Quantum machine learning with PennyLane and Xanadu Quantum Codebook

Feb 1, 2022 · Toronto, Canada

Abstract

The first part of this talk provides an introduction to quantum machine learning using the Python-based PennyLane software library, covering key concepts like variational circuits and hybrid models. We show how circuits can be constructed and trained in PennyLane on a variety of hardware devices and simulators.

The second part of this talk gives an introduction to the Xanadu Quantum Codebook, explaining both the motivation behind it and how to use it.

Presenters

Thomas Bromley
Thomas is a Quantum Machine Learning Developer at Xanadu who works on PennyLane, the world’s leading quantum differentiable programming software library. Thomas holds an MSc in Physics from the University of Warwick and a PhD in Physics from the University of Nottingham. Thomas' background is in the measurement and quantification of quantum properties and he now focuses on making cutting edge quantum algorithms available through software and over the cloud.

Catalina Albornoz
Catalina holds a MSc. in Electronics from Los Andes University and Engineering Diploma from IMT Atlantique in France. She’s currently Quantum Community Manager at Xanadu, where she helps build the community around PennyLane. In the past Catalina has worked at IBM, where she was an IBM Quantum Ambassador, and at GreenYellow Colombia, where she was Project Manager for energy efficiency projects.

Moderators

Pawel Gora , CEO of Quantum AI Foundation
Dr. Sebastian Zajac, board member of QPoland

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Held in partnership with the Washington QC Meetup

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