September 27, 2021 to October 1, 2021
ECT* - Trento
Europe/Rome timezone

Machine learning phase transitions in a scalable manner on classical and quantum processors

Sep 27, 2021, 3:00 PM
50m
Aula Renzo Leonardi (ECT* - Trento)

Aula Renzo Leonardi

ECT* - Trento

Strada delle Tabarelle, 286 38123 - Villazzano (TN) Italy

Speaker

Marina Marinkovic (ETH Zurich)

Description

As the applications of machine learning in lattice gauge theories are moving beyond the toy models, the parallelization of learning algorithms and alternative approaches to their efficient implementation gains in importance. In this talk, I will present two possible avenues to speed up the methods with applications to phase transitions classifications. After the discussion of the support vector machine learning model with a focus on its efficient parallelization, we will move the SVM to a quantum circuit and benchmark it using the Ising model in two dimensions.

Presentation materials