From Molecules to Quantum Computers: A Research Retrospective

Quantum computers promise to unlock new capabilities in areas ranging from the study of physical systems to cryptography. The field of quantum computing is built on the solid foundations of computational science that the Department of Energy Computational Science Graduate Fellowship continues to build. In this special research retrospective, I discuss my path in quantum computing research that receiving this award made possible. Starting with an introduction to quantum computing, I discuss how variational methods came to be popular on quantum computing hardware today, and the need to mitigate errors. The setting of variational algorithms facilitates a connection between quantum computers and the theory of machine learning, leading to discovery of phenomena, such as barren plateaus in the training landscape. This connection has allowed us to better understand the role of data, and how data can elevate machine learning models above traditional computation.