4 Minute read
This research is comprised of two distinct, but related projects. KU Leuven is the home institution for one project and the University of Melbourne will host the second.
The details - KU Leuven
Project aims:
- To describe the topology of the droplets and their motherbodies, their evolution in terms of parameters and to study phase transitions.
- Analyse models in great detail with tools from integrable probability and asymptotic analysis
Non-Hermitian matrices have their eigenvalues in the complex plane. For random non-Hermitian matrices, the typical behaviour is that the complex eigenvalues behave as mutually repelling charged particles, like electrons in a trap that accumulate on a region in the complex plane, known as the droplet. In the simplest cases, the droplet is a disk.
The research project studies deformations that lead to more complicated droplets. The average characteristic polynomial in these models will be a polynomial with orthogonality in the complex plane. The zeros of these polynomials typically accumulate along certain contours within the droplet, called a motherbody.
The graduate researcher on this project is: Sampad Lahiry
Supervision team - KU Leuven
Principal Investigators (PIs):
KU Leuven: Professor Dr Arno Kuijlaars
The University of Melbourne: Dr Mario Kieburg
Co-Principal Investigators (Co-PIs):
The University of Melbourne: Professor Peter Forrester
The details - The University of Melbourne
Project aims:
- The ultimate goal of this project is to find novel universal correlations between eigenvalues and singular values.
- To achieve this, the graduate researcher will apply techniques from harmonic analysis on matrix spaces, bi-orthogonal functions and asymptotic analysis
Non-Hermitan linear operators describe a multitude of systems like open scattering systems in physics or the signal transmission in wireless telecommunications. Such operators can be characterised either by their eigenvalues or their singular values.
In this project, the long-standing problem of their relation will be addressed for a specific class of random matrices with the goal to revealing universal correlations between these two sets of quantities.
We aim for the computation of the joint level densities of the eigenvalues and singular values at finite matrix dimension. A well-known relation, called the Haagerup-Larson theorem, for infinite dimensional matrices shall be re-derived and its corrections for finite matrix dimensions will be quantified. Furthermore, two simple deformations of the probability density of the random matrix will be investigated in this context, too.
The first deformation introduces holes in the complex spectrum and makes contact with the Leuven-based project. The second kind of deformation squeezes the originally isotropic spectrum to an elongated shape. Both kinds of deformations are encountered in quantum field theoretical applications.
The graduate researcher on this project is: Matthias Allard
Supervision team - The University of Melbourne
Principal Investigators (PIs):
The University of Melbourne: Dr Mario Kieburg
KU Leuven: Professor Dr Arno Kuijlaars
Co-Principal Investigators (Co-PIs):
The University of Melbourne: Professor Peter Forrester
First published on 26 August 2022.
Share this article
Other joint PhD projects
-
Effective translation policies for official communication in diverse communities
This project looks at translation policies in Brussels and Melbourne. It will propose guidelines for effective multilingual communication in linguistically superdiverse cities.
-
Subcellular Ca2+ signalling microdomains regulating cardiomyocyte growth and function
This project will examine how calcium can act in a selective manner to precisely control heart muscle cell growth and gene expression.
-
Soil-structure interaction framework for offshore foundations in sand under cyclic loading
Two paired projects researching soil-structure interaction frameworks for offshore foundations.
-
Trustworthy and insightful algorithms for industrial decision making
This project will use state-of-the-art optimisation technologies in the form of mathematical models and algorithms to find optimal solutions for industry.