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LECTURES

Chapter 15: Complexity

Lecture
40: April 30

Forest
fire automaton model

Neural
networks and associative memory

Lecture
39: April 27

Two-dimensional
sandpile automaton

Lecture
38: April 25

The
Gutenberg-Richter Law

One-dimensional
sandpile automaton

Lecture
37: April 20

Lattice
Gas Model of Fluid Flow

Lecture
36: April 18

2-D
Cellular Automata (continued)

Lecture
35: April 16

Conway's
Game of Life

Lecture
34: April 13

One-dimensional
Boolean cellular automaton

Chapter 18: Quantum Systems

Lecture
33: April 11

Path
Integral Quantum Monte Carlo (continued)

Lecture
32: April 9

Path
Integral Quantum Monte Carlo

Lecture
31: April 6

Quantum
Systems - Catching up!

Lecture
30: April 4

Random
Walk Quantum Monte Carlo

Lecture
29: April 2

Quantum
Systems - Catching up!

Parabolic
partial differential equations.

Lecture
28: March 30

Quantum
Systems - Catching up!

Lecture
27: March 28

Time-Dependendent
Schrödinger Equation

Lecture
26: March 26

Bound
state solutions by deterministic integration

Chapter 17: Monte Carlo Simulation of the Canonical Ensemble

Lecture
25: March 23

Finite
Size Scaling - Catching up!

Lecture
24: March 21

Autocorrelations
- Catching up!

Lecture
23: March 19

Ising
phase transition and finite size scaling

Lecture
22: March 16

Autocorrelations
in the 2-D Ising model simulation

Lecture
21: March 12

Counting
States: Energy versus Entropy

Lecture
20: March 2

The
Two-Dimensional Ising Model

Chapter 16: The Microcanonical Ensemble

Lecture
19: February 28

One
dimensional Ising Model: theory and simulation

Lecture
18: February 26

The
One-Dimensional Ising Model

Lecture
17: February 23

The
Microcanonical Ensemble

Chapter 12: Random Walks

Lecture
16: February 21

Application
of the pivot algorithm

Lecture
15: February 19

Kink-jump
polymer dynamics

Lecture
14: February 16

Symmetries
of the square lattice

The
double cul-de-sac polymer

Lecture
13: February 14

Reptation
method for enriching a polymer sample

Lecture
12: February 12

More
on Self-Avoiding Random Walks

Applications
of Random Walks to Polymers

DNA
is a Polymer

Lecture
11: February 9

Modified
Random Walks: A Lattice Gas

Self-Avoiding
Random Walk in 2 Dimensions

Lecture
10: February 7

A
random walk in two dimensions

More
on graphics programming

Chapter 11: Numerical Integration and Monte Carlo Methods

Lecture
9: February 5

Importance
Sampling

Metropolis
Monte Carlo Algorithm

Lecture
8: February 2

Generating
the Gaussian distribution

Overview
of Java graphics programming

Lecture
7: January 31

Monte
Carlo Quadrature and Error Analysis

Lecture
6: January 29

Quadrature
and Integration

Programming
the Rectangular Approximation

Multidimensional
Quadrature

Chapter 7: Random Processes

Lecture
5: January 26

Random
Walks

2-D
Random Walk - Java Graphics

Lecture
4: January 24

Binomial,
Poisson, and Gaussian Distributions

Relationship
between Poisson and Gaussian distributions

Lecture
3: January 22

Darts
and the Poisson distribution

Another
Poisson applet

Lecture
2: January 19

Random
sequences

Pseudo-random
number generators

How
good are they?

Lecture
1: January 17

Random
processes

Tossing
a coin

Random
number generators

Questions or comments: [email-masked]