Operator Algebraic Tools in Quantum Information Theory 
 
 
 

Time:  Tuesday 4-5.30 pm        Wednesday 4-5.30 pm

Location:  03.06.011/ 02.10.011 

Instructor: Marius Junge     

Course description
:


The focus of this course lies in information theoretical foundations based on common tools from functional analysis. The major gools are on entropic inequatities including
   SSA
   Data processing
   Recovery
   Additivity of squashed entanglement
   Decay for semigroups
   

Lectures

Quantum mechanics and simple norms

Entropy, weak typicality, and channels

Relative entropy, minimal output entropy for classical channel

Interpolation

Classical Data processing inequality

Conditional expectations



Impartant concepts in mathematics have been developped to understand solutions, and solutions spaces of certain PDE's. This allows to classify and treat certain classes of PDE's. Fourier analysis is one the most of important of these theories. In this sense this couse is also a first step towards mathematics on the graduate level.

 
 


Plan:

I: Basics on PDE's

What is a PDE? Linear PDE's,  characteristic curves and lines,
well-posedness.


II Wave equation 

How to find a solution in 1D? causality, solution formulae, reflection principle,  inhomogenous problem (3.3-3.4),  well-posedness.
Duhamel

III Fourier analysis

Hilbert spaces and inner products,  abstract Fourier coefficients, concrete Fourier coefficients,  different form of convergence, Gibbs phenomena, a little peek at continuous Fourier coefficients.

IV Heat equation

Solution formulae, reflection, source, well-posedness.

V Boundary problems in 1D

separation of variables.

VI Laplace equation

The equation, rectangles and cubes, Poisson formula

VII Boundary problems in plane and space

solid virbration, Legendre functions.

wave equation
Books:
Walter A. Strauss, Partial Differential Equations, An Introduction, Second edition


Link to lectures


Attendance: If you miss the class more than three times unexcused, you may be dropped! It is you task to drop the class in time, and make space who actually need the class.  If I can not recognize a student, he will not be handed out  an exam.

Grading:
Homework   (20%)

Midterm1   January 31  (25%)
Midterm2   February 28   (25%)

Final  (
7:00-10:00 p.m., Wednesday, May 9)   (30%)

Practice probems

Practice probems solutions

Exam1

Practice problems2

Practice problems2-solutions


Practice problems final

Practice problems final solutions


hw1
hw2
hw3
hw4
hw5
hw6
hw7
hw8
hw9
hw10
hw11
hw12




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