PHY 28
Natural Computation and Self-Organization:

The Physics of Information Processing in Complex Systems

Announcements:

PHY 256 is now a two-quarter sequence: PHY 256 in Winter 2010 and PHY 250 in Spring 2010; eventually becoming PHY 256AB. This allows for a more in-depth (and gradually paced) exploration of the concepts and techniques. Winter will focus on the physics of information—nonlinear dynamical systems, measurement theory, and information theory. Spring will cover physics of computation and computational mechanics.

For the first time, the course will include a numerical lab using our new CMPy open source environment for computational mechanics.

The information linked in below is being incrementally updated, as the Winter quarter approaches. And so, information at some links will be out of date.

Instructor: Professor Jim Crutchfield (Physics and CSC)
Assistant: John Mahoney (Physics and CSC).
WWW: cse.ucdavis.edu/~chaos/courses/ncaso/

Catalog number: Physics 256 (CRN 56841)
Level: Graduate
Units: 3
Times: TuTh 0210-0330 PM
Location: 185 Physics Building
Office hours and locations:
Crutchfield: W 0300-0400 PM, 1109 Mathematical Sciences Building
Mahoney: Times TBA, 1227 Mathematical Sciences Building
Poster: [jpg]

The course explores how nature's structure reflects how nature computes. It introduces intrinsic unpredictability (deterministic chaos) and the emergence of structure (self-organization) in natural complex systems. Using statistical mechanics, information theory, and computation theory, the course will develop a systematic framework for analyzing processes in terms of their causal architecture. This is determined by answering three questions: (i) How much historical information does a process store? (ii) How is that information stored? And (iii) how is the stored information used to produce future behavior? The answers to these questions tell one how a system intrinsically computes.

The course will develop tools to describe and quantify randomness and structure. It will show how they are necessarily complementary and how they are intimately related to concepts from the theory of computation. A number of example complex systems—taken from physics, chemistry, and biology—will be used to illustrate the phenomena and methods. The course will also take time to reflect on the intellectual history of these topics, which is quite rich and touches on many basic questions in fundamental physics and the sciences and technology generally. New topics this year include complex materials and computation in quantum systems. The course will bring students to the research frontier in nonlinear physics and complex systems.

Outline: (Course Syllabus [PDF] [HTML] )
PHY 256 (Winter 2010):

PHY 250 (Spring 2010):

Complex systems to be analyzed:

Audience: Graduate students in physics, mathematics, computer science, engineering, mathematical biology, and theoretical neuroscience. Others also welcome.

Reference materials:

  1. Books:
  2. Computational Mechanics Reader.
  3. Lecture notes.
  4. Software tools.
  5. Supplemental Readings for historical background, projects, programming, and amusement.

Course Work:

  1. Assigned Readings.
  2. Weekly Problem Sets.
  3. Final Exam (PHY 256 Winter 2010): Take home.
  4. Research Project (PHY 250 Spring 2010):
    • Project report:
      • Orally presented as final exam.
      • Written report: Due electronically 10 June.
    • Project Presentation Schedule.
    • Report Organization.
    • Example projects can be found here.