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Wednesday 5:00-6:00 BA3008, Thursday 5:00-6:00 BA 6183 and Friday 2:00-3:00 BA3008
This course concentrates on partial differential equations appearing in physics, material sciences, biology, geometry, and engineering. It deals with evolution equations, mostly nonlinear, and addresses the questions of:
To deal with these questions, the course will develop some key mathematical techniques, like:
The following list gives an idea of the equations considered in this course:
Link to course description for more information.
Link to course notes.
Wednesday 3:00-4:00 BA1170, Thursday 4:00-5:00 BA 6183 and Friday 6:00-7:00 BA1170
The goal of this course is to explain key concepts of Quantum Mechanics and to arrive quickly to some topics which are at the forefront of active research. Examples of the latter topics are Bose-Einstein condensation and quantum information, both of which have witnessed an explosion of research in the last decade and both involve deep and beautiful mathematics.
Prerequisites for this course: I will cover all necessary definitions beyond multivariable calculus and linear algebra, but without familiarity with elementary ordinary and partial differential equations, the course will be tough. Knowledge of elementary theory of functions and operators would be helpful. No physics background is required.
S. Gustafson and I. M. Sigal, Mathematical Concepts of Quantum Mechanics, Springer
In covering information theory we will follow on-line material and papers.
Link to Course Description
In this course, we consider key partial differential equations of the first and second order and develop some basic techniques in showing existence, uniqueness and smoothness of their solutions. Specifically, we consider the transport, Laplace, heat and wave equations. These equations are important in mathematics and in applications, relevant to current research and the techniques needed to analyze these equations play the central role in PDEs and beyond.
R. McOwen, Partial Differential Equations, 2nd edition, Prentice-Hall, 2003
Much of the material we cover could also be found in
L.C. Evans, Partial Differential Equations, AMS
ETH Hönggerberg, Zürich
In this course we cover several fundamental equations of quantum physics: the Schrödinger equation, which lies at the foundation of Quantum Mechanics, the Gross-Pitaevskii, Landau-Lifshitz and Hartree and Hartree-Fock equations playing an important role in condensed matter physics, the Ginzburg-Landau equations of superconductivity, and the Yang-Mills equations of particle physics.
In this course we develop some basic techniques in solving partial differential equations and analyzing their solutions. The long term goal is to understand principal evolution equations. We establish an existence theory for the selected class of equations, describe their key properties, isolate their most important solutions and study stability or instability of these solutions. Some of non-evolution equations appear as static equations for the evolution ones. Given the time constraint, we have to be very selective about the equations we consider. The guiding principles are the importance of the equations in mathematics and in applications, relevance to the current research and the central role of the techniques needed to analyze these equations.
In this course we will study mean curvature, Ricci and harmonic map flows. We also plan to describe the curvature flow of networks of plane curves. We will give careful definitions of these flows, present existence results and results on formation of singularities (e.g. collapse to a point and neck-pinching) and soliton dynamics. We will also introduce main techniques, such as parabolic existence theory, maximum principles and monotonicity (entropy) formulae.
We will explain all needed notions from Differential Geometry and Partial Differential Equations, but knowledge of these subjects on an introductory level is required for this course
Prerequisites for this course:
Differential Geometry of Curves and Surfaces; Elementary PDEs
References for the course:
K.Ecker, Regularity theory for mean curvature flow , Birkhaeuser, 2004; ISBN 08 176 32433
P.Topping, Lectures on the Ricci flow , London math society lecture notes series 325, Cambridge Univ Press, 2006; ISBN 0-521-68947-3. (The book can be downloaded from the webpage of Prof. Peter Topping)
The goal of this course is to explain key concepts of Real Analysis with the view at applications. The course is about the same level as MAT357, but while MAT357 deals mainly with theory, the present course aims at developing interesting applications.
Kenneth R. Davidson and Allan P. Donsig, Real Analysis and Applications, Springer, 2010.
The goal of this course is to explain key concepts of Quantum Field Theory and to arrive quickly to some topics which are at the forefront of active research. We will aim at physically relevant and mathematically interesting theories. We will try to be as self-contained as possible and rigorous whenever the rigour is instructive. Whenever the rigorous treatment is prohibitively time-consuming we give an idea of the proof, if such exists, and/or explain the mathematics involved without providing all the details.
Prerequisites for this course: The course will concentrate on mathematical foundations of Quantum Field Theory. No serious knowledge of physics is necessary for this course. What is needed are the mathematical foundations of Quantum Mechanics, as e.g. in APM421HF Mathematical Concepts in Quantum Mechanics course. The latter include Functional Analysis, Partial Differential Equations and Probability, all on an elementary level. At the end of the course I plan to use some geometrical and topological techniques.
K. Huang, Quantum Field Theory: From Operators to Path Integrals, John Wiley, New York, 1998. ISBN 0-471-14120-8
We will also use S. Gustafson and I. M. Sigal, Mathematical Concepts of Quantum Mechanics, 2nd edition, Springer, 2005
In this course we discuss two key groups of biological models which were intensively studied in the last few years. The first group deals with collective behaviour of interacting biological organisms such as cells and bacteria (e.g. chemotaxis). The goal here is to describe such phenomena as aggregation (congregation of cells or bacteria into tightly bound, rigid colonies) and developmental pattern formation.
The second group of models deals with mechanisms through which networks of interacting biomolecules (proteins or genes) carry out the essential functions in living cells. Among the questions which are addressed here is how the genetic and biochemical networks withstand considerable variations and random perturbations of biochemical parameters. The complexity and high inter-connectedness of these networks makes the question of the stability in their functioning of special importance.
Finally we will discuss mathematical models of the dynamics of HIV-1 and of cancer growth.
The models above are expressed in terms of Markov chains and stochastic ordinary differential equations. In addition, in the first case, reaction-diffusion equations (e.g. Keller-Segel equations) and stochastic particle dynamics are used. This mathematical background together with its biological interpretation will .be developed in the course.
Prerequisites for this course: some familiarity with elementary ordinary and partial differential equations and elementary probability theory. No knowledge of biology is required.
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Page last updated: September 2017