This was part of Bayesian Statistics and Statistical Learning

Learning Entanglement Types

Luke Oeding, Auburn University

Thursday, December 14, 2023


We use machine learning techniques to develop tests to separate types of quantum entanglement. In particular, I will describe an artificial neural network model we used to learn membership on certain algebraic varieties. Our results show that it is possible to learn membership on varieties (like a hyperdeterminantal hypersurface) where traditional interpolation methods would be infeasible. 


This is joint work with Hamza Jaffali who works at ColibrITD, a quantum information startup in Paris, France.