Derivatives of elementary functions, limits. Covers applications and modelling: graphing and optimization. Credit will be granted for only one of MATH 100 or MATH 116. [3-0-0] Prerequisite: Either (a) a score of 67% or higher in one of MATH 12, PREC 12 or (b) a score of 60% or higher in one of MATH 125, MATH 126. Equivalency: MATH116
Definite integral, integration techniques, applications, modelling, linear ODE's. Credit will be granted for only one of MATH 101 or MATH 142. [3-0-0] Prerequisite: One of MATH 100, MATH 116.
Antiderivatives, the definite integral, integration techniques, numerical integration, infinite series, applications of integration to differential equations and probability, linear algebra. Credit will be granted for only one of MATH 101, MATH 103, or MATH 142. [3-1-0] Prerequisite: One of MATH 100, MATH 116.
Intended for students not majoring in Mathematics or the Sciences who want some exposure to mathematical thinking. Logic, set theory, combinatorics, probability theory, matrix algebra, linear programming, graphs, and networks. This course cannot be taken for credit toward a B.Sc. or B.Sust. degree. [3-0-1] Prerequisite: Foundations of Mathematics 11.
The derivative; limits; rate of change; derivatives of algebraic, logarithmic, trigonometric and exponential functions; applications to marginal analysis; elasticity of demand; optimization and curve-sketching, Newtons Method and Taylor polynomials. Credit will be granted for only one of MATH 116 or MATH 100. [3-0-0] Prerequisite: Either (a) a score of 67% or higher in one of MATH 12, PREC 12 or (b) a score of 60% or higher in one of MATH 125, MATH 126. Equivalency: MATH100
Prepares students for a calculus course. Functions and their graphs; inverse functions; algebraic, exponential, logarithmic, trigonometric functions; trigonometric identities. Cannot be counted for credit toward the B.Sc. or B.Sust. degree. Credit will be granted for only one of MATH 125 or MATH 126. Students with credit for MATH 100 or 116 may not take MATH 125 for further credit. [3-0-1] Prerequisite: One of Principles of Mathematics 11, Pre-Calculus 11, Foundations of Mathematics 12.
Prepares students for calculus. Functions; graphs; inverse, algebraic, exponential, logarithmic, trigonometric functions; trigonometric identities. Uses cyclical analysis common in some Indigenous cultures. Cannot be counted for credit toward the B.Sc. or B.Sust. degree. Credit will be granted for only one of MATH 126 or 125. Students with credit for MATH 100 or 116 may not take MATH 126 for credit. [3-0-1] Prerequisite: One of Principles of Mathematics 11, Pre-Calculus 11, Foundations of Mathematics 12, or permission of the Department.
Continuation of MATH 116. Antiderivatives, the definite integral, integration techniques, numerical integration, double integrals, applications of integration including application to probability, elementary differential equations, functions of several variables; partial derivatives; Lagrange multipliers. Credit will be granted for only one of MATH 142 or MATH 101. [3-0-0] Prerequisite: One of MATH 100, MATH 116.
For Arts and prospective Education students who wish to gain a deeper understanding of mathematics. Using the approach of problem solving and logical reasoning throughout, topics are chosen from discrete mathematics, elementary number theory, probability and statistics, measurement and geometry, linear algebra, and applications. Credit will only be granted for one of MATH 160 or EDUC 160. Cannot be used for credit toward a B.Sc. or B.Sust. degree, or for the B.A. Major in Mathematics program.[3-0-0] Prerequisite: Prerequisite: Foundations of Mathematics 11 or Pre-calculus 11 Equivalency: EDUC 160
Analytic geometry in two and three dimensions, partial and directional derivatives, chain rule, maxima and minima, second derivative test, Lagrange multipliers, multiple integrals with applications. [3-1-0] Prerequisite: Either (a) MATH 101 or (b) a score of 65% or higher in MATH 103.
Sets and functions; induction; cardinality; properties of the real numbers; sequences, series, and limits. Logic, structure, style, and clarity of proofs emphasized throughout. [3-0-1] Prerequisite: Either (a) MATH 101 or (b) a score of 65% or higher in MATH 103.
Systems of linear equations, operations on matrices, determinants, eigenvalues and eigenvectors, diagonalization of symmetric matrices, and vector geometry. [3-0-0] Prerequisite: One of MATH 100, MATH 116.
Vector spaces, linear maps, change of basis, eigenvalues and eigenvectors, Jordan canonical forms, matrix decomposition, inner product spaces, orthogonality, linear operators. [3-0-0] Prerequisite: MATH 221.
First-order equations, initial value problems, existence and uniqueness theorems, second-order linear equations, superposition of solutions, independence, general solutions, non-homogeneous equations, phaseplane analysis, numerical methods, matrix methods for linear systems, and applications of differential equations to the physical, biological, and social sciences. [3-0-1] Prerequisite: Either (a) MATH 101 or (b) a score of 65% or higher in MATH 103. Corequisite: MATH 221 is recommended.
Numerical techniques for basic mathematical processes and their analysis. Taylor polynomials, root-finding, linear systems, eigenvalues, approximating derivatives, locating minimizers, approximating integrals, solving differential equations. Credit will be granted for only one of MATH 303 or COSC 303. [3-1-0] Prerequisite: All of MATH 200, MATH 221 and either (a) COSC 111 or (b) DATA 301. Equivalency: COSC303
LU-factorization, iterative estimates for eigenvalues, dynamical systems, orthogonality, QR-factorization, and applications of linear algebra. [3-0-0] Prerequisite: MATH 221.
Classical Euclidean, finite, modern, transformation geometry, and non-Euclidean geometry. [3-0-0] Prerequisite: MATH 220.
Properties of integers, the integers modulo n, groups, subgroups, cyclic groups, permutation groups, linear groups, quotient groups and homomorphisms, isomorphism theorems, direct products, and an introduction to rings and fields. [3-0-0] Prerequisite: MATH 220.
Divisibility of integers, congruences, Euler's Theorem, primitive roots, quadratic reciprocity, special Diophantine equations, distributions of primes. [3-0-0] Prerequisite: One of MATH 220, COSC 221.
Topics chosen by the instructor. These might include: division algorithms, group theory, continued fractions, primality testing, factoring. [3-0-0] Prerequisite: MATH 312.
Parametrizations, inverse and implicit functions, integrals with respect to length and area; grad, div, and curl, and theorems of Green, Gauss, and Stokes. [3-0-0] Prerequisite: MATH 200.
Methods of separation of variable, Fourier series, heat, wave and Laplace's equations, boundary value problems, eigenfunction expansions, and Sturm-Liouville problems. [3-0-1] Prerequisite: All of MATH 200, MATH 225.
Congruences and groups, introduction to rings and fields, and topics chosen from: lattices, Boolean algebra and applications, balanced incomplete block designs, introduction to cryptography, applications to group theory. [3-0-0] Prerequisite: MATH 221. Corequisite: MATH 311.
The real number system, real Euclidean n-space; open, closed, compact, and connected sets; Bolzano-Weierstrass theorem; sequences and series; continuity and uniform continuity; differentiability and mean-value theorems; Riemann or Riemann-Stieltjes integrals. [3-0-0] Prerequisite: MATH 220.
Metric and normed vector spaces; limits in normed vector spaces, compactness; sequences and series of functions, approximation of continuous functions by polynomials; functions from Rm to Rn, inverse and implicit function theorems. [3-0-0] Prerequisite: MATH 327.
Covers properties of rings and fields, factorization, polynomials over a field, field extensions, field isomorphisms and automorphism, group of automorphisms, and Galois theory of unsolvability. [3-0-0] Prerequisite: MATH 311.
Non-linear systems and iteration of functions; flows, phase portraits, periodic orbits, chaotic attractors, fractals, and invariant sets. [3-0-0] Prerequisite: All of MATH 200, MATH 225.
Linear programming problems, dual problems, the simplex algorithm, solution of primal and dual problems, sensitivity analysis. Additional topics chosen from: Karmarkar's algorithm, non-linear programming, game theory, applications. [3-0-0] Prerequisite: MATH 221.
Covers analytic functions, Cauchy-Riemann equations, power series, Laurent series, elementary functions, contour integrals, and poles and residues. Introduction to conformal mapping and applications of analysis to problems in physics and engineering. [3-0-0] Prerequisite: MATH 200.
Local theory of curves, Frenet-Serret apparatus, fundamentals of the Gaussian theory of surface, normal curvature, geodesics, Gaussian and mean curvatures, theorema egregium, an introduction to Riemannian geometry, Gauss-Bonnet Theorem, and applications. [3-0-0] Prerequisite: All of MATH 200, MATH 221. and 9 credits of 300-level MATH.
Pricing theory of financial derivative securities. Options and markets, present and future values, price movement modeled by Brownian motion, Ito's formula, parbolic partial differential equations, Black-Scholes model. Prices of European options as solutions of initial/boundary value problems for heat equations, American options, free boundary problems. [3-0-0] Prerequisite: All of MATH 221, MATH 319 and one of MATH 302, STAT 303.
General (point-set) topology. Naive set theory, relations and functions, order relations, cardinality, Axiom of Choice, well-ordering, topological spaces, bases, subspaces, product spaces, limit points, continuous functions, homeomorphisms, metric spaces, connectedness, compactness, countability axioms, separation axioms, Urysohn lemma, Tietze extension theorem, Urysohn metrization theorem, Tychonoff theorem. [3-0-0] Prerequisite: MATH 327.
Lebesgue measure, measurable functions, integration, convergence theorems, Lp spaces, Holder and Minkowski inequalities, Lebesgue-Radon-Nikodym theorem, Lebesgue differentiation. Credit will be granted for only one of MATH 427 or MATH 527. [3-0-0] Prerequisite: MATH 327.
Banach spaces, linear operators, bounded and compact operators, strong, weak, and weak* topology. Hahn-Banach, open mapping, and closed graph theorems. Hilbert spaces, symmetric and self-adjoint operators, spectral theory for bounded operators. Credit will be granted for only one of MATH 428 or MATH 528. [3-0-0] Prerequisite: MATH 327.
Students should consult the department for the particular topics offered in a given year. [3-0-0] Prerequisite: Third-year standing and permission of the department head.
Students should consult the department for the particular topics offered in a given year. [3-0-0] Prerequisite: Third-year standing and permission of the department head.
Formulation of real-world optimization problems using techniques such as linear programming, network flows, integer programming, and dynamic programming. Solution by appropriate software. [3-0-0] Prerequisite: MATH 340.
Basic graph theory, emphasizing trees, tree growing algorithms, and proof techniques. Problems chosen from: shortest paths, maximum flows, minimum cost flows, matchings, graph colouring. Linear programming duality will be an important tool. [3-0-0] Prerequisite: MATH 340.
Introductory course in mostly non-algorithmic topics. Planarity and Kuratowski's theorem, graph colouring, graph minors, random graphs, cycles in graphs, Ramsey theory, extremal graph theory. Proofs emphasized. [3-0-0] Prerequisite: At least 12 credits of 300-level MATH.
Investigation of a specific topic as agreed upon by the student and the faculty supervisor. Students will be expected to complete a project and make an oral presentation. Prerequisite: 15 credits of 300- or 400-level MATH and STAT courses and permission of the department head and faculty supervisor.
Mathematical modelling in biological disciplines such as population dynamics, ecology, pattern formation, tumour growth, immune response, biomechanics, and epidemiology. Theory of such models formulated as difference equations, ordinary differential equations, and partial differential equations. [3-0-0] Prerequisite: MATH 225. MATH 319 is recommended.
Students should consult the department for the particular topics offered in a given year. [3-0-0] Prerequisite: Third-year standing and permission of the department head.
Convex analysis, non-smooth optimization, Karush-Kuhn-Tucker theorem, iterative methods. [3-0-0] Prerequisite: MATH 327.
Mathematical analysis and development of derivative-free optimization methods. Heuristic methods, direct search methods, model-based methods, convergence analysis, topics in implementation and testing. Credit will be granted for only one of MATH 462 or MATH 562. [3-0-0] Prerequisite: All of MATH 200, MATH 220, MATH 221. MATH 303 or COSC 303 is recommended.
Nonconvex analysis, semi-continuous functions, Lipschitz functions, tangent cone, normal cone, subdifferentials, optimality conditions, regularizations, algorithms for nonconvex optimization. Credit will be granted for only one of MATH 464 or MATH 564. [3-0-0] Prerequisite: MATH 327.
Splitting Algorithms. Monotone operators, inclusion problems and duality, non-expansive mappings, fundamental algorithms and variants featuring acceleration and randomization. Credit will be granted for only one of MATH 465 or MATH 565. [3-0-0] Prerequisite: MATH 327. MATH 461 is recommended.
Topological spaces, interior, closure, and boundary of a set, creating new topological spaces, quotient spaces: examples and applications, continuous functions and homeomorphism, metric spaces & metrizability, connectedness, compactness, countability and separation axioms, applications chosen from the above topics. [3-0-0]
Theory of the nature of problems from combinatorial optimization; solution techniques and theory; topics from integer programming, network flows, and matroids. [3-0-0]
Lebesgue measure, measurable functions, integration, convergence theorems, Lp spaces, Holder and Minkowski inequalities, Lebesgue-Radon-Nikodym theorem, Lebesgue differentiation. Credit will be granted for only one of MATH 527 or MATH 427. [3-0-0]
Banach spaces, linear operators, bounded and compact operators, strong, weak, and weak* topology. Hahn-Banach, open mapping, and closed graph theorems. Hilbert spaces, symmetric and self-adjoint operators, spectral theory for bounded operators. Credit will be granted for only one of MATH 528 or MATH 428. [3-0-0]
Ring localizations, integral elements, prime and maximal ideals, Dedekind domains, unique factorization of ideals, algebraic number fields, integral bases, discriminants, norms, class number. [3-0-0]
Pass/Fail.
Mathematical methods in modelling biological processes at levels from cell biochemistry to community ecology. [3-0-0]
Mathematical analysis and development of derivative-free optimization methods. Heuristic methods, direct search methods, model-based methods, convergence analysis, topics in implementation and testing. Credit will be granted for only one of MATH 562 or MATH 462. [3-0-0]
Separation and support properties of convex sets; polar, tangent, and normal cones; Fenchel conjugation; subgradient calculus for convex functions; Fenchel duality for convex optimization problems; algorithms for non-differentiable optimization; non-smooth analysis and optimization for non-convex objects. [3-0-0]
Nonconvex analysis, semi-continuous functions, Lipschitz functions, tangent cone, normal cone, subdifferentials, optimality conditions, regularizations, algorithms for nonconvex optimization. Credit will be granted for only one of MATH 464 or MATH 564. [3-0-0]
Splitting Algorithms. Monotone operators, inclusion problems and duality, non-expansive mappings, fundamental algorithms and variants featuring acceleration and randomization. Credit will be granted for only one of MATH 565 or MATH 465. [3-0-0]
Topics from optimization and analysis that are particularly relevant for beginning graduate students at the master's level. [0-0-3]. The credit value for this course will be determined in consultation with the student prior to the registration.
Presentation and discussion of recent results in the mathematical, statistical, or related literature. Credit may be obtained more than once. Pass/Fail. [0-0-1]. The credit value for this course will be determined in consultation with the student prior to the registration.
Topics chosen from group theory, rings and modules, Galois theory, commutative rings, categorical algebra, representations of finite groups, and other topics. The credit value for this course will be determined in consultation with the student prior to the registration.
Topics, which depend on the students' background and requirements and on the instructor, are drawn from functional analysis, measure and integration theory, non-smooth analysis, and variational analysis. [3-0-0]. The credit value for this course will be determined in consultation with the student prior to the registration.
Advanced theoretical, algorithmic, or computational topics in optimization. Non-smooth optimization and analysis in infinite-dimensional spaces; monotone operators; subgradient calculus for non-convex functions; semidefinite programming. Interior point methods, projection, and other non-differentiable algorithms. Complexity of optimization algorithms; practical overview of optimization solvers for continuous and discrete problems; numerical and symbolic computation of Fenchel conjugates. [3-0-0]. The credit value for this course will be determined in consultation with the student prior to the registration.
Topics will be chosen from different areas of applied mathematics. Content will be determined so as to complement course offerings and meet the needs of the students. Credit for this course may be obtained more than once. The credit value for this course will be determined in consultation with the student prior to the registration.
Topics chosen will depend on the instructor. These may include algebraic number theory, group representation theory, analytic number theory, category theory, combinatorics or algebraic topology. The credit value for this course will be determined in consultation with the student prior to the registration.
Advanced study under the direction of a faculty member may be arranged in special situations. The credit value for this course will be determined in consultation with the student prior to the registration.
Pass/Fail.
Topics from optimization and analysis that are particularly relevant for master's students nearing completion of their program, as well as beginning Ph.D. students. [0-0-3]. The credit value for this course will be determined in consultation with the student prior to the registration.