Episode description
Episode description
During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series. With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk. I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.
Q#, a quantum-focused domain-specific language explicitly designed to correctly, clearly and completely express quantum algorithms.
TITLE: Empowering Quantum Machine Learning Research with Q#
SPEAKER: Dr Christopher Granade
AFFILIATION: Quantum Systems, Microsoft, Washington, USA HOSTED BY: A/Prof Chris Ferrie, UTS Centre for Quantum Software and Information
ABSTRACT: In this talk, I will demonstrate how the Q# quantum programming language can be used to start exploring quantum machine learning, using a binary classification problem as an example. I will describe recent work in QML algorithms for classification, and show how Q# allows implementing and using this classifier through high-level quantum development features. Finally, I will discuss how these approaches can be used as part of a reproducible research process to share your explorations with others.