# Machine Learning for High Energy Physics, on and off the Lattice

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

## Machine learning with quantum field theories

Sep 27, 2021, 4:40 PM
30m
Aula Renzo Leonardi (ECT* - Trento)

### Aula Renzo Leonardi

#### ECT* - Trento

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

### Speaker

Dimitrios Bachtis (Swansea University (UK))

### Description

The exact equivalence between lattice field theories and the mathematical framework of Markov random fields opens up the opportunity to investigate machine learning from the perspective of quantum field theory. In this talk we prove Markov properties for the $\phi^{4}$ theory and we then derive $\phi^{4}$ neural networks which can be viewed as generalizations of conventional neural network architectures. Finally, applications pertinent to the minimization of an asymmetric distance between the probability distribution of the $\phi^{4}$ machine learning algorithms and target probability distributions are additionally presented.