Overview
Syllabus
Lecture 01: Introduction to Projection Theory
Lecture 02: Fundamental Methods of Projection Theory
Lecture 03: Projection Theory in Euclidean Space
Lecture 04: The Fourier Method in Euclidean Space
Lecture 05: The Large Sieve
Lecture 06: Projections and Smoothing
Lecture 07: Applications of the Large Sieve to Number Theory
Lecture 08: The Szemeredi-Trotter Theorem
Lecture 09: Reflections on the Szemeredi-Trotter Theorem
Lecture 10: Sum-Product Theory
Lecture 11: Contagious Structure in Projection Theory
Lecture 12: The Bourgain-Katz-Tao Projection Theorem
Lecture 13: The Balog-Szemeredi-Gowers Theorem
Lecture 14: The Bourgain Projection Theorem Part 1 (over the Real Numbers)
Lecture 15: The Bourgain Projection Theorem, Part 2
Lecture 16: The Bourgain Projection Theorem, Part 3
Lecture 17: Random Walks on Finite Groups, Part 1
Lecture 18: Random Walks on Finite Groups, Part 2
Lecture 19: Random Walks on Finite Groups, Part 3
Lecture 20: Homogeneous Dynamics, Part 1
Lecture 21: Homogeneous Dynamics, Part 2
Lecture 22: Sharp Projection Theorems, Part 1: Introduction and Beck's Theorem.
Lecture 23: Sharp Projection Theorems, Part 2: AD Regular Case
Lecture 24: Sharp Projection Theorems, Part 3: Combining Different Scales
Taught by
MIT OpenCourseWare