GFF Convergence and Six Vertex Models: Phase Transitions

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (28)

Page 1 of 3

Covers percolation theory, absorbed polymers, giant molecules, phase transition, scaling assumptions, and universal behavior in percolation models.

FK-Percolation and the Six-Vertex Model: Critical Phenomena

Covers the transition from the six-vertex model to FK-percolation, focusing on critical phenomena and phase transitions in two-dimensional systems.

Epidemics and Bootstrap Percolation in Square Lattice

Explores epidemics spread models and Bootstrap Percolation in square lattice networks, focusing on the Kolmogorov equation and probability generating functions.

Phase Transitions: Percolation in 2D Networks

Explores phase transitions through percolation in 2D networks.

Law of Large Numbers: Strong Convergence

Explores the strong convergence of random variables and the normal distribution approximation in probability and statistics.

Dependence and Correlation

Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.

Variance and Covariance: Properties and Examples

Explores variance, covariance, and practical applications in statistics and probability.

Conditional Density and Expectation

Explores conditional density, expectations, and independence of random variables with practical examples.

Elements of Statistics: Probability and Random Variables

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Percolation: Bond Percolation

Covers bond percolation on a square lattice, discussing percolation phases, critical threshold, mean cluster size, and critical point scenarios.