Applied and Computational Mathematics

Program Description

Research interests of the members cover several closely connected areas which include dynamical systems and delay equations; physics of fluids and continua; material sciences; phase transitions and crystal growth; numerical methods in fluid dynamics and asymptotic analysis; shape and structural optimization; control of partial differential equations.

Two research centers are affiliated with the group:

Program Members

Academic Program

The objective of this program is a training in modern mathematics aimed at applications and in the use of computers as a tool in the analysis, optimization, and control of physical and technological systems. It welcomes strong graduate students with a variety of backgrounds (ranging from the physical sciences and engineering to mathematics) wishing to work in partial differential equations and their applications. The program is sufficiently broad to accomodate software development and physical modelling as well as topics requiring delicate techniques in functional analysis or partial differential equations.

It is intended to offer students the possibility of collaborative contact with several local government and industrial research groups such as the Canadian Space Agency and a variety of other organisations with which members of the group have been involved at various times.

The program covers several closely connected areas which include:

  • Dynamical systems and delay equations.
  • Physics of fluids and continua.
  • Material sciences; phase transitions and crystal growth.
  • Numerical methods in fluid dynamics and asymptotic analysis.
  • Shape and structural optimization.
  • Control of partial differential equations.

There are no formal programmatic requirements beyond the departmental requirements. However the following guidelines should be followed and courses must be selected in consultation with an adviser from the group.

  1. All students should take courses in partial differential equations: appropriate courses are MATH 580 and MATH 581 at McGill and MAT 6110 at U de M.
  2. It is essential that most (and desirable that all) students develop their computational skills by taking appropriate courses in numerical analysis. Beyond the introductory courses, generally at an undergraduate level, the essential courses cover computational mathematics (MATH 578 at McGill and MAT6470 at U de M) numerical differential equations (MATH 579 at McGill) finite difference methods (MAT 6165 at U de M) and finite element methods (MTH 6206/7 at Polytechnique and MAT6450 at U de M).
  3. Students should develop an understanding of neighbouring areas of physics such as fluids and continuum mechanics, thermodynamics, etc. Suitable courses include MATH 555 at McGill and MAT 6150 at U de M; other useful courses can be found in Physics or Engineering departments.
  4. Students involved in fluid mechanics or material sciences should take a course on asymptotic and perturbation methods: MATH 651 at McGill or MTH 6506 at Polytechnique.
  5. Students in shape optimization or control should take at least one course in optimization. The following courses are available: MATH 560 at McGill, MAT 6428, MAT 6439 (Optimisation et contrôle), MAT 6441 (Analyse et optimisation de forme) at U de M; MTH 6403 and MTH 6408 at Polytechnique.
  6. Students who wish to work on shape optimization or the control of distributed parameter systems will need to develop a strong background in real analysis and functional analysis.

We expect that future elaboration and formalization of this program will occur within the framework described above which allows also for the introduction of additional areas under the broad umbrella of the program title.

2023-24 Course Listings


Honours Linear Optimization

Honours level introduction to linear optimization and its applications: duality theory, fundamental theorem, sensitivity analysis, convexity, simplex algorithm, interior point methods, quadratic optimization, applications in game theory.

Prof. Tim Hoheisel

MATH 517

Institution: McGill University

Numerical Analysis 1

Development, analysis and effective use of numerical methods to solve problems arising in applications. Topics include direct and iterative methods for the solution of linear equations (including preconditioning), eigenvalue problems, interpolation, approximation, quadrature, solution of nonlinear systems.

Prof. Jean-Philippe Lessard

MATH 578

Institution: McGill University

Advanced Partial Differential Equations 1

Classification and wellposedness of linear and nonlinear partial differential equations; energy methods; Dirichlet principle. Brief introduction to distributions; weak derivatives. Fundamental solutions and Green's functions for Poisson equation, regularity, harmonic functions, maximum principle. Representation formulae for solutions of heat and wave equations, Duhamel's principle. Method of Characteristics, scalar conservation laws, shocks.

Prof. Jérôme Vétois

MATH 580

Institution: McGill University

Modélisation mathématique et applications

Processus de modélisation mathématiques avancés : simulations, estimation de paramètres, interprétation. Utilisation des mathématiques dans un milieu multidisciplinaire (p. ex. oncologie, neurosciences, génétique). Étude de cas et projets appliqués.

Prof. Morgan Craig

MAT 6465

Institution: Université de Montréal

Analyse géométrique des données

Formulation et modélisation analytique des géométries intrinsèques de données. Algorithmes pour les construire et les utiliser en apprentissage automatique. Applications : classification, regroupement et réduction de la dimensionnalité.

Prof. Guy Wolf

MAT 6493

Institution: Université de Montréal

Mathématiques pour l’intelligence artificielle

Notions fondamentales de probabilités appliquées à divers domaines de l’intelligence artificielle. Réseaux bayésiens, champs markoviens, diverses méthodes d’inférence (variationnelle, par maximum a posteriori, recuit simulé, etc.), échantillonnage et méthodes de Monte Carlo par chaînes de Markov, séries chronologiques, partitionnement spectral et modèles à variables latentes. Applications en imagerie, en analyse de textes et sur les réseaux de neurones.

Prof. Félix Camirand-Lemyre

STT 760

Institution: Université de Sherbrooke


Topics in Analysis: Nonsmooth Analysis and applications

This course provides an introduction to Nonsmooth Analysis, beginning with proximal calculus, featuring proximal normals, subgradients, and generalizations of ordinary rules of calculus.   Some specializations to classical Convex Analysis are given, and various types of tangency are studied.   A main application is to nonsmooth constrained optimization.   

 The course reference is "Nonsmooth Analysis and Control Theory" by F.H. Clarke, Yu. S. Ledyaev, R.J. Stern and P.R. Wolenski--Graduate Texts in Mathematics (173), Springer, 1998.   (A pdf of this book will be made available.)  

Prof. Ron Stern

MAST 661-O (837-O)

Institution: Concordia University

Algorithmic Game Theory

Foundations of game theory. Computation aspects of equilibria. Theory of auctions and modern auction design. General equilibrium theory and welfare economics. Algorithmic mechanism design. Dynamic games.

Prof. Adrian Vetta

MATH 553

Institution: McGill University

Honours Convex Optimization

Convex sets and functions, subdifferential calculus, conjugate functions, Fenchel duality, proximal calculus. Subgradient methods, proximal-based methods. Conditional gradient method, ADMM. Applications including data classification, network-flow problems, image processing, convex feasibility problems, DC optimization, sparse optimization, and compressed sensing.

Prof. Courtney Paquette

MATH 563

Institution: McGill University

Numerical Differential Equations

Numerical solution of initial and boundary value problems in science and engineering: ordinary differential equations; partial differential equations of elliptic, parabolic and hyperbolic type. Topics include Runge Kutta and linear multistep methods, adaptivity, finite elements, finite differences, finite volumes, spectral methods.

Prof. Gantumur Tsogtgerel

MATH 579

Institution: McGill University

Systèmes dynamiques

Flots discrets et continus. Équations différentielles non linéaires, techniques classiques d’analyse de dynamique, existence et stabilité de solutions, variétés invariantes, bifurcations, formes normales, systèmes chaotiques. Applications moderne.

Prof. Guillaume Lajoie

MAT 6215

Institution: Université de Montréal

Mathématiques biologiques

Examen de modèles fondamentaux utilisés en biologie mathématique et de leur analyse utilisant des outils modernes de calcul scientifique. Systèmes dynamiques discrets et continus, procédés stochastiques, modèles statistiques et simulation numérique. Enquête des publications récentes en biologie mathématique par journal club.

Prof. Morgan Craig

MAT 6463

Institution: Université de Montréal

Calcul scientifique

Virgule flottante. ÉDOs. Méthodes directes et itératives pour la résolution de systèmes linéaires et non-linéaires. Valeurs propres. ÉDPs elliptiques et paraboliques. Équation de Black-Scholes. Optimisation sans contraintes (MAT 6473 uniquement), Décomposition en valeurs singulières (SVD, MAT 6473 uniquement).

Prof. Robert G. Owens

MAT 6470 (3 crédits) / MAT 6473 (4 crédits)

Institution: Université de Montréal