Maths 730

Measure theory and integration (Semester 1) 2020

This course presents the modern theory of integration, which has been developed over the last 2500 years by mathematicians such as Archimedes, Newton, Leibniz, Riemann and Lebesgue. This elegant theory gives powerful theorems for the interchange of integrals and limits and allows very general functions to be integrated. It is the foundation for the theory of probability, and is widely used in other areas such as physics. It is an essential tool in analysis. Part of the recommended preparation for Maths 731.

Recommended preparation: You will need to be proficient in the basics of real analysis, as taught in Maths 332 and Maths 333.

Textbook: The Elements of Integration and Lebesgue Measure , R. G. Bartle 1995.

Resources:

Lecturer: Shayne Waldron.

Class times: The class meets on Monday 9 am (in Clock Tower East, Room G10), Thursday 12 pm (in Clock Tower, Room 018), Friday 9 am (in Clock Tower East, Room G10).

Exam: To be announced.

Assignments: There will be about ten assignments. The assignments will be handed out on Friday, and collected the following Friday. Marked assignments will be handed back with model solutions.

Assessment: The final grade will be calculated: 30% assignments and 70% final exam, or 100% on the final exam, whichever is the maximum.

Syllabus: We will follow the text book quite closely. Below is a rough summary of the what will be covered in the first 16 lectures.

  1. Introduction, set theory: cardinality and de Morgan's laws
  2. The extended reals, and infinite limits of sequences
  3. The liminf and limsup of a sequence of extended reals, and their properties.
  4. sigma algebras, and the example of the Borel sigma algebra
  5. measurable functions
  6. sums, products, limits, limsups, etc of measurable functions
  7. measures, and a proof there is no measure on the power set of the reals which has the basic properties we would desire
  8. the measure of expanding and contracting sequences of sets, and sets of measure zero, including the Cantor set
  9. Simple function, the approximation of a nonnegative measurable function by an increasing sequence of simple functions
  10. The integral of a simple nonnegative function
  11. Integration of nonnegative measurable functions, and the monotone convergence theorem
  12. Fatou's Lemma, integration against a nonnegative measurable function gives a measure.
  13. The integral of a nonnegative function is zero iff it is zero a.e. Definition of the integral of f in terms of the integral of its positive and negative parts and space L of integrable functions.
  14. Dominated convergence theorem, and the continuous version.
  15. Norms, and L_p spaces (everything but Minkowskii's inequality and completeness proved).
  16. L_p is a Banach space.
  17. Brief comments about different modes of convergence.
  18. Brief comments about signed measures and charges, the Jordan decomposition and the Radon-Nikodym theorem (we may return to this if time permits).

    Midsemster break. We now aim to construct the Lebesgue and product measures.

  19. Overview: outer measures and the Caratheodory magic construction. Show that a measure on an algebra gives a natural outer measure.
  20. Show that a measure of length is define on the algebra generated by the half open intervals.
  21. Caratheodory magic.
  22. The construction of Lebesgue measure (or Lebesgue-Stieljes measure)
  23. More on Lebesgue measure: translation invariance, inner and outer regularity. Haar measure.
  24. Convex functions and Jensen's inequality (3 lectures).
  25. Equality in Holder's inequality.
  26. The represensation of the continuous linear functionals on L_p(mu), 1