Quantum computing is an emerging research field at the intersection of physics, computer science and applied mathematics. Quantum computers are devices that exploit coherent quantum phenomena to speed-up calculations. Quantum machine learning is a subfield of quantum computing that investigates the application of quantum computers algorithms for machine learning problems. This course will give an elementary introduction to quantum machine learning, and review a few examples of quantum algorithms for classification and clustering problems. In our first meeting, we will give a general introduction, and review quantum algorithms for solving linear systems of equations, Grover search and simulating sparse Hamiltonian dynamics.
Date: 2 June 2023
Time: 11:00 am
Location: Computational Physics Laboratory, Department of Electromagnetism and Condensed Mater, Ground Floor, Faculty of Science (next to the giant pendulum)