The Quantum Information and Computing group aims to better understand and harness the power of near-term quantum computers to solve scientific problems. We are particularly interested in the rapidly growing field of quantum machine learning. A large part of our work focuses on applying quantum information theory and classical learning theory to sit quantum machine learning on stronger foundations. In parallel, we are working to develop new algorithms for simulating quantum systems on noisy quantum computers. In both cases, we explore applications of our work to other areas physics including material science, quantum chemistry, high energy physics and even quantum foundations.
