of Victoria
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M.Sc. (CSU Long Beach); PhD (UC Irvine); Prized postdoctoral fellow in quantum sciences and technology (IQ, Université de Sherbrooke); Fulbright U.S. Scholar (University of York, UK)
Quantum computing, quantum matter, condensed matter theory, density functional theory, tensor networks, error-correction
RESEARCH
Quantum computing is a fundamental rethink of how a computer is constructed. Instead of moving electrons around in a circuit (which can be slow and produce a lot of heat), one can imagine using other properties from quantum physics to perform computations. When using a single spin, the resulting qubit will contain a superposition of states and this allows for algorithms that can be much harder to run on a classical computer. My research spans the construction and use of a quantum computer, working on everything from materials for qubits, designing networks of qubits, error-correction, and how to use a quantum computer with quantum algorithms. The main algorithmic focus is to solve problems in quantum chemistry and density functional theory. Often, we use tensor networks as a computational tool with our in-house library DMRjulia to supplement our theoretical expressions and statements.
TEACHING
Dr. Baker has taught a variety of graduate courses on quantum physics, classical physics, statistical physics, density functional theory, and computational methods. He has also delivered summer school courses on tensor networks, and he is actively looking to work with students from all backgrounds in his activities.