MAC-MIGS Deep Dive on Quantum Machine Learning (5th/6th June)

5th June 2023



MAC-MIGS Deep Dive on Quantum Machine Learning – 5th/6th June

** Quantum Machine Learning **

We are pleased to invite PhD students and members of staff to attend a MAC-MIGS Deep Dive in Quantum Machine Learning with Francesco Tacchino (IBM, Zurich).

There will be two introductory lectures, a research seminar, and an opportunity to discuss with the speaker. The talks will be in G.03 Bayes Centre (Ground Floor). Registration is required:

Registration form

Details and timetable are below.

All talks by Francesco Tacchino (IBM, Zurich)

Monday 5th June in G.03 Bayes Centre

10.00-11.00 Introduction to quantum machine learning (Lecture 1)
11.00-11.30 Coffee, Tea, Biscuits
11.30-12.30 Introduction to quantum machine learning (Lecture 2)

Monday afternoon chat at Bayes 5th floor (5.45) 15.00-16.00

Tuesday 6th June in G.03 Bayes Centre

14.00-15.00 Quantum computing: technology and applications in the natural sciences (Research seminar)

Organisers: Lehel Banjai, Des Johnston, Matias Ruiz



Title: An introduction to quantum machine learning
In recent years, machine learning brought about a novel perspective on information processing systems and the way they interact with the surrounding world. Almost in parallel, quantum computing appeared as a technological paradigm that could offer efficient solutions for currently intractable problems. Quantum Machine Learning (QML) aims at establishing a productive interplay between these fields, integrating quantum techniques into machine learning protocols and devising new solutions for the analysis of classical and quantum data.
In this tutorial, I will present some fundamental concepts in QML, with a focus on parametrized quantum circuits. After some preliminary examples, I will introduce quantum perceptrons, quantum support vector machines and quantum neural networks, discussing their properties, potential applications, and proof-of-principle implementations on quantum processors.
Title: Quantum computing: technology and applications in the natural sciences

Over the last few decades, quantum information processing has emerged as a gateway towards new, powerful approaches to scientific computing. Quantum technologies are nowadays experiencing a rapid development and could lead to effective solutions in different domains including physics, chemistry, and life sciences, as well as optimisation, artificial intelligence, and finance. In this talk, I will review the state-of-the-art and recent progress in the field, both in terms of hardware and software, and present a broad spectrum of potential applications, with a focus on natural sciences and machine learning.