Thomas E. Baker
Theoretical Quantum Information, Condensed Matter, and Quantum Chemistry
Tensor networks, quantum computing, topological physics, computational methods, quantum error correction, superconductivity, magnetism, proximity effects, superconducting-circuit quantum electrodynamics, density functional theory, density matrix renormalization group, Monte Carlo
Hello!(Bonjour!)
I am a Canada Research Chair in Quantum Computing for Modeling of Molecules and Materials at the University of Victoria. I am in the Department of Physics & Astronomy and also the Department of Chemistry.
I was most recently at the University of York in the United Kingdom on a Fulbright scholarship, funded by the Bureau of Educational and Cultural Affairs of the United States Department of State. If you are located in the UK and interested in talking, please send me a message.
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About me:
My experience has taken me to a variety of theoretical physics topics from classical physics to density functional theory and quantum computing. I often use tensor networks as a computational tool and have made my own library.
My very first research project was on constructing PVC drifter units and measuring the currents in Avila Bay, California with GPS. This has application for understanding the biology in the bay, and we used a machine learning technique known as kriging to interpolate the data.
My master's thesis and several papers were on the topic of competition between superconductivity and magnetism. This used quantum transport equations to find the Green's functions. I also solved the bead on a hoop problem, which is partially solved in many introductory physics courses on Lagrangian mechanics.
For my doctoral work, I used the density matrix renormalization group (DMRG) to investigate the exact properties of density functional theory (DFT). We demonstrated that the pure-density functional could be learned by machine learning techniques.
Recently I have been using tensor networks to model superconducting circuits and also working on algorithms for quantum computing.