Course 2024-2025 a.y.

30552 - ADVANCED ANALYSIS AND OPTIMIZATION - MODULE 2

Department of Decision Sciences

Course taught in English
code 30552 anche the code 30551 ‘Advanced Analysis and Optimization - Module 1’ are respectively the first and the second module of the course code 30550 ‘Advanced Analysis and Optimization

Student consultation hours
Class timetable
Exam timetable
Go to class group/s: 27
BAI (5 credits - II sem. - OB  |  MAT/05)
Course Director:
ALESSANDRO PIGATI

Classes: 27 (II sem.)
Instructors:
Class 27: ALESSANDRO PIGATI


Suggested background knowledge

For a fruitful and effective learning experience, it is recommended to be fluent with multivariable calculus (limits, partial derivatives, integrals) and basic linear algebra (vector spaces, linear maps, change of basis, diagonalization).

Mission & Content Summary

MISSION

The purpose of this course is to present the foundations of complex analysis in one variable and differential geometry. Both subjects are deeply intertwined with algebraic topology, and thus this will also be the occasion to introduce basic notions such as the fundamental group, covering spaces, and some degree theory. Specifically, the goal of the first half is to have a solid understanding of holomorphic functions on the plane and their representation through a power series or through Cauchy's formula, touching on subjects like homotopic curves, covering spaces, residues, Fourier series, and harmonic functions on the plane. In the second half, we will develop the theory of differentiable manifolds in the Euclidean space and their relation with smooth non-convex optimization, presenting also the Lagrange multiplier principle and its applications. We will then introduce Riemannian metrics and geodesics and we will state some important classical results in Riemannian geometry, as well as differential forms and basic results of degree theory, with applications such as the existence of Nash equilibria in game theory. Some parts are fundamental in any program involving mathematical and computing sciences: the theory and applications encountered in this course will create a strong foundation to master complex analysis, understand the geometry of the plane and arbitrary manifolds, and solve constrained optimization problems appearing in real-world models.

CONTENT SUMMARY

  • Complex analysis:
    • Complex numbers and Euler's formula
    • Holomorphic functions and Cauchy's integral theorem for basic curves
    • Homotopy between loops and fundamental group
    • Cauchy's integral formula
    • Power series representation
    • Relation to Fourier series and harmonic functions
    • Special holomorphic functions such as exp and log
    • Poles and residues
    • Applications of residues to compute particular integrals
    • If time allows: covering spaces, ramified coverings, Riemann surfaces

 

  • Basics of differential geometry:
    • Inverse and implicit function theorem
    • Equivalent definitions of embedded differentiable manifolds
    • Tangent space and differential of smooth maps between manifolds
    • Constrained optimization: Lagrange multipliers
    • Multilinear alternating forms and differential forms
    • Stokes' theorem (statement)
    • Riemannian metrics and geodesics
    • Exponential map and characterizations of failure of injectivity (statement)
    • Completeness and Hopf-Rinow theorem (statement)
    • If time allows: basic notions of curvature and classical results relating geodesics, curvature, and topology (statements)

 

  • Degree theory:
    • Definition of degree of smooth maps between manifolds
    • Invariance under smooth homotopies and independence on the codomain point
    • Characterization using volume forms (statement)
    • Brouwer's fixed-point theorem
    • Applications to topology and Nash equilibria in game theory

Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Know and apply fundamental notions in complex analysis: holomorphic functions, Cauchy's integral formula, power series, calculus of residues
  • Know and apply fundamental notions in differential geometry: concrete examples of manifolds, parametrization, tangent space, differential of maps, metrics, geodesics, differential forms, Stokes' theorem
  • Solve constrained optimization problems using Lagrange multipliers
  • Understand degree theory and its topological applications such as Brouwer's fixed-point theorem

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Apply the calculus of residues in simple settings
  • Solve constrained optimization problems in simple settings
  • Operate with objects and tools from complex analysis and differential geometry
  • Make use of the presented methodological tools in applied sciences such as computer science and physics

Teaching methods

  • Lectures
  • Practical Exercises
  • Individual works / Assignments

DETAILS

Online lectures have the same conceptual role as face-to-face lectures. The actual choice between offering face-to-face lectures, online lectures, or both will depend on the university's policies.

 

Exercise sessions (again: both face-to face and online) are dedicated to the application of the main theoretical results obtained during lectures to problems and exercises of various nature.


Assessment methods

  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  x x

ATTENDING AND NOT ATTENDING STUDENTS

Students will be evaluated on the basis of written exams, which can be taken in one of the two following ways. 


The exam can be split into two partial exams. Each partial may contain multiple-choice questions and open-answer questions; each partial weighs for one-half of the final mark. Multiple-choice questions mainly aim at evaluating the knowledge of the fundamental mathematical notions and the ability to apply these notions to the solution of simple problems and exercises, while open-answer questions mainly aim at evaluating: 

  • The ability to articulate the knowledge of mathematical notions in a conceptually and formally correct way, adequately using definitions, theorems and proofs.
  • The ability to actively search for deductive ideas that are fit to prove possible links between the properties of mathematical objects. 
  • The ability to apply mathematical notions to the solution of more complex problems and exercises.

 

The exam can also be taken as a single general exam, which contains both multiple-choice questions and open-answer questions. The general exam covers the whole syllabus of the course and it can be taken in one of the four general sessions scheduled in the academic year. This option is mainly meant for students who have withdrawn from the two-partials procedure or could not follow it. Each type of question contributes in a specific way to the assessment of the students' acquired knowledge. Multiple-choice questions mainly aim at evaluating the knowledge of the fundamental mathematical notions and the ability to apply these notions to the solution of simple problems and exercises, while open-answer questions mainly aim at evaluating: 

  • The ability to articulate the knowledge of mathematical notions in a conceptually and formally correct way, adequately using definitions, theorems and proofs.
  • The ability to actively search for deductive ideas that are fit to prove possible links between the properties of mathematical objects. 
  • The ability to apply mathematical notions to the solution of more complex problems and exercises.

 
We will take care to obtain final grades whose distribution follows the grade distribution that is recommended by Università Bocconi.
 


Teaching materials


ATTENDING AND NOT ATTENDING STUDENTS

  • Lecture notes (main reference, updated regularly on Blackboard)
     
  • Needham, Tristan. Visual complex analysis. Clarendon Press (new edition), 1999. ISBN: 978-0-1985-3446-4
     
  • Giaquinta, Mariano;  Modica, Giuseppe. Mathematical analysis. An Introduction to functions of several variables.
    Birkhäuser Boston, Inc., Boston, MA,  2009. ISBN: 978-0-8176-4374-4
Last change 20/11/2024 23:57