Events

Title: The Douglas-Rachford splitting algorithm for inconsistent minimization problems

Abstract:

The Douglas--Rachford (DR) method is one of the most popular splitting methods in optimization. The method was first introduced in 1956 to numerically solve certain types of heat equations.

Title: Robust counterpart approximations of scalar chance constraints

Abstract:

We will cover section 2.1, section 2.2 and part of section 2.3 of the book Robust Optimization by Ben-Tal et al.

Title: On Pretty Good State Transfer, Entanglement, and Spin Chains

Abstract: 

We discuss the Vieira and Rigolin paper “Almost perfect transport of an entangled two-qubit state through a spin chain”,

Title: Polynomial systems: Graphical structure, Geometry, and Applications

Abstract:

Various problems in areas such as robotics, power systems, computer vision, cryptography, and chemical reaction networks, can be modeled by systems of polynomial equations, and in many cases the resulting systems have a simple sparsity structure.

Title: ALBANIS: A brief overview of Lattice-Based NIST Submissions

Abstract:

Now that the NIST competition is in the first round of the review process, it is our turn to take a look at the submissions (at least, briefly).

Title: Algorithms and complexity for quantum advantage

Abstract:

There is strong evidence that a sufficiently large fault-tolerant quantum computer would solve certain computational problems exponentially faster than any classical computer. How can quantum algorithms and complexity theory help guide the way forward in our current era of small and noisy quantum computers?

Title: An Introduction to Quantum Graphs, Chromatic Numbers and Lovász Inequalties

Abstract:

Quantum graph theory, also known as non-commutative graph theory, is an operator system generalization of graph theory. Quantum graphs were first used to extend the notion of one-shot-zero-error capacity of a "Noisy Channel" to "Quantum Channels". 

Title: Robust Convex Optimization 

Abstract:

We continue our study of convex optimization problems with uncertain data by discussing the paper by Ben-Tal and Nemirovski, 'Robust Convex Optimization'.

Title: Constructing Graphs Pseudo-Similar Vertices

Abstract:

Let G be a graph. Let a and b be vertices in G, then a and b are pseudo-similar if G\a is isomorphic to G\b, but there's no automorphism of G that maps a onto b.

Title: An introduction to vertex minors

Abstract:

This introductory lecture on vertex minors of graphs will highlight the similarities and differences with minors of graphs. We will also discuss the main conjectures relating to vertex minors.