El día Miércoles 19 de Noviembre 2025 a las 16:10 hrs, en el Auditorio San Agustín (Facultad de Ingeniería), se realizó la séptima charla en el ciclo de seminarios del Departamento de Matemática y Física Aplicadas (DMFA) en su versión 2025. El seminario es organizado por los académicos del DMFA, Dr. Sergio Caucao y Dr. Patrick Concha.

 

A Deep Learning Approach for Quantum Entanglement

and Quantum Discord Discrimination

Dr. Daniel Uzcátegui 
Universidad Católica de la Santísima Concepción

Resumen:

In this work, we propose a deep learning-based approach for quantum resource classification using convolutional autoencoders (CAE). We train models to distinguish entangled from separable states for dxd systems with d = 2,…,7, which enables identification of bound and free entanglement. Through extensive numerical simulations across various quantum state families, we demonstrate that our model achieves high classification accuracy. Furthermore, we leverage the learned representations to generate samples of bound entangled states–the rarest form of entanglement and notoriously difficult to construct analytically. We separately train the same CAE architecture for detecting the presence of quantum discord and show that the model also exhibits high accuracy while requiring significantly less training time.