MATH 500: Probability  Credits: 3  − Description 

MATH 511: Analysis I  Credits: 3  − Description 
Content: An introduction to fundamental analytic concepts including: The complex number system, geometry and topology of the complex plane, analytic functions, conformal mappings, complex integration, and singularities. 
MATH 512: Analysis II  Credits: 3  − Description 
Content: Topics will include: Measure and integration theory on the real line as well as on a general measure space, Bounded linear functionals on L^p spaces. If time permits, Sobolev spaces and Fourier transforms will be introduced. Prerequisites: Students are expected to have the background of Math 411412 sequence or the equivalent. 
MATH 515: Numerical Analysis I  Credits: 3  − Description 
Content: Course will cover fundamental parts of
numerical linear algebra including matrix factorizations,
solution of linear systems and leastsquares problems,
the calculation of eigenvalues and eigenvectors, and
basic notions on
iterative methods for largescale matrix problems. Issues pertaining
to conditioning and numerical stability will be thoroughly
analyzed. We will also point
out and use links to other mathematical and computer science
disciplines such as mathematical modelling, computer
architectures and parallel computing. Particulars: Excellent background in linear algebra is assumed.
Some knowledge of computer architectures, programming
and elementary numerical analysis is
highly desirable. 
MATH 516: Numerical Analysis II  Credits: 3  − Description 
Content: This course covers fundamental concepts of numerical analysis and scientific computing. Material includes numerical methods for curve fitting (interpolation, splines, least squares), differentiation, integration, and differential equations.
It is assumed that students have a strong background in numerical linear algebra. Prerequisites: Math 515, undergraduate course work in multivariable calculus and ordinary differential equations. An undergraduate course in numerical analysis would help, but is not absolutely essential. 
MATH 517: Iterative Methods for Linear Systems  Credits: 3  − Description 
Prerequisites: Prerequisite MATH 516 
MATH 521: Algebra I  Credits: 3  − Description 
Content: Linear algebra, including canonical forms, infinitedimensional vector spaces, tensor products, and multilinear algebra. Group theory including group actions and representations. Particulars: Text: A.W. Knapp, "Basic algebra", Birkhauser, 2006. 
MATH 522: Algebra II  Credits: 3  − Description 
Content: Continuation of 521. Topics: Modules, especially modules over a principal ideal domain, fields, Galois theory, representation of finite groups, Commutative algebra. Prerequisites: Math 521. 
MATH 523: Commutative Algebra & Algebraic Geometry  Credits: 3  − Description 

MATH 524: Theory of Computing  Credits: 3  − Description 

MATH 528: Algebraic Number Theory  Credits: 3  − Description 

MATH 531: Graph Theory I  Credits: 3  − Description 

MATH 532: Graph Theory II  Credits: 3  − Description 

MATH 535: Combinatorics I  Credits: 3  − Description 

MATH 536: Combinatorics II  Credits: 3  − Description 
Content: This course is the second of the sequence of Math 535536 and as such will continue to develop the topics from the first semester. Specific topics will include finite geometries, Hadermard matrices, Latin Squares, an introduction to design theory, extremal set theory and an introduction to combinatorial coding theory. 
MATH 541: General Topology I  Credits: 3  − Description 
Content: An introduction to some of the fundamental concepts of topology required for basic courses in analysis. Some of these comcepts are: Baire category, topological spaces, completeness, compact and locally compact sets, connected and locally connected sets, characterizations of arcs, Jordan curves, and Peano continua, completeness, metric spaces, separability, countable bases, open and closed mappings, and homeomorphisms. Other selected topics if time permits from algebraic topology or continua theory. 
MATH 542: General Topology II  Credits: 3  − Description 
Content: The content of 542 may vary. Standard topics include Algebraic Topology (the fundamental group and covering spaces, homology and cohomology); Differential Topology (manifolds, transversality, intersection theory, integration on manifolds); and Geometric Topology (hyperbolic geometry knots and 3manifolds). Chosen in accordance with the interest of students and instructor. 
MATH 543: Algebraic Topology I  Credits: 3  − Description 
Content: Homotopy theory, the fundamental group, free products of groups with amalgamation, Van Kampen's Theorem, covering spaces, classification of surfaces, classifying spaces, higher homotopy groups 
MATH 544: Algebraic Topology II  Credits: 3  − Description 
Content: Singular, simplicial and cellular homology, long exact sequences in homology, MayerVietoris sequences, excision, Euler characteristic, degrees of maps, BorsukUlam theorem, Lefschetz fixed point theorem, cohomology, universal coefficient theorem, the cup product, Poincare duality 
MATH 545: Introduction to Differential Geometry I  Credits: 3  − Description 
Content: An introduction to Riemannian geometry. The main goal is an understanding of the nature and uses of curvature, which is the local geometric invariant that measures the departure from Euclidean geometry. No previous experience in differential geometry is assumed, and we will rely heavily on pictures of surfaces in 3space to illustrate key concepts. Particulars: Open to undergraduates with permission of the instructor. 
MATH 546: Intro. to Differential Geometry II  Credits: 3  − Description 
Content: An introduction to Riemannian geometry and global analysis. Topics to be covered: Manifolds, Riemannian metrics, Connections, Curvature; Geodesics, Convexity, Topics in Global Analysis. 
MATH 547: Differential Topology  Credits: 3  − Description 
Content: Smooth manifolds, tangent spaces and derivatives, Sard's theorem, inverse function theorem, transversality, intersection theory, fixedpoint theory, vector fields, Euler characteristic, the PoincareHopf theorem, exterior algebras, differential forms, integration, Stokes' theorem, de Rham cohomology. 
MATH 550: Functional Analysis  Credits: 3  − Description 
Content: An introduction to concepts and applications including: metric
and normed spaces, Hilbert
and Banach spaces, linear operators and functionals,
compactness in metric and normed spaces, Fredholm's solvability theory,
spectral theory,
calculus in metric and normed spaces, selected
applications. Prerequisites: Math 511, Math 512. 
MATH 555: Intro To Applied Analysis  Credits: 3  − Description 

MATH 556: Ordinary Differen Equations II  Credits: 3  − Description 

MATH 557: Partial Differential Equations I  Credits: 3  − Description 

MATH 558: Partial Differential Equations  Credits: 3  − Description 
Content: This course will introduce some of the basic techniques for studying and solving partial differential equations (PDE's) with special emphasis on applications. Included in the course are the following topics:
1. Basic concepts, sample problems, motivation
2. Maximum principles for elliptic and parabolic equations
3. Basic concepts of the theory of distributions
4. Method of fundamental solutions; Green's functions
5. Fourier transform
6. Variational methods, eigenvalues and eigenfunctions
7. Applications; Maxwell's equations, diffusion, geometric flows, image processing 
MATH 561: Matrix Analysis  Credits: 3  − Description 
Content: Main topics:
Eigenvalues and eigenvectors of matrices, invariant subspaces, Schur triangular form, diagonalizable matrices, minimal polynomial, characteristic polynomial, HamiltonCayley Theorem, localization of eigenvalues, Gerschgorin's Theorem. Unitary, Hermitian and skewHermitian matrices. Normal matrices and the Spectral Theorem. Orthogonalization. Householder matrices and the QR factorization.
MoorePenrose pseudoinverse. Applications to the solution of under and overdetermined systems of linear equations. Other generalized inverses. Applications to data fitting (leastsquares approximation).
The Singular Value Decomposition. Matrix norms: spectral norm and Frobenius norm. Solution to matrix nearness problems. Applications to signal processing and information retrieval. Jordan canonical form. An algorithmic proof. Powers of matrices. Matrix functions. Applications to systems of differential equations. Bilinear and quadratic forms. Hermitian forms. Congruence. Sylvester's Law of Inertia. Rayleigh's principle. CourantFischer Theorem. Positive definite and semidefinite matrices. Applications to statistics (covariance matrices) and numerical analysis (PDE's).
Additional topics:
Nonnegative matrices. The spectral radius. Positive matrices. Directed graphs. Nonnegative irreducible matrices. PerronFrobenius Theorem. Mmatrices. Applications to probability theory (Markov chains), economics (Leontiev's inputoutput model), and numerical analysis (iterative methods for linear systems). Structured matrices: circulant, Toeplitz, Hankel, Cauchy, Vandermonde, others. Block generalizations. Applications in signal processing, image processing, and numerical analysis (PDE's, interpolation). 
MATH 576R: Seminar in Topology  Credits: 1  3  − Description 

MATH 577R: Seminar in Combinatorics  Credits: 3  − Description 
Content: The seminar in combinatorics is a research seminar for students and faculty. It runs weekly, and features speakers from outside Emory who come to talk about topics of interest to the Emory faculty. 
MATH 577R: Seminar in Combinatorics  Credits: 3  − Description 
Content: The seminar in combinatorics is a research seminar for students and faculty. It runs weekly, and features speakers from outside Emory who come to talk about topics of interest to the Emory faculty. 
MATH 578R: Seminar in Algebra  Credits: 3  − Description 
Content: Research topics in algebra of current interest to faculty and students. 
MATH 578R: Seminar in Algebra  Credits: 3  − Description 
Content: Research topics in algebra of current interest to faculty and students. 
MATH 579R: Seminar in Analysis  Credits: 1  12  − Description 

MATH 579R: Seminar in Analysis  Credits: 3  − Description 
Content: Topics include: numerical methods for linear algebra, inverse problems and PDE's 
MATH 584: Algorithms  Credits: 3  − Description 
Content: This course is a graduate level introduction to the design and analysis of algorithms. Although we will review some undergraduate level material, we will instead emphasize reading and experimentation at a level appropriate for the initiation of research. This course will have both theoretical and practical content. As course highlights, students will be expected to implement and analyze the performance of a fundamental data structure, starting with a close reading of the original research paper. 
MATH 587G: Number Theory  Credits: 3  − Description 

MATH 590: Teaching Seminar  Credits: 3  − Description 
Content: This seminar will concentrate on effective teaching techniques in mathematics. Topics included will include:
General advice for new TA's. General advice for International TA's. Students will present several practice lectures over different levels of material. They will receive practice on quiz and test preparation. Syllabus information on courses most likely to be taught by new TA's will be supplied. General professional development information will also be included. 
MATH 593: Computability & Logic  Credits: 3  − Description 

MATH 597R: Directed Study  Credits: 1  9  − Description 

MATH 597R: Directed Study  Credits: 1  9  − Description 

MATH 599R: Research  Credits: 1  9  − Description 

MATH 599R: Master's Thesis Research  Credits: 1  9  − Description 

MATH 721: Struct Of Algebraic Systems I  Credits: 3  − Description 

MATH 730: Linear Algebra In Combinatoric  Credits: 3  − Description 

MATH 731: Ramsey Theory  Credits: 3  − Description 
Content: This course will continue the development of ramsey theory begun in Math 531532 and Math 535536. Included will be: Sets: Ramsey's theorem, the compactness principle. Progressions: Van der Waerden's Theorem, the HalesJewett Theorem, spaces  affine and vector, Roth's Theorem and Szemeredi's Theorem. Equations: Schur's Theorem, regular homogeneous equations and systems, Rado's Theorem, finite sums and unions, Folkman's Theorem. Numbers: exact ramsey numbers, asymptotics, Van der Waerden numbers. The symmetric hypergraph Theorem, Schur and Rado numbers, higher ramsey numbers. Bipartite ramsey theory, induced ramsey theory, restricted results, Euclidean and Graph ramsey theory. Topological Dynamics, Ultra filters, the infinite. Prerequisites: Math 531532 and Math 535536 or permission of the instructor. 
MATH 732: Extremal Graph Theory  Credits: 3  − Description 
Content: Continue the development of extremal in Graph Theory begun in Math 532. Included will be: Connectivity: structure of 2 and 3 connected graphs, minimally kconnected graphs. Matchings: fundamentals, the number of 1factors, ffactors, coverings. Cycles: Graphs with large girth and large min. degree, vertex disjoint cycles, edge disjoint cycles, cycles of specific lengths, circumference. Diameter: Graphs with large subgraphs of small diameter, factors of small diameter, ties to connectivity. Colorings: General colorings, sparse graphs of large chromatic no., perfect graphs. Turan type Extremal Theory. Prerequisites: Math 532 Graph Theory II or permission of the instructor. 
MATH 733: Probabilistic Methods  Credits: 3  − Description 
Content: This course will develope discrete probabilistic aspects of topics begun in Math 535536. Included will be: The probabilistic method of Erdos. Modifications: the deletion method. Refinements: the LovaszLocal Lemma and its applications. The secondmoment method. Large deviation inequalities and Derandomization. 
MATH 736: Random Algorithms  Credits: 3  − Description 

MATH 737: Random Graph Theory  Credits: 3  − Description 
Content: This course will introduce the fundamental topics in Random Graph Theory. Included will be: Basic Models: binomial, uniform. The method of moments: subgraph counts Thresholds for large subgraphs: connectedness, perfect matchings, hamiltonicity. Phase transitions. Advanced tools: martingales, Janson's inequality. Chromatic Number and other partition and extremal properties. 
MATH 741: Geometric Topology  Credits: 3  − Description 

MATH 748: Advanced Partial Differential Equations  Credits: 3  − Description 
Content: This course will discuss advanced topics in the modern theory of nonlinear partial differential equations and their applications. Included in the course are many of the following topics: * Basic concepts, sample problems in physics, biology, and geometry * Linear and quasilinear elliptic and parabolic equations; basic methods and results on solvability * Quasilinear geometric problems: mean curvature problem, Christoffel's problem, evolution by mean curvature, prescribing scalar curvature, Yamabe's problem * Convexity and elliptic and parabolic equations of MongeAmpere type, Aleksandrov's geometric methods, Calabi's problem and Chern's classes, Fully nonlinear problems * N. Krylov's and C. Evans's results on nonlinear problems * The reflector mapping problem, the Gauss curvature problem, the Weyl problem, the Minkowski problem * Variational problems associated with some nonlinear PDE's * MongeKantorovich optimal transportation theory and its connections with nonlinear PDE's Prerequisites: Mathematics 558 or permission of the instructor. 
MATH 755: Ordinary Differen Equations II  Credits: 3  − Description 

MATH 756: Part Differential Equations II  Credits: 3  − Description 

MATH 771: Numerical Optimization  Credits: 3  − Description 
Content: This course will provide students with an overview of stateoftheart numerical methods for solving unconstrained, largescale optimization problems. Algorithm development will be emphasized, including efficient and robust implementations. In addition, students will be exposed to stateoftheart software that can be used to solve optimization problems. Prerequisites: Mathematics 511512, 515516. 
MATH 772: Numerical Partial Differential Equations  Credits: 3  − Description 
Content: Partial Differential Equations are a formidable tool for describing realworld problems ranging from fluid dynamics to economical studies. Unfortunately, in many cases an explicit solution of these equations cannot be found. Numerical techniques are mandatory for finding an approximate solution. The choice of the most appropriate method is usually problemdependent. In this course we will consider different classes of differential problems and discuss possible methods of solution, their features in terms of accuracy, computational cost, implementation. Particular emphasis will be given to the Galerkin class of methods (Finite Elements, Spectral Methods), even if Finite Volume and Finite Differences methods will be considered as well. The course will be partially carried out in the Computer Lab, where theoretical properties of the different methods will be verified with Matlab and FreeFem codes. Prerequisites: Mathematics: 511512, 515516. 
MATH 786R: Topics in Topology  Credits: 1  4  − Description 
Content: In this course we will study discrete groups from a geometric perspective. (Discrete groups are groups which are defned by generators and relations, such as free groups, free abelian groups, braid groups, etc.) By treating groups as geometric objects, one can solve many algebraic problems which are much more difficult without the geometry. Introductory topics include: Free groups, group presentations, Cayley graphs and Cayley complexes, Dehn's problems, fundamental groups, hyperbolic geometry, EilenbergMacLane spaces and some algebraic topology. Advanced topics may include: Coxeter and Artin groups, BassSerre theory (of groups acting on trees and other spaces), CAT(0) geometry, CAT(0) groups, hyperbolic groups, coarse geometry (quasiisometries etc), ends of groups, boundaries of groups, Gromov's polynomial growth theorem. Particulars: TBA Prerequisites: TBA 
MATH 787R: Topics in Combinatorics: Hypergraphs  Credits: 3  − Description 

MATH 787R: Topics in Combinatorics  Credits: 3  − Description 

MATH 788R: Topics in Algebra: Algebraic Groups  Credits: 3  − Description 
Content: The course will consist of the following distinct components :
1. Structure theory of reductive groups over algebraically closed fields : Overview of objects and notions such as tori, solvable groups, Lie algebras, Jordan decomposition. Conjugacy of Borel subgroups and maximal tori, root systems, Bruhat decomposition, representation and classification of semi simple groups in terms of root systems.
2. Galois cohomology of linear algebraic groups : Classical groups and algebras with involutions, Steinberg's theorem, dimension two fields and Serre's conjecture, cohomological invariants and a discussion on some open questions in this area. 
MATH 788R: Topics in Algebra: Representation Theory  Credits: 3  − Description 

MATH 789R: Topics in Analysis: Bayesian Inverse Problems and Uncertainty Qualification  Credits: 3  − Description 
Content: This special topics course introduces basic concepts as well as more recent advances in Bayesian methods for solving inverse problems. Motivated by realworld applications, we will contrast the frequentists and the Bayesian approach to inverse problems and emphasize the role of regularization/priors. Also, we will explore sampling techniques used for uncertainty quantification. Particulars: Literature:
Somersalo and Calvetti, An Introduction to Bayesian Scientific Computing, Springer, 2007
Kaipio and Somersalo, Statistical and Computational Inverse Problems, Springer 2004 
MATH 797R: Directed Study  Credits: 1  9  − Description 

MATH 799R: Dissertation Research  Credits: 1  9  − Description 
