Semester page for FYS5419 - Spring 2025

Dear all, welcome back! The end of the semester is approaching and our last sessions are devoted to quantum machine learning.

This week we will try to finalize our discussion of quantum support vector machines, with code examples using PennyLane (I am almost giving up Qiskit...). The code examples are tailored to classification problems, with a classical one such as the Iris data and a vanilla one on credit score (pseudo financial data). The last data set is used for quantum neural networks as well. If we get time, we will dive into quantum neural networks as well.

This topic continues next week as well (lecture May 14). We may start with Boltzmann machines on May 14 if we get time. Else, our last session is May 21, we will wrap up and discuss the project as well.

The lectures will always be recorded and uploaded afterwards for those who cannot attend in person. 

The plan this week is thus

Dear all, welcome back! This week we continue our discussion of quantum machine learning. Last week we introduced support vector machines and will now venture (after a short repetition from last week) into quantum support vector machines.  After our discussion of quantum support vector machines, we will venture into (May 7) into quantum neural networks and finally quantum boltzmann machines (May 14). 

The plans this week are thus

Plans for the week of April 28-May 2

1. Classical Support Vector Machines, reminder from last week

2. Classical Kernels and transition to Quantum Kernels

3. Quantum Support Vector Machines

Reading recommendations

1. For classical Support Vector Machines, see lecture notes by Morten Hjorth-Jensen at ...

Dear all, welcome back to the last four weeks of the semester! We hope you had a great break and thx to everybody for excellent answers to project 1. It was a pleasure to read and grade them. 

Before the Easter break, we concluded our discussion of quantum Fourier transforms and the quantum phase estimation algorithm. These two algorithms can form the basis for the second project, and for those of you who feel tempted, one can also venture into an exploration of Shor's algorithm.

We will use the remaining time to discuss quantum machine learning algorithms, with a focus on quantum support vector machines, neural networks and eventually quantum Boltzmann machines. 

Tomorrow, our lecture will via zoom only, and the plan is to give first an introduction to quantum ML methods and then to dive into classical support vector machines (SVMs), a very popular ML methods, which hopefully allows to make a smooth transition to quantum ML metho...