Lectures related to Complex Systems: Critical Phenomena

Explores linear programming optimization with constraints, Dijkstra's algorithm, and LP formulations for finding feasible solutions.

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Explores the Curie-Weiss model, spin glasses, and optimization problems in statistical physics.

Introduces complexity classes, including P and NP, and explores examples of easy and hard problems.

Explores the Ford Fulkerson algorithm, Max-Flow Min-Cut theorem, Incidence matrix, and network optimization complexity.

Delves into oracles, certificates, and the NP complexity class, raising the fundamental P versus NP question.