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.
https://youtu.be/3OS7Pq6JoDY
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.