Matt studied Theoretical Physics at the University of York, graduating in 2012 with first-class honours. He obtained his PhD under the supervision of Prof. Rex Godby, specialising in many-body quantum theory. His thesis, Electrons in Model Nanostructures
, received the K. M. Stott Prize for excellence in scientific research.
Matt conducted postdoctoral research at the Max Planck Institute of Microstructure Physics in Germany with Prof. Eberhard Gross and at Durham University in the group of Dr Nikitas Gidopoulos, where he contributed to the development of fundamental theories within many-body quantum mechanics and condensed matter physics.
Currently, Matt is a lecturer at the University of York, where he teaches courses in mathematics and theoretical physics. He has authored numerous academic papers in leading journals and written articles on artificial intelligence for the Institute of Physics. Matt regularly presents his research at international conferences and is a member of both the Engineering and Physical Sciences Research Council (EPSRC) Peer Review College and the European Theoretical Spectroscopy Facility (ETSF).
Matt's research focuses on the fundamentals of quantum theory and its application to modelling the electron excitation properties of materials. His contributions to his field include the authorship of the iDEA code, a comprehensive Python software library for exploring and understanding many‑body quantum mechanics, fundamental insights into the calculation of excited electron states with density functional theory, and the development of a method for accurately simulating many‑electron real‑time dynamics.
Kohn and Sham's approach to density functional theory is the most popular method in materials science; however, it is notoriously unreliable for calculating electron excitation properties.
Modelling the response of electrons to an applied electric field remains a challenge; yet determining the flow of charge through a material is crucial for the design of integrated circuits.
Many-body perturbation theory is commonly used to calculate the spectral function; however, increasing the accuracy of this approach is challenging owing to the computational cost.