sin x3 dx3/dt sin x1
x1
x3
x2
13
Hyperlabyrinth Chaos (N101)
14
(No Transcript)
15
Minimal High-D Chaotic L-V Model
dxi /dt xi(1 xi 2 xi xi1)
16
Lotka-Volterra Model (N101)
17
(No Transcript)
18
Delay Differential Equation
19
(No Transcript)
20
Partial Differential Equation
21
(No Transcript)
22
Summary of High-N Dynamics
  • Chaos is common for highly-connected networks
  • Sparse, circulant networks can also be chaotic
    (but the parameters must be carefully tuned)
  • Quasiperiodic route to chaos is usual
  • Symmetry-breaking, self-organization, pattern
    formation, and spatio-temporal chaos occur
  • Maximum attractor dimension is of order N/2
  • Attractor is sensitive to parameter
    perturbations, but dynamics are not

23
Shameless Plug
Chaos and Time-Series Analysis J. C.
SprottOxford University Press (2003) ISBN
0-19-850839-5
An introductory text for advanced
undergraduate and beginning graduate students in
all fields of science and engineering
24
References
  • http//sprott.physics.wisc.edu/
    lectures/davidson.ppt (this talk)
  • http//sprott.physics.wisc.edu/chaostsa/ (my
    chaos textbook)
  • sprott_at_physics.wisc.edu (contact me)
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