The official source of material for this course is the syllabus page, this page will be a source of material for the course.

To give you a brief idea of what you can expect to be able to do at the end of the course here are the Intended Learning Outcomes:

UEQ: Feedback on feedback

I have made a few comments on the feedback you have given me and the course. One person wrote "Really, I never knew proofs get this long." I'm sorry, there is little I can do about this, it is the nature of the beast. If you stay on into the fourth year why not take my course on Analytic Number Theory, where we take half the course to prove the Prime Number Theorem.

Feedback on UEQs

Coursework Test 2017-18

The coursework test will be on Thursday, 15th March at 11.00am in Simon Theatre B. Details will be released a week before the test.

The Timetable 2017-18

  9.00 10.00 11.00 12.00 1.00 2.00 3.00 4.00 5.00
Monday    
  Feedback Tutorial
Zochonis B26
       
Tuesday     Lecture
Simon C
Feedback Tutorial
Samuel Alexander
A116
         
Wednesday                  
Thursday   Feedback Tutorial
Humanities Bridge St
Hanson Room
Lecture
Simon C
           
Friday                  

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Past & Present exam papers

Exam Papers Solutions and
Feedback
June 2015 2015 Solutions
June 2016 2016 Solutions 2016 Feedback
June 2017 2017 solutions & Feedback

Lecture Notes

I am making all the material available before the course starts. I am trusting that students will not use this as an excuse to not attend lectures but come along to see the material developed and explained in the lectures.

Notes Contents
1. Continuity Functions of Several Variables: Notation; Limits of vector-valued functions; Scalar-valued examples; Sandwich Rule; Vector-valued examples; Limit Laws; Directional limits; Limits along curves; Continuity of vector-valued functions; Continuity Laws; Composition Laws.
1. Appendix Appendix Uniqueness of Limit; Example of Limit; Sandwich Rule; Composition Results.
2. Differentiation Differentiation of functions of several variables: Directional derivatives; Partial Derivatives; Differentiable implies Continuous I; Vector-valued Linear Functions; Scalar-valued Linear Functions; Fréchet Derivative; Best Affine Approximation; Differentiable implies Continuous II; Derivative exists implies directional derivative exists; Jacobian Matrix; Special case: Gradient vector; Jacobian Matrix revisited; Use of the Jacobian matrix; When is a function differentiable?; Examples; Product and Quotient functions; Rules for differentiation; The Chain Rule; The Chain Rule: Special cases; Products and Quotients of Scalar-valued functions; the Inverse function.
2. Appendix Appendix Partial and directional derivatives; Directional derivative implies directional continuity; Bounds on Linear maps; Derivative is unique; the Best Affine Approximation is unique; Mean Value Theorem; Differentiable does not implies C1; Earlier example revisited; Rules of Differentiation.
3. Surfaces Surfaces and the Implicit Function Theorem: Surfaces; a graph as a surface; An Image set as a surface: parametric description; A Level set as a surface: Implicit description; Level sets are graphs (locally): Implicit Function Theorem; Parametric sets are graphs (locally): Inverse Function Theorem; Manifolds; Tangent Spaces and Planes; Tangent Space for a graph; Tangent Space for an Parametric set; Tangent Space for a Level Set;
3. Appendix Appendix on Surfaces Full Rank; Jacobian matrix of a graph written as an image set; Jacobian matrix of a graph written as a level set; Surface of a unit ball in R3; Why did I define a surface as a graph in the way I did?; Permuting the coordinate functions in a parametric set; permuting the variables in a level set; Tangent Space for a Parametric set; Surfaces as level sets f-1(0). Which f?; Definition of Tangent Plane; Background Linear Algebra; Tangent Space for a Parametric Set; Tangent Space for a Level Set; Proof of the Inverse Function Theorem.
3. Tangent Spaces Appendix on Tangent Spaces Tangent Spaces for a surface in R3 with illustrations.
4. Implicit Function Theorem Proof of the Implicit Function Theorem: by Induction.
5. ExtremAl Values Extremal Values: Extremal Values and Lagrange multipliers;
5. Appendix Appendix Examples including the GM-AM inequality & the Cauchy-Schwarz inequality along with their extensions.
6. Forms and Integration Differential forms and their integration: Differential 1-forms; Exact 1-forms; higher-order derivatives; Closed 1-forms; line integrals; Differential 2-forms; Surface integrals; Products of 1-forms; Derivatives of 1-forms; Stoke's Theorem (statement of); Green's Theorem (statement of); These later topics will only be covered if there is time: Differentiable k-forms; products and derivatives of k-forms; integration of a k-form over a manifold.
6. Appendix Appendix Projections are linearly independent; Second derivatives need not be equal; motivation for the definition of a 2-form; Proof of Stoke's Theorem; Vector fields; A basis for k-forms.

Here are some additional notes I have typed up. They might help you as background, but they are not examinable.

Notes Contents
Higher Order Derivatives Higher Order Derivatives: Higher order partial derivatives; The Hessian Matrix.
Taylor Series Taylor Series Best Linear and Quadratic Approximations; estimates on the errors of such approximations.

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Problem and Solution Sheets

Question Sheets

In the nine question sheets there are a total of 95 questions with 54 additional questions. These questions reinforce the material in the lectures.

Question Sheet 1
Limits
Question Sheet 2
Continuity
Question Sheet 3
The Directional Derivative
Question Sheet 4
The Frechet Derivative I
Question Sheet 5
The Frechet Derivative II
Question Sheet 6
The Implicit & Inverse Functions
Question Sheet 7
Tangent Spaces & Planes
Question Sheet 8
Lagrange's Method
Question Sheet 9
Differential Forms

Solution Sheets

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Background Notes

Analysis

A very good knowledge of the results and methods of real analysis, as found in MATH20101 or MATH20111, is required. The present course will take results from those courses, such as the Inverse Function Theorem, and generalise them to vector valued functions of severable variables.

Linear Algebra

I expect you remember the ideas and results of Linear Algebra found in MATH10202 and MATH10212, such as linear maps being represented by matrices, vector spaces and their bases. I will also rely on results not found there, such as the Spectral Theorem for Symmetric matrices. I would advise you to research this result, though appropriate notes will be given.

Recommended Texts

Reading List for MATH20132.