Please note:
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Mathematics Honours
This program leads to a bachelor of science (BSc) honours degree.
Prerequisite Grade Requirement
To enroll in a course offered by the Department of Mathematics, a student must obtain a grade of C or better in each prerequisite course. Some courses may require higher prerequisite grades. Check the MATH course’s Calendar description for details.
Students will not normally be permitted to enroll in any course for which a D grade or lower was obtained in any prerequisite. No student may complete, for further credit, any course offered by the Department of Mathematics which is a prerequisite for a course the student has already completed with a grade of C or higher, without permission of the department.
Program Requirements
Students complete 120 units, as specified below.
Lower Division Requirements
Students complete either
both of
An elementary introduction to computing science and computer programming, suitable for students with little or no programming background. Students will learn fundamental concepts and terminology of computing science, acquire elementary skills for programming in a highlevel language and be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode, data types and control structures, fundamental algorithms, computability and complexity, computer architecture, and history of computing science. Treatment is informal and programming is presented as a problemsolving tool. Prerequisite: BC Math 12 or equivalent is recommended. Students with credit for CMPT 102, 128, 130 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129, 130 or 135 first may not then take this course for further credit. Quantitative/BreadthScience.
Section  Instructor  Day/Time  Location 

D100 
Angelica Lim 
Mo, We, Fr 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 
D200 
Angelica Lim 
Mo, We, Fr 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 
D400 
Harinder Khangura 
Mo, We, Fr 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 
D401 
Th 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 

D402 
Th 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D403 
Th 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 

D404 
Th 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D405 
Th 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D406 
Th 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D407 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D408 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
A second course in computing science and programming intended for students studying mathematics, statistics or actuarial science and suitable for students who already have some background in computing science and programming. Topics include: a review of the basic elements of programming: use and implementation of elementary data structures and algorithms; fundamental algorithms and problem solving; basic objectoriented programming and software design; computation and computability and specification and program correctness. Prerequisite: CMPT 102 or CMPT 120. Students with credit for CMPT 125 or 135 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Janice Regan 
Mo, We, Fr 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
D101 
We 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 

D102 
We 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 

D103 
We 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D104 
We 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D105 
We 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D106 
We 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D107 
We 5:30 PM – 6:20 PM 
REMOTE LEARNING, Burnaby 

D108 
We 5:30 PM – 6:20 PM 
REMOTE LEARNING, Burnaby 
(Students transferring into a math program should contact the math undergraduate advisor if they have already completed equivalent courses.)
or both of
An introduction to computing science and computer programming, using a systems oriented language, such as C or C++. This course introduces basic computing science concepts. Topics will include: elementary data types, control structures, functions, arrays and strings, fundamental algorithms, computer organization and memory management. Prerequisite: BC Math 12 (or equivalent, or any of MATH 100, 150, 151, 154, or 157). Students with credit for CMPT 102, 120, 128 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129 or 135 first may not then take this course for further credit. Quantitative/BreadthScience.
A second course in systemsoriented programming and computing science that builds upon the foundation set in CMPT 130 using a systemsoriented language such as C or C++. Topics: a review of the basic elements of programming; introduction to objectoriented programming (OOP); techniques for designing and testing programs; use and implementation of elementary data structures and algorithms; introduction to embedded systems programming. Prerequisite: CMPT 130. Students with credit for CMPT 125, 126, or 129 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Toby Donaldson 
Mo, We, Fr 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
D101 
Th 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Th 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D103 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D104 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D105 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D106 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D107 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D108 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 
and all of
Introduction to counting, induction, automata theory, formal reasoning, modular arithmetic. Prerequisite: BC Math 12 (or equivalent), or any of MATH 100, 150, 151, 154, 157. Quantitative/BreadthScience.
Section  Instructor  Day/Time  Location 

D100 
Andrei Bulatov 
Mo, We, Fr 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 
D101 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D103 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D104 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D105 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D106 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D107 
Th 5:30 PM – 6:20 PM 
REMOTE LEARNING, Burnaby 

D108 
Th 5:30 PM – 6:20 PM 
REMOTE LEARNING, Burnaby 

D200 
Harinder Khangura 
Mo, We, Fr 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 
D201 
Th 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 

D202 
Th 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 

D203 
Th 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D204 
Th 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D205 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D206 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D207 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D208 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
A continuation of MACM 101. Topics covered include graph theory, trees, inclusionexclusion, generating functions, recurrence relations, and optimization and matching. Prerequisite: MACM 101 or (ENSC 251 and one of MATH 232 or MATH 240). Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Michael Monagan 
Mo, We, Fr 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 
D200 
Mahsa Faizrahnemoon 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
D300 
Mo, We, Fr 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

OP01  TBD  
OP02  TBD  
OP03  TBD 
Using a mathematical software package for doing calculations in linear algebra. Development of computer models that analyze and illustrate applications of linear algebra. All calculations and experiments will be done in the Matlab software package. Topics include: largescale matrix calculations, experiments with cellular automata, indexing, searching and ranking pages on the internet, population models, data fitting and optimization, image analysis, and cryptography. Prerequisite: One of CMPT 102, 120, 126, 128 or 130 and one of MATH 150, 151, 154 or 157 and one of MATH 232 or 240. MATH 232 or 240 can be taken as corequisite. Students in excess of 80 units may not take MACM 203 for further credit. Quantitative.
Using a mathematical software package for doing computations from calculus. Development of computer models that analyze and illustrate applications of calculus. All calculations and experiments will be done in the Maple software package. Topics include: graphing functions and data, preparing visual aids for illustrating mathematical concepts, integration, Taylor series, numerical approximation methods, 3D visualization of curves and surfaces, multidimensional optimization, differential equations and disease spread models. Prerequisite: One of CMPT 102, 120, 126, 128 or 130 and MATH 251. MATH 251 can be taken as a corequisite. Students in excess of 80 units may not take MACM 204 for further credit. Quantitative.
Mathematical induction. Limits of real sequences and real functions. Continuity and its consequences. The mean value theorem. The fundamental theorem of calculus. Series. Prerequisite: MATH 152; or MATH 155 or 158 with a grade of B. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Stephen Choi 
Mo, We, Fr 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 
D101 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D103 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 
Rectangular, cylindrical and spherical coordinates. Vectors, lines, planes, cylinders, quadric surfaces. Vector functions, curves, motion in space. Differential and integral calculus of several variables. Vector fields, line integrals, fundamental theorem for line integrals, Green's theorem. Prerequisite: MATH 152; or MATH 155 or MATH 158 with a grade of at least B. Recommended: It is recommended that MATH 240 or 232 be taken before or concurrently with MATH 251. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Jamie Mulholland 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
OP01  TBD 
Vector calculus, divergence, gradient and curl; line, surface and volume integrals; conservative fields, theorems of Gauss, Green and Stokes; general curvilinear coordinates and tensor notation. Introduction to orthogonality of functions, orthogonal polynomials and Fourier series. Prerequisite: MATH 240 or 232, and 251. MATH 240 or 232 may be taken concurrently. Students with credit for MATH 254 may not take MATH 252 for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Razvan Fetecau 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
D101 
Th 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Th 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 
Firstorder differential equations, second and higherorder linear equations, series solutions, introduction to Laplace transform, systems and numerical methods, applications in the physical, biological and social sciences. Prerequisite: MATH 152; or MATH 155/158 with a grade of at least B, MATH 232 or 240. Students with credit for MATH 310 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Steven Ruuth 
Mo, We, Fr 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 
D101 
Tu 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D102 
Tu 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 

D103 
Tu 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 
Basic laws of probability, sample distributions. Introduction to statistical inference and applications. Prerequisite: or Corequisite: MATH 152 or 155 or 158. Students wishing an intuitive appreciation of a broad range of statistical strategies may wish to take STAT 100 first. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Derek Bingham 
Mo, We, Fr 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 
OP01  TBD 
and one of
Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Topics as for Math 151 with a more extensive review of functions, their properties and their graphs. Recommended for students with no previous knowledge of Calculus. In addition to regularly scheduled lectures, students enrolled in this course are encouraged to come for assistance to the Calculus Workshop (Burnaby), or Math Open Lab (Surrey). Prerequisite: PreCalculus 12 (or equivalent) with a grade of at least B+, or MATH 100 with a grade of at least B, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 151, 154 or 157 may not take MATH 150 for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Sophie Burrill 
Mo, Tu, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
D200 
Natalia Kouzniak 
Mo, We, Fr 11:30 AM – 12:20 PM We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 
OP01  TBD  
OP02  TBD  
OP03  TBD 
Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Logarithmic and exponential functions, trigonometric functions, inverse functions. Limits, continuity, and derivatives. Techniques of differentiation, including logarithmic and implicit differentiation. The Mean Value Theorem. Applications of differentiation including extrema, curve sketching, Newton's method. Introduction to modeling with differential equations. Polar coordinates, parametric curves. Prerequisite: PreCalculus 12 (or equivalent) with a grade of at least A, or MATH 100 with a grade of at least B, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 154 or 157 may not take MATH 151 for further credit. Quantitative.
Designed for students specializing in the biological and medical sciences. Topics include: limits, growth rate and the derivative; elementary functions, optimization and approximation methods, and their applications; mathematical models of biological processes. Prerequisite: PreCalculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 151 or 157 may not take MATH 154 for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Luis Goddyn 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
OP01  TBD  
OP02  TBD 
Designed for students specializing in business or the social sciences. Topics include: limits, growth rate and the derivative; logarithmic, exponential and trigonometric functions and their application to business, economics, optimization and approximation methods; introduction to functions of several variables with emphasis on partial derivatives and extrema. Prerequisite: PreCalculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 151 or 154 may not take MATH 157 for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Randall Pyke Justin Chan 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D200 
Mo, We, Fr 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

OP01  TBD  
OP02  TBD 
and one of
Riemann sum, Fundamental Theorem of Calculus, definite, indefinite and improper integrals, approximate integration, integration techniques, applications of integration. Firstorder separable differential equations and growth models. Sequences and series, series tests, power series, convergence and applications of power series. Prerequisite: MATH 150 or 151; or MATH 154 or 157 with a grade of at least B. Students with credit for MATH 155 or 158 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Vijaykumar Singh 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
D200 
Brenda Davison 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D300 
Brenda Davison 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
OP01  TBD  
OP02  TBD  
OP03  TBD 
Designed for students specializing in the biological and medical sciences. Topics include: the integral, partial derivatives, differential equations, linear systems, and their applications; mathematical models of biological processes. Prerequisite: MATH 150, 151 or 154; or MATH 157 with a grade of at least B. Students with credit for MATH 152 or 158 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Jonathan Jedwab Natalia Kouzniak 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
D200 
Natalia Kouzniak Jonathan Jedwab 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
OP01  TBD  
OP02  TBD 
Designed for students specializing in business or the social sciences. Topics include: theory of integration, integration techniques, applications of integration; functions of several variables with emphasis on double and triple integrals and their applications; introduction to differential equations with emphasis on some special firstorder equations and their applications; sequences and series. Prerequisite: MATH 150 or 151 or 154 or 157. Students with credit for MATH 152 or 155 may not take MATH 158 for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

E100 
Mo 4:30 PM – 5:20 PM We 4:30 PM – 6:20 PM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 

OP01  TBD 
and one of
Linear equations, matrices, determinants. Introduction to vector spaces and linear transformations and bases. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. An emphasis on applications involving matrix and vector calculations. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 make not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Luis Goddyn 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D200 
Seyyed Aliasghar Hosseini 
Mo, We, Fr 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 
OP01  TBD  
OP02  TBD 
Linear equations, matrices, determinants. Real and abstract vector spaces, subspaces and linear transformations; basis and change of basis. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. Applications. Subject is presented with an abstract emphasis and includes proofs of the basic theorems. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 232 cannot take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Jonathan Jedwab 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
OP01  TBD 
and at least one of
Introduction to a variety of practical and important data structures and methods for implementation and for experimental and analytical evaluation. Topics include: stacks, queues and lists; search trees; hash tables and algorithms; efficient sorting; objectoriented programming; time and space efficiency analysis; and experimental evaluation. Prerequisite: (MACM 101 and ((CMPT 125 and 127), CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252). Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Igor Shinkar 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D101 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D102 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D103 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D104 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D105 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D106 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D107 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D108 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D200 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D201 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D202 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D203 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D204 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D205 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D206 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D207 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D208 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
This course is a continuation of STAT 270. Review of probability models. Procedures for statistical inference using survey results and experimental data. Statistical model building. Elementary design of experiments. Regression methods. Introduction to categorical data analysis. Prerequisite: STAT 270 and one of MATH 152, MATH 155, or MATH 158. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Liangliang Wang 
Tu 10:30 AM – 12:20 PM Fr 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 
D101 
Mo 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Mo 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D103 
Mo 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D104 
Mo 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 
+The following substitutions are also permitted.
They may not be used to satisfy the upper division requirements below.
MACM 409  Numerical Linear Algebra: Algorithms, Implementation and Applications (3) for MACM 203.
MACM 401  Introduction to Computer Algebra (3) for MACM 204.
MACM 442  Cryptography (3) for MACM 204.
* strongly recommended
** with a B grade or better
Upper Division Requirements
Students complete at least 48 units of which at least 15 must be at the 400 level. Students complete all of
Sequences and series of functions, topology of sets in Euclidean space, introduction to metric spaces, functions of several variables. Prerequisite: MATH 242 and 251. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Nilima Nigam 
Mo, We, Fr 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 
D101 
Th 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Th 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 
The integers, fundamental theorem of arithmetic. Equivalence relations, modular arithmetic. Univariate polynomials, unique factorization. Rings and fields. Units, zero divisors, integral domains. Ideals, ring homomorphisms. Quotient rings, the ring isomorphism theorem. Chinese remainder theorem. Euclidean, principal ideal, and unique factorization domains. Field extensions, minimal polynomials. Classification of finite fields. Prerequisite: MATH 240 (or MATH 232 with a grade of at least B). Students with credit for MATH 332 may not take this course for further credit. Quantitative.
Finite groups and subgroups. Cyclic groups and permutation groups. Cosets, normal subgroups and factor groups. Homomorphisms and isomorphisms. Fundamental theorem of finite abelian groups. Sylow theorems. Prerequisite: MATH 340 or 342 or 332. Students with credit for MATH 339 may not take this course for further credit.
Section  Instructor  Day/Time  Location 

D100 
Nils Bruin 
Mo, We, Fr 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
D101 
Tu 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 
Students will develop skills required for mathematical research. This course will focus on communication in both written and oral form. Students will write documents and prepare presentations in a variety of formats for academic and nonacademic purposes. The LaTeX document preparation system will be used. Course will be given on a pass/fail basis. Corequisite: MATH 499W.
An honours research project in mathematics is an original presentation of an area or problem in mathematics. A typical project is an original synthesis of knowledge generated from students research experience. A project can contain substantive, original mathematics, but need not. The presentation consists of a written report and an oral presentation both of which must be completed before the end of the exam period. Prerequisite: 18 credits of upper division MATH or MACM courses. Must be in an honours program with a GPA of at least 3.0. Corequisite: MATH 498. Writing.
and one of
Structures and algorithms, generating elementary combinatorial objects, counting (integer partitions, set partitions, Catalan families), backtracking algorithms, branch and bound, heuristic search algorithms. Prerequisite: MACM 201 (with a grade of at least B). Recommended: knowledge of a programming language. Quantitative.
Fundamental concepts, trees and distances, matchings and factors, connectivity and paths, network flows, integral flows. Prerequisite: MACM 201 (with a grade of at least B). Quantitative.
Model building using integer variables, computer solution, relaxations and lower bounds, heuristics and upper bounds, branch and bound algorithms, cutting plane algorithms, valid inequalities and facets, branch and cut algorithms, Lagrangian duality, column generation of algorithms, heuristics algorithms and analysis. Prerequisite: MATH 308. Quantitative.
An introduction to the theory and practice of errorcorrecting codes. Topics will include finite fields, polynomial rings, linear and nonlinear codes, BCH codes, convolutional codes, majority logic decoding, weight distribution of codes, and bounds on the size of codes. Prerequisite: MATH 340 or 332. Quantitative.
In addition to the above core requirement of 24 units, students must complete the requirements for at least one of the three concentrations below.
Algebra and Number Theory Concentration
Students complete at least 9 units from the following list of which at least 3 units must be at the 400 level.
Data structures and algorithms for mathematical objects. Topics include long integer arithmetic, computing polynomial greatest common divisors, the fast Fourier transform, Hensel's lemma and padic methods, differentiation and simplification of formulae, and polynomial factorization. Students will use a computer algebra system such as Maple for calculations and programming. Prerequisite: CMPT 307 or MATH 332 or MATH 340. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Michael Monagan 
Tu 2:30 PM – 4:20 PM Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 
D101 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
An introduction to the subject of modern cryptography. Classical methods for cryptography and how to break them, the data encryption standard (DES), the advanced encryption standard (AES), the RSA and ElGammal public key cryptosystems, digital signatures, secure hash functions and pseudorandom number generation. Algorithms for computing with long integers including the use of probabilistic algorithms. Prerequisite: (CMPT 201 or 225) and one of (MATH 340 or 332 or 342); or CMPT 405. Students with credit for MACM 498 between Fall 2003 and Spring 2006 may not take this course for further credit. Quantitative.
Linear Algebra. Vector space and matrix theory. Prerequisite: MATH 340 or 332 or permission of the instructor. Students with credit for MATH 438 may not take this course for further credit. Quantitative.
A study of ideals and varieties. Topics include affine varieties, ideals, Groebner bases, the Hilbert basis theorem, resultants and elimination, Hilbert's Nullstellensatz. irreducible varieties and prime ideals, decomposition of varieties, polynomial mappings, quotient rings, projective space and projective varieties. Prerequisite: MATH 340. Students who have taken this course as MATH 439 Special Topics may not complete this course for further credit.
An introduction to the theory and practice of errorcorrecting codes. Topics will include finite fields, polynomial rings, linear and nonlinear codes, BCH codes, convolutional codes, majority logic decoding, weight distribution of codes, and bounds on the size of codes. Prerequisite: MATH 340 or 332. Quantitative.
Analysis and Optimization Concentration
Students complete at least 9 units from the following list of which at least 3 units must be at the 400 level.
A presentation of the problems commonly arising in numerical analysis and scientific computing and the basic methods for their solutions. Prerequisite: MATH 152 or 155 or 158, and MATH 232 or 240, and computing experience. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Steven Ruuth 
Mo, We, Fr 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 
D101 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D102 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D103 
We 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D104 
Th 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D105 
Th 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 

D106 
Th 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D107 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 
Linear programming modelling. The simplex method and its variants. Duality theory. Postoptimality analysis. Applications and software. Additional topics may include: game theory, network simplex algorithm, and convex sets. Prerequisite: MATH 150, 151, 154, or 157 and MATH 240 or 232. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Mahsa Faizrahnemoon 
Mo, We, Fr 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 
D101 
Tu 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Tu 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D103 
Tu 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D104 
Tu 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 
Theoretical and computational methods for investigating the minimum of a function of several real variables with and without inequality constraints. Applications to operations research, model fitting, and economic theory. Prerequisite: MATH 232 or 240, and 251. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Randall Pyke Randall Pyke 
Mo, We, Fr 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 
D102 
Th 5:30 PM – 6:20 PM 
REMOTE LEARNING, Burnaby 
Fourier series, ODE boundary and eigenvalue problems. Separation of variables for the diffusion wave and Laplace/Poisson equations. Polar and spherical coordinate systems. Symbolic and numerical computing, and graphics for PDEs. Prerequisite: MATH 260 or MATH 310; and one of MATH 251 with a grade of B+, or one of MATH 252 or 254. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Ralf Wittenberg 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D101 
Tu 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
Model building using integer variables, computer solution, relaxations and lower bounds, heuristics and upper bounds, branch and bound algorithms, cutting plane algorithms, valid inequalities and facets, branch and cut algorithms, Lagrangian duality, column generation of algorithms, heuristics algorithms and analysis. Prerequisite: MATH 308. Quantitative.
Firstorder linear equations, the method of characteristics. The wave equation. Harmonic functions, the maximum principle, Green's functions. The heat equation. Distributions and transforms. Higher dimensional eigenvalue problems. An introduction to nonlinear equations. Burgers' equation and shock waves. Prerequisite: (MATH 260 or MATH 310) and one of MATH 314, MATH 320, MATH 322, PHYS 384. An alternative to the above prerequisite is both of (MATH 252 or MATH 254) and (MATH 260 or MATH 310), both with grades of at least A. Quantitative.
Convergence in Euclidean spaces, Fourier series and their convergence, Legendre polynomials, Hermite and Laguerre polynomials. Prerequisite: MATH 232 or 240 and one of MATH 314, 320, 322, PHYS 384. Students with credit for MATH 420 or MATH 719 may not complete this course for further credit. Quantitative.
Metric spaces, normed vector spaces, measure and integration, an introduction to functional analysis. Prerequisite: MATH 320. Quantitative.
An introduction to probability from the rigorous point of view. Random variables. Generating functions. Convergence of random variables. The strong law of large numbers and the central limit theorem. Stochastic processes. Stationary process and martingales. Prerequisite: MATH 242 and (MATH 348 or STAT 380).
Discrete Mathematics Concentration
Students complete
Introduction to a variety of practical and important data structures and methods for implementation and for experimental and analytical evaluation. Topics include: stacks, queues and lists; search trees; hash tables and algorithms; efficient sorting; objectoriented programming; time and space efficiency analysis; and experimental evaluation. Prerequisite: (MACM 101 and ((CMPT 125 and 127), CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252). Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Igor Shinkar 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D101 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D102 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D103 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D104 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D105 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D106 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D107 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D108 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D200 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D201 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D202 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D203 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D204 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D205 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D206 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D207 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D208 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
and at least 9 units from the following list of which at least 3 units must be at the 400 level.
Analysis and design of data structures for lists, sets, trees, dictionaries, and priority queues. A selection of topics chosen from sorting, memory management, graphs and graph algorithms. Prerequisite: CMPT 225, MACM 201, MATH 151 (or MATH 150), and MATH 232 or 240.
Section  Instructor  Day/Time  Location 

D100 
Qianping Gu 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
Models of computation, methods of algorithm design; complexity of algorithms; algorithms on graphs, NPcompleteness, approximation algorithms, selected topics. Prerequisite: CMPT 307.
An introduction to the subject of modern cryptography. Classical methods for cryptography and how to break them, the data encryption standard (DES), the advanced encryption standard (AES), the RSA and ElGammal public key cryptosystems, digital signatures, secure hash functions and pseudorandom number generation. Algorithms for computing with long integers including the use of probabilistic algorithms. Prerequisite: (CMPT 201 or 225) and one of (MATH 340 or 332 or 342); or CMPT 405. Students with credit for MACM 498 between Fall 2003 and Spring 2006 may not take this course for further credit. Quantitative.
Structures and algorithms, generating elementary combinatorial objects, counting (integer partitions, set partitions, Catalan families), backtracking algorithms, branch and bound, heuristic search algorithms. Prerequisite: MACM 201 (with a grade of at least B). Recommended: knowledge of a programming language. Quantitative.
Fundamental concepts, trees and distances, matchings and factors, connectivity and paths, network flows, integral flows. Prerequisite: MACM 201 (with a grade of at least B). Quantitative.
Model building using integer variables, computer solution, relaxations and lower bounds, heuristics and upper bounds, branch and bound algorithms, cutting plane algorithms, valid inequalities and facets, branch and cut algorithms, Lagrangian duality, column generation of algorithms, heuristics algorithms and analysis. Prerequisite: MATH 308. Quantitative.
An introduction to the theory and practice of errorcorrecting codes. Topics will include finite fields, polynomial rings, linear and nonlinear codes, BCH codes, convolutional codes, majority logic decoding, weight distribution of codes, and bounds on the size of codes. Prerequisite: MATH 340 or 332. Quantitative.
Additional Electives
Students must complete an additional 15 upper division units. These units can be any upper division MATH or MACM courses or taken from the following list.
Central forces, rigid body motion, small oscillations. Lagrangian and Hamiltonian formulations of mechanics. Prerequisite: PHYS 384, with a minimum grade of C or permission of the department. Nonphysics majors may enter with MATH 252; MATH 260 or MATH 310; PHYS 211. All prerequisite courses require a minimum grade of C. Quantitative.
Review of discrete and continuous probability models and relationships between them. Exploration of conditioning and conditional expectation. Markov chains. Random walks. Continuous time processes. Poisson process. Markov processes. Gaussian processes. Prerequisite: STAT 330, or all of: STAT 285, MATH 208W, and MATH 251. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Richard Lockhart 
Mo, We, Fr 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 
D101 
We 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 

D102 
Fr 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 
They may include additional courses from the three Concentrations. The total number of 400 level units must be at least 15.
NOTE: SFU students accepted in the accelerated master’s within the Department of Mathematics may apply a maximum of 10 graduate course units, taken while completing the bachelor's degree, towards the upper division electives of the bachelor's program and the requirements of the master's degree. For more information go to: https://www.sfu.ca/gradstudies/apply/programs/acceleratedmasters.html.
Science Electives
Students obtain at least six units in courses offered by the Faculty of Science outside the Department of Mathematics, and the Department of Statistics and Actuarial Science. Courses PHYS 100, BISC 100 and CHEM 110/111 cannot be used to satisfy this requirement.
Other Requirements
Of the total 120 units required for the honours, at least 60 units must be from the upper division. A cumulative grade point average (CGPA) of at least 3.00 and an upper division grade point average of at least 3.00 are required. These averages are calculated on all courses completed at the University. If both averages are at least 3.50, the designation 'first class' applies.
University Honours Degree Requirements
Students must also satisfy University degree requirements for degree completion.
Writing, Quantitative, and Breadth Requirements
Students admitted to Simon Fraser University beginning in the fall 2006 term must meet writing, quantitative and breadth requirements as part of any degree program they may undertake. See Writing, Quantitative, and Breadth Requirements for universitywide information.
WQB Graduation Requirements
A grade of C or better is required to earn W, Q or B credit
Requirement 
Units 
Notes  
W  Writing 
6 
Must include at least one upper division course, taken at Simon Fraser University within the student’s major subject  
Q  Quantitative 
6 
Q courses may be lower or upper division  
B  Breadth 
18 
Designated Breadth  Must be outside the student’s major subject, and may be lower or upper division 6 units Social Sciences: BSoc 6 units Humanities: BHum 6 units Sciences: BSci 
6 
Additional Breadth  6 units outside the student’s major subject (may or may not be Bdesignated courses, and will likely help fulfil individual degree program requirements) Students choosing to complete a joint major, joint honours, double major, two extended minors, an extended minor and a minor, or two minors may satisfy the breadth requirements (designated or not designated) with courses completed in either one or both program areas. 
Residency Requirements and Transfer Credit
 At least half of the program's total units must be earned through Simon Fraser University study.
 At least two thirds of the program's total upper division units must be earned through Simon Fraser University study.