Complex Variables II

MATH-GA.2460-001

Courant Institute of Mathematical Sciences,
New York University
Spring Semester, 2023
Lecture: in person Tuesdays, 5:10-7:00PM, room 512

Instructor: Jonathan Goodman, web page, email: goodman@cims.nyu.edu
phone: 212-998-3326, office: 529 Warren Weaver Hall
office hours: 1 pm to 3 pm Mondays or by appointment
(email for a time)

Course description

The second half of a two semester Masters level class on Complex Analysis. We will take material from the textbook of Marsden and Hoffman starting at Chapter 5. This includes conformal mapping and series and product expansions. Afterwards, there will be topics as time permits, hopefully including parts of Fourier analyis that use complex variable theory and some stuff on elliptic integrals and genus 1 Riemann surfaces (tori). Aside from the specific material, a goal is to gain facility in matheamtical analysis and to be exposed to ideas that are developed in active parts of mathematics including topology, number theory and partial differential equations.

Prerequisites:

A first course in Complex variables equivalent to our Complex Variables I.

Books:
Assignments, exams, grading:

The final grade will be based on weekly homework assignments and an in-class written final exam.

Communication:

Please use the Brightspace site for content and homework communications. This way everyone sees and benefits from questions and answers, and there can be class discussion. related comm. Email the instructor for issues that do not involve others such as scheduling appointments, homework extensions, advice, etc.

Academic integrity:

Students are encouraged to explore and collaborate widely to understand the material. This includes looking at print and online sources and interacting with experts and each other. Students may receive some help with assignments, but each student must create (write up, code, run) solutions individually. Students may not share ("borrow" or lend) assignment solutions -- all writing must be done individually. Students may not plagairize solutions from other sources such as books or web sites. Assignments may not be crowd-sourced on any web platform. Do not post homework exercises. Violation of these policies may result in grade lowering or more serious penalties, depending on severity.