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Massachusetts Institute of Technology

Projection Theory

Massachusetts Institute of Technology via MIT OpenCourseWare

Overview

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The class studies projection theory, starting from the first questions and building up to recent developments. Projection theory studies how a set *X* behaves under different orthogonal projections. Questions of this type aren't usually emphasized in the graduate analysis curriculum, but they come up in many areas of math, including harmonic analysis, analytic number theory, additive combinatorics, and homogeneous dynamics. We will survey several applications of projection theory. For each topic, we will introduce and motivate the topic and see how it connects with projection theory. We will prove something about each topic but not necessarily the strongest results.

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

Prof. Lawrence D Guth

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