Reviews material presented in MATH 1106 lectures, provides problem-solving techniques and tips as well as prelim review. Provides further instruction for students who need reinforcement. Not a substitute for attending MATH 1106 lectures or discussions.

Academic Career: UG Instructor: Brendan Caseria (bjc297)Full details for MATH 1006 : Academic Support for MATH 1106

Reviews material presented in MATH 1110 lectures, provides problem-solving techniques and tips as well as prelim review. Provides further instruction for students who need reinforcement. Not a substitute for attending MATH 1110 lectures.

Academic Career: UG Instructor: Brendan Caseria (bjc297)Full details for MATH 1011 : Academic Support for MATH 1110

Reviews material presented in MATH 1120 lectures, provides problem-solving techniques and tips as well as prelim review. Provides further instruction for students who need reinforcement. Not a substitute for attending MATH 1120 lectures or discussions.

Academic Career: UG Instructor: Mark Jauquet (maj29)Full details for MATH 1012 : Academic Support for MATH 1120

Reviews material presented in MATH 2210 lectures, provides problem-solving techniques and tips as well as prelim review. Provides further instruction for students who need reinforcement. Not a substitute for attending MATH 2210 lectures or discussions.

Academic Career: UG Instructor: Mark Jauquet (maj29)Full details for MATH 1021 : Academic Support for MATH 2210

The goal of this course is to give students a strong basis in some quantitative skills needed in the life and social sciences. There will be an emphasis on modeling, using fundamental concepts from calculus developed in the course, including: derivatives, integrals, and introductory differential equations. Examples from the life sciences are used throughout the course. To give a concrete example, we will study predator-prey populations. We will write down mathematical models that describe the evolution of these populations, analyze both quantitative and qualitative properties to make predictions about the future of these populations, and discuss the assumptions and limitations of the models. Note that while we will cover the topics of derivatives and integrals, this course has a different, much more applied, focus from courses such as MATH 1110 - Calculus I or a typical high school calculus course.

Distribution: (MQR-AS)Academic Career: UG Instructor: Steve Bennoun (sjb366)

Full details for MATH 1106 : Modeling with Calculus for the Life Sciences

Topics include functions and graphs, limits and continuity, differentiation and integration of algebraic, trigonometric, inverse trig, logarithmic, and exponential functions; applications of differentiation, including graphing, max-min problems, tangent line approximation, implicit differentiation, and applications to the sciences; the mean value theorem; and antiderivatives, definite and indefinite integrals, the fundamental theorem of calculus, substitution in integration, the area under a curve. Graphing calculators are used, and their pitfalls are discussed, as applicable to the above topics.

Distribution: (MQR-AS)Academic Career: UG Instructor: Itamar Oliveira (is355)

Full details for MATH 1110 : Calculus I

Focuses on integration: applications, including volumes and arc length; techniques of integration, approximate integration with error estimates, improper integrals, differential equations (separation of variables, initial conditions, systems, some applications). Also covers infinite sequences and series: definition and tests for convergence, power series, Taylor series with remainder, and parametric equations.

Distribution: (MQR-AS)Academic Career: UG Instructor: Robert Connelly (rc46)

Full details for MATH 1120 : Calculus II

We apply mathematical reasoning to problems arising in the social sciences. We discuss game theory and its applications to questions of governing and the analysis of political conflicts. The problem of finding fair election procedures to choose among three or more alternatives is analyzed.

Distribution: (MQR-AS)Academic Career: UG Instructor: Birgit Speh (bes12)

Full details for MATH 1340 : Strategy, Cooperation, and Conflict

Introductory statistics course discussing techniques for analyzing data occurring in the real world and the mathematical and philosophical justification for these techniques. Topics include population and sample distributions, central limit theorem, statistical theories of point estimation, confidence intervals, testing hypotheses, the linear model, and the least squares estimator. The course concludes with a discussion of tests and estimates for regression and analysis of variance (if time permits). The computer is used to demonstrate some aspects of the theory, such as sampling distributions and the Central Limit Theorem. In the lab portion of the course, students learn and use computer-based methods for implementing the statistical methodology presented in the lectures.

Distribution: (MQR-AS)Academic Career: UG Instructor: Michael Nussbaum (mn66)

Full details for MATH 1710 : Statistical Theory and Application in the Real World

Full details for MATH 1890 : FWS: Writing in Mathematics

Essentially a second course in calculus. Topics include techniques of integration, finding areas and volumes by integration, exponential growth, partial fractions, infinite sequences and series, tests of convergence, and power series.

Distribution: (MQR-AS)Academic Career: UG Instructor: Qi Hou (qh55)

Full details for MATH 1910 : Calculus for Engineers

Introduction to multivariable calculus. Topics include partial derivatives, double and triple integrals, line and surface integrals, vector fields, Green's theorem, Stokes' theorem, and the divergence theorem.

Distribution: (MQR-AS)Academic Career: UG Instructor: Marie B.Langlois (mb2636)

Full details for MATH 1920 : Multivariable Calculus for Engineers

Topics include vectors and vector-valued functions; multivariable and vector calculus including multiple and line integrals; first- and second-order differential equations with applications; systems of differential equations; and elementary partial differential equations. Optional topics may include Green's theorem, Stokes' theorem, and the divergence theorem.

Distribution: (MQR-AS)Academic Career: UG Instructor: James Quigley (jdq27)

Full details for MATH 2130 : Calculus III

Topics include vector algebra, linear transformations, matrices, determinants, orthogonality, eigenvalues, and eigenvectors. Applications are made to linear differential or difference equations. The lectures introduce students to formal proofs. Students are required to produce some proofs in their homework and on exams.

Distribution: (MQR-AS)Academic Career: UG Instructor: Anil Nerode (an17)

Full details for MATH 2210 : Linear Algebra

Differential and integral calculus of functions in several variables, line and surface integrals as well as the theorems of Green, Stokes, and Gauss.

Distribution: (MQR-AS)Academic Career: UG Instructor: Andy Borum (adb328)

Full details for MATH 2220 : Multivariable Calculus

Topics include vector fields; line integrals; differential forms and exterior derivative; work, flux, and density forms; integration of forms over parametrized domains; and Green's, Stokes', and divergence theorems.

Distribution: (MQR-AS)Academic Career: UG Instructor: John Hubbard (jhh8)

Full details for MATH 2240 : Theoretical Linear Algebra and Calculus

A mathematical study of the formal languages of standard first-order propositional and predicate logic, including their syntax, semantics, and deductive systems. The basic apparatus of model theory will be presented. Various formal results will be established, most importantly soundness and completeness.

Distribution: (MQR-AS)Academic Career: UG Instructor: Harold Hodes (hth3)

Full details for MATH 2810 : Deductive Logic

Introduction to ordinary and partial differential equations. Topics include: first-order equations (separable, linear, homogeneous, exact); mathematical modeling (e.g., population growth, terminal velocity); qualitative methods (slope fields, phase plots, equilibria, and stability); numerical methods; second-order equations (method of undetermined coefficients, application to oscillations and resonance, boundary-value problems and eigenvalues); and Fourier series. A substantial part of this course involves partial differential equations, such as the heat equation, the wave equation, and Laplace's equation. (This part must be present in any outside course being considered for transfer credit to Cornell as a substitute for MATH 2930.)

Distribution: (MQR-AS)Academic Career: UG Instructor: Mahdi Esmaily Moghadam (me399)

Full details for MATH 2930 : Differential Equations for Engineers

Linear algebra and its applications. Topics include matrices, determinants, vector spaces, eigenvalues and eigenvectors, orthogonality and inner product spaces; applications include brief introductions to difference equations, Markov chains, and systems of linear ordinary differential equations. May include computer use in solving problems.

Distribution: (MQR-AS)Academic Career: UG Instructor: Katya Scheinberg (ks2375)

Full details for MATH 2940 : Linear Algebra for Engineers

In mathematics, the methodology of proof provides a central tool for confirming the validity of mathematical assertions, functioning much as the experimental method does in the physical sciences. In this course, students learn various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and in set theory and combinatorics, and then moving to applications and illustrations of these via topics in one or more of the three main pillars of mathematics: algebra, analysis, and geometry. Since cogent communication of mathematical ideas is important in the presentation of proofs, the course emphasizes clear, concise exposition.

Distribution: (MQR-AS)Academic Career: UG Instructor: Brian Hwang (bwh59)

Full details for MATH 3040 : Prove It!

Provides a transition from calculus to real analysis. Topics include rigorous treatment of fundamental concepts in calculus: including limits and convergence of sequences and series, compact sets; continuity, uniform continuity and differentiability of functions. Emphasis is placed upon understanding and constructing mathematical proofs.

Distribution: (MQR-AS)Academic Career: UG Instructor: Katherine Meyer (kjm298)

Full details for MATH 3110 : Introduction to Analysis

An introduction to structures of abstract algebra, including groups, rings, fields, factorization of polynomials and integers, congruences, and the structure of finite abelian groups. Additional topics include modules over Euclidean domain and Sylow theorems.

Distribution: (MQR-AS)Academic Career: UG Instructor: Karola Meszaros (km626)

Full details for MATH 3340 : Abstract Algebra

Introduction to the concepts and methods of abstract algebra and number theory that are of interest in applications. Covers the basic theory of groups, rings and fields and their applications to such areas as public-key cryptography, error-correcting codes, parallel computing, and experimental designs. Applications include the RSA cryptosystem and use of finite fields to construct error-correcting codes and Latin squares. Topics include elementary number theory, Euclidean algorithm, prime factorization, congruences, theorems of Fermat and Euler, elementary group theory, Chinese remainder theorem, factorization in the ring of polynomials, and classification of finite fields.

Distribution: (MQR-AS)Academic Career: UG Instructor: Marcelo Aguiar (ma18)

Full details for MATH 3360 : Applicable Algebra

Introduction to the rigorous theory underlying calculus, covering the real number system and functions of one variable. Based entirely on proofs. The student is expected to know how to read and, to some extent, construct proofs before taking this course. Topics typically include construction of the real number system, properties of the real number system, continuous functions, differential and integral calculus of functions of one variable, sequences and series of functions.

Distribution: (MQR-AS)Academic Career: UG Instructor: Gennady Uraltsev (gu35)

Full details for MATH 4130 : Honors Introduction to Analysis I

Proof-based introduction to further topics in analysis. Topics may include the Lebesgue measure and integration, functions of several variables, differential calculus, implicit function theorem, infinite dimensional normed and metric spaces, Fourier series, ordinary differential equations.

Distribution: (MQR-AS)Academic Career: UG Instructor: Camil Muscalu (fm69)

Full details for MATH 4140 : Honors Introduction to Analysis II

Theoretical and rigorous introduction to complex variable theory. Topics include complex numbers, differential and integral calculus for functions of a complex variable including Cauchy's theorem and the calculus of residues, elements of conformal mapping.

Distribution: (MQR-AS)Academic Career: UG Instructor: Timothy Buttsworth (tjb267)

Full details for MATH 4180 : Complex Analysis

Introduction to nonlinear dynamics, with applications to physics, engineering, biology, and chemistry. Emphasizes analytical methods, concrete examples, and geometric thinking. Topics include one-dimensional systems; bifurcations; phase plane; nonlinear oscillators; and Lorenz equations, chaos, strange attractors, fractals, iterated mappings, period doubling, renormalization.

Distribution: (MQR-AS)Academic Career: UG Instructor: Lionel Levine (ll432)

Full details for MATH 4210 : Nonlinear Dynamics and Chaos

Introduction to the fundamentals of numerical linear algebra: direct and iterative methods for linear systems, eigenvalue problems, singular value decomposition. In the second half of the course, the above are used to build iterative methods for nonlinear systems and for multivariate optimization. Strong emphasis is placed on understanding the advantages, disadvantages, and limits of applicability for all the covered techniques. Computer programming is required to test the theoretical concepts throughout the course.

Distribution: (MQR-AS)Academic Career: UG Instructor: David Bindel (dsb253)

Full details for MATH 4260 : Numerical Analysis: Linear and Nonlinear Problems

Topics are selected from first-order quasilinear equations, classification of second-order equations, with emphasis on maximum principles, existence, uniqueness, stability, Fourier series methods, approximation methods.

Distribution: (MQR-AS)Academic Career: UG Instructor: Timothy Healey (tjh10)

Full details for MATH 4280 : Introduction to Partial Differential Equations

Introduction to linear algebra, including the study of vector spaces, linear transformations, matrices, and systems of linear equations. Additional topics are quadratic forms and inner product spaces, canonical forms for various classes of matrices and linear transformations.

Distribution: (MQR-AS)Academic Career: UG Instructor: Yuri Berest (yb26)

Full details for MATH 4310 : Linear Algebra

Honors version of a course in abstract algebra, which treats the subject from an abstract and axiomatic viewpoint, including universal mapping properties. Topics include groups, groups acting on sets, Sylow theorems; rings, factorization: Euclidean rings, principal ideal domains and unique factorization domains, the structure of finitely generated modules over a principal ideal domain, fields, and Galois theory. The course emphasizes understanding the theory with proofs in both homework and exams.

Distribution: (MQR-AS)Academic Career: UG Instructor: Allen Knutson (ak596)

Full details for MATH 4340 : Honors Introduction to Algebra

Continuation of MATH 4410, although formally independent of the material covered there. The emphasis here is the study of certain combinatorial structures, such as Latin squares and combinatorial designs (which are of use in statistical experimental design), classical finite geometries and combinatorial geometries (also known as matroids, which arise in many areas from algebra and geometry through discrete optimization theory). There is an introduction to partially ordered sets and lattices, including general Möbius inversion and its application, as well as the Polya theory of counting in the presence of symmetries.

Distribution: (MQR-AS)Academic Career: UG Instructor: Ed Swartz (ebs22)

Full details for MATH 4420 : Introduction to Combinatorics II

An introduction to a topic that is central to mathematics and important in physics and engineering. The objects of study are certain classes of matrices, such as orthogonal, unitary, or symplectic matrices. These classes have both algebraic structure (groups) and geometric/topological structure (manifolds). Thus the course will be a mixture of algebra and geometry/topology, with a little analysis as well. The topics will include Lie algebras (which are an extension of the notion of vector multiplication in three-dimensional space), the exponential mapping (a generalization of the exponential function of calculus), and representation theory (which studies the different ways in which groups can be represented by matrices). Concrete examples will be emphasized. Background not included in the prerequisites will be developed as needed.

Distribution: (MQR-AS)Academic Career: UG Instructor: Mahdi Asgari (ma735)

Full details for MATH 4500 : Matrix Groups

Differential geometry involves using calculus to study geometric concepts such as curvature and geodesics. This introductory course focuses on the differential geometry of curves and surfaces. It may also touch upon the higher-dimensional generalizations, Riemannian manifolds, which underlie the study of general relativity.

Distribution: (MQR-AS)Academic Career: UG Instructor: Justin Moore (jtm237)

Full details for MATH 4540 : Introduction to Differential Geometry

Introduction to probability theory, which prepares the student to take MATH 4720. The course begins with basics: combinatorial probability, mean and variance, independence, conditional probability, and Bayes formula. Density and distribution functions and their properties are introduced. The law of large numbers and the central limit theorem are stated and their implications for statistics are discussed.

Distribution: (MQR-AS)Academic Career: UG Instructor: Laurent Saloff-Coste (lps2)

Full details for MATH 4710 : Basic Probability

Statistics have proved to be an important research tool in nearly all of the physical, biological, and social sciences. This course serves as an introduction to statistics for students who already have some background in calculus, linear algebra, and probability theory. Topics include parameter estimation, hypothesis testing, and linear regression. The course emphasizes both the mathematical theory of statistics and techniques for data analysis that are useful in solving scientific problems.

Distribution: (MQR-AS)Academic Career: UG Instructor: Marten Wegkamp (mhw73)

Full details for MATH 4720 : Statistics

A one-semester introduction to stochastic processes which develops the theory together with applications. The course will always cover Markov chains in discrete and continuous time and Poisson processes. Depending upon the interests of the instructor and the students, other topics may include queuing theory, martingales, Brownian motion, and option pricing.

Distribution: (MQR-AS)Academic Career: UG Instructor: Christian Noack (cjn59)

Full details for MATH 4740 : Stochastic Processes

An independent research course by arrangement with an individual professor. The goal is for the student to perform an independent investigation into a specific mathematical question. The student and professor will set expectations and grading policies at the beginning of the term.

Academic Career: UG Instructor: Marcelo Aguiar (ma18)Full details for MATH 4900 : Supervised Research

An independent reading course by arrangement with an individual professor. The goal is for the student to master a body of mathematics outside the normal curriculum. The student and professor will set expectations and grading policies at the beginning of the term.

Academic Career: UG Instructor: Marcelo Aguiar (ma18)Full details for MATH 4901 : Supervised Reading

Examines principles underlying the content of the secondary school mathematics curriculum, including connections with the history of mathematics, technology, and mathematics education research. One credit is awarded for attending three of the four Saturday workshops per year. Other credit options are available by permission of instructor for students completing additional work (e.g., independent study projects or presentations).

Academic Career: GR Instructor: Mary Ann Huntley (mh688)Full details for MATH 5080 : Special Study for Teachers

This course covers complex analysis, Fourier analysis, and distribution theory.

Academic Career: GR Instructor: John Hubbard (jhh8)Full details for MATH 6120 : Complex Analysis

This course highlights applications of functional analysis to the theory of partial differential equations (PDEs). It covers parts of the basic theory of linear (elliptic and evolutionary) PDEs, including Sobolev spaces, existence and uniqueness of solutions, interior and boundary regularity, maximum principles, and eigenvalue problems. Additional topics may include: an introduction to variational problems, Hamilton-Jacobi equations, and other modern techniques for non-linear PDEs.

Academic Career: GR Instructor: Timothy Healey (tjh10)Full details for MATH 6160 : Partial Differential Equations

Covers basic theory of Hilbert and Banach spaces and operations on them. Applications.

Academic Career: GR Instructor: Alex Townsend (ajt253)Full details for MATH 6220 : Applied Functional Analysis

Topics include review of planar (single-degree-of-freedom) systems; local and global analysis; structural stability and bifurcations in planar systems; center manifolds and normal forms; the averaging theorem and perturbation methods; Melnikov's method; discrete dynamical systems, maps and difference equations, homoclinic and heteroclinic motions, the Smale Horseshoe and other complex invariant sets; global bifurcations, strange attractors, and chaos in free and forced oscillator equations; and applications to problems in solid and fluid mechanics.

Academic Career: GR Instructor: Steven Strogatz (shs7)Full details for MATH 6270 : Applied Dynamical Systems

MATH 6310-6320 are the core algebra courses in the mathematics graduate program. MATH 6320 covers Galois theory, representation theory of finite groups, and introduction to homological algebra.

Academic Career: GR Instructor: Nicolas Templier (npt27)Full details for MATH 6320 : Algebra

A first course on homological algebra. Topics will include a brief introduction to categories and functors, chain and cochain complexes, operations on complexes, (co)homology, standard resolutions (injective, projective, flat), classical derived functors, Tor and Ext, Yoneda's interpretation of Ext, homological dimension, rings of small dimensions, introduction to group cohomology.

Academic Career: GR Instructor: Martin Kassabov (mdk35)Full details for MATH 6350 : Homological Algebra

An introduction to number theory focusing on the algebraic theory. Topics include, but are not limited to, number fields, Dedekind domains, class groups, Dirichlet's unit theorem, local fields, ramification, decomposition and inertia groups, and the distribution of primes.

Academic Career: GR Instructor: Shankar Sen (ss70)Full details for MATH 6370 : Algebraic Number Theory

An introduction to enumerative combinatorics from an algebraic, geometric and topological point of view. Topics include, but are not limited to, permutation statistics, partitions, generating functions, various types of posets and lattices (distributive, geometric, and Eulerian), Möbius inversion, face numbers, shellability, and relations to the Stanley-Reisner ring.

Academic Career: GR Instructor: Karola Meszaros (km626)Full details for MATH 6410 : Enumerative Combinatorics

MATH 6510-MATH 6520 are the core topology courses in the mathematics graduate program. MATH 6510 is an introductory study of certain geometric processes for associating algebraic objects such as groups to topological spaces. The most important of these are homology groups and homotopy groups, especially the first homotopy group or fundamental group, with the related notions of covering spaces and group actions. The development of homology theory focuses on verification of the Eilenberg-Steenrod axioms and on effective methods of calculation such as simplicial and cellular homology and Mayer-Vietoris sequences. If time permits, the cohomology ring of a space may be introduced.

Academic Career: GR Instructor: James West (jew13)Full details for MATH 6510 : Algebraic Topology

Conditional expectation, martingales, Brownian motion. Other topics such as Markov chains, ergodic theory, and stochastic calculus depending on time and interests of the instructor.

Academic Career: GR Instructor: Lionel Levine (ll432)Full details for MATH 6720 : Probability Theory II

This course will focus on the finite sample theory of statistical inference, emphasizing estimation, hypothesis testing, and confidence intervals. Specific topics include: uniformly minimum variance unbiased estimators, minimum risk equivariant estimators, Bayes estimators, minimax estimators, the Neyman-Pearson theory of hypothesis testing, and the construction of optimal invariant tests.

Academic Career: GR Instructor: Florentina Bunea (fb238)Full details for MATH 6730 : Mathematical Statistics I

Introduction to model theory at the level of the books by Hodges or Chang and Keisler.

Academic Career: GR Instructor: Justin Moore (jtm237)Full details for MATH 6830 : Model Theory

Selection of advanced topics from dynamical systems. Content varies.

Academic Career: GR Instructor: Steven Strogatz (shs7)Full details for MATH 7280 : Topics in Dynamical Systems

Talks on various methods in scientific computing, the analysis of their convergence properties and computational efficiency, and their adaptation to specific applications.

Academic Career: GR Instructor: Anil Damle (asd239)Alex Townsend (ajt253)

Full details for MATH 7290 : Seminar on Scientific Computing and Numerics

Selection of advanced topics from number theory. Course content varies.

Academic Career: GR Instructor: David Zywina (djz44)Full details for MATH 7370 : Topics in Number Theory

Topics will vary depending on the instructor and the level of the audience. They range from representation theory of Lie algebras and of real and p-adic Lie groups, geometric representation theory, quantum groups and their representations, invariant theory to applications of Lie theory to other parts of mathematics.

Academic Career: GR Instructor: Dan Barbasch (dmb14)Full details for MATH 7390 : Topics in Lie Groups and Lie Algebras

A seminar on an advanced topic in topology or a related subject. Content varies. The format is usually that the participants take turns to present.

Academic Career: GR Instructor: Kathryn Mann (kpm85)Full details for MATH 7520 : Berstein Seminar in Topology

A weekly seminar in which visiting or local speakers present results in topology, geometric group theory, or related subjects.

Academic Career: GR Full details for MATH 7560 : Topology and Geometric Group Theory SeminarSelection of advanced topics from modern algebraic, differential, and geometric topology. Content varies.

Academic Career: GR Instructor: James Hyde (jth263)Full details for MATH 7580 : Topics in Topology

Selection of advanced topics from modern geometry. Content varies.

Academic Career: GR Instructor: Xiaodong Cao (xc46)Full details for MATH 7620 : Topics in Geometry

Selection of topics from algebraic geometry. Content varies.

Academic Career: GR Instructor: Daniel Halpern-Leistner (dsh233)Full details for MATH 7670 : Topics in Algebraic Geometry

Selection of advanced topics from probability theory. Content varies.

Academic Career: GR Instructor: Philippe Sosoe (ps934)Full details for MATH 7710 : Topics in Probability Theory

A twice weekly seminar in logic. Typically, a topic is selected for each semester, and at least half of the meetings of the course are devoted to this topic with presentations primarily by students. Opportunities are also provided for students and others to present their own work and other topics of interest.

Academic Career: GR Instructor: Slawomir Solecki (ss3777)Full details for MATH 7820 : Seminar in Logic

Supervised research for the doctoral dissertation.

Academic Career: GR Instructor: Karola Meszaros (km626)Full details for MATH 7900 : Supervised Reading and Research