Plans for the week of April 27-May 1

Dear all, welcome back to FYS5419/9419.

This week the plan is to bring back some of the material from the QAOA lecture material from last week (Note that the recording has not yet been uploaded) and link this with quantum machine learning methods based on neural networks. The topics for this week's lecture are thus:

Reminder of QAOA material from last week

Basics of quantum machine learning (QML)

Quantum neural networks (QNN) and links to QAOA and other methods

The teaching material is in different formats at https://github.com/CompPhysics/QuantumComputingMachineLearning/tree/gh-pages/doc/pub/week14, see PDF file and jupyter-notebook. The jupyter-notebook is a companion to the PDF file. Note that the PDF file contains the discussion of the material with math etc, while the Jupyter-notebook discusses implementations of the quantum neural networks.

This week we have lab/project work from 815am-10am and the lecture 1015am-12pm.

The plan for the rest of semester is more or less as follows:

## May 4-8, 2026 Quantum Machine Learning

  - Quantum neural networks and Quantum Physics Informed Neural Networks (QPINNs)

  - Sovling differential equations with QPINNs

  - Teaching material in different formats at https://github.com/CompPhysics/QuantumComputingMachineLearning/tree/gh-pages/doc/pub/week15, see PDF file and jupyter-notebook. The jupyter-notebook is a companion to the PDF file 

## May 11-15, 2026

  - Quantum neural networks and quantum Boltzmann machines

  - Teaching material in different formats at https://github.com/CompPhysics/QuantumComputingMachineLearning/tree/gh-pages/doc/pub/week16, see PDF file and jupyter-notebook. The jupyter-notebook is a companion to the PDF file

## May 18-22, 2026

  - Summary of course and discussion of and work on project 2

Best wishes,

Carl Fredrik and Morten