Dr Yannic Rath is a Higher Scientist in the Quantum Technologies Department (Quantum Computing Circuits group) working on the development of computational techniques to uncover, describe and ultimately harness quantum physical phenomena. His main focus is the development of trustworthy machine learning frameworks as novel tools to tackle open challenges within computational quantum science.
Research Interests
Biography
Prior to joining NPL in late 2023, Yannic worked as a post-doctoral research associate and as a PhD student in the Theory and Simulation of Condensed Matter Systems group with Prof. George Booth at King’s College London (2018 – 2023). Yannic also holds an MSc in Physics with extended research from Imperial College London (2018), as well as two BSc degrees in both Physics and Computer Science (both obtained from Leibniz University Hannover, Germany – awarded in 2014 and 2016 respectively).
Research Highlights
As part of his PhD, recognised with the 2023 King’s College outstanding thesis prize, Yannic co-developed the framework of Gaussian Process States. Building upon Bayesian machine learning techniques, this toolkit provides novel computational capabilities for the efficient simulation of quantum systems. This includes the description of quantum phenomena underpinning the behaviour of chemical systems – one of the central areas of interest in Yannic’s work. As part of this effort, Yannic has recently introduced a novel framework for a practical application of wavefunction descriptions for high accuracy molecular dynamics simulations. Furthermore, he is one of the main developers of the ALSM scheme, significantly reducing measurement requirements for the characterization of quantum metrological devices with machine learning.
A list of Yannic’s publications can be found on Google Scholar.
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