xola101/pennylane-demo-cern

Contains material for the PennyLane tutorial at CERN on 3/4 February 2021.

pennylane-demo-cern

This repository contains material for the PennyLane tutorial at CERN on 3/4 February 2021.

Schedule

9:30 - 9:45 Welcome and recap of seminar (open on github) (open with Google Drive)

9:45 - 10:30 Part I: Classical machine learning with automatic differentiation

Notebook 1-classical-ml-with-automatic-differentiation (open on github) (open with colab)

Learning objectives:

• be able to explain the concept of automatic differentiation,

• be able to train a simple linear model using automatic differentiation.

10:30 - 11:15 Part II: Differentiable quantum computing

Notebook 2-differentiable-quantum-computations (open on github) (open with colab)

Learning objectives:

• be able to implement a variational quantum circuit in PennyLane,

• compute the gradient of a variational quantum circuit,

• train a variational quantum circuit like a machine learning model.

11:15 - 11:45 Break

11:45 - 12:25 Part III: Quantum gradients on remote devices

Slides (open on github) (open with Google Drive)

Notebook 3-quantum-gradients (open on github) (open with colab)

Learning objectives:

• be able to explain two different ways to compute quantum gradients,

• understand why parameter-shift rules are needed for hardware,

• be able to compute a quantum gradient on a remote backend.

12:25-12:30 Final words