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Riemann Surfaces and Complex Analysis (MAST90056)

Graduate courseworkPoints: 12.5On Campus (Parkville)

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Year of offer2019
Subject levelGraduate coursework
Subject codeMAST90056
Semester 2
FeesSubject EFTSL, Level, Discipline & Census Date

Riemann surfaces arise from complex analysis. They are central in mathematics, appearing in seemingly diverse areas such as differential and algebraic geometry, number theory, integrable systems, statistical mechanics and string theory.

The first part of the subject studies complex analysis. It assumes students have completed a first course in complex analysis so begins with a quick review of analytic functions and Cauchy's theorem, emphasising topological aspects such as the argument principle and Rouche's theorem.

Topics also include: Schwarz's lemma; limits of analytic functions, normal families, Riemann mapping theorem; multiple-valued functions, differential equations and Riemann surfaces. The second part of the subject studies Riemann surfaces and natural objects on them such as holomorphic differentials and quadratic differentials.

Topics may also include: divisors, Riemann-Roch theorem; the moduli space of Riemann surfaces, Teichmueller space; integrable systems.

Intended learning outcomes

After completing this subject, students will gain an understanding of:

  • topological aspects of complex analytic functions;
  • Riemann mapping theorem and its proof;
  • Riemann surfaces;
  • holomorphic differentials and line integrals on Riemann surfaces;
  • the relevance of this course to further studies in this and related areas.

Generic skills

In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. These include:

  • problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies;
  • analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
  • collaborative skills: the ability to work in a team;
  • time-management skills: the ability to meet regular deadlines while balancing competing commitments.

Last updated: 3 April 2019