Machine Learning for maximizing the memristivity of single and coupled
  quantum memristors
Carlos Hernani-Morales Gabriel Alvarado Francisco Albarrán-Arriagada Yolanda Vives-Gilabert Enrique Solano José D. Martín-Guerrero
We propose machine learning (ML) methods to characterize the memristive
properties of single and coupled quantum memristors. We show that maximizing
the memristivity leads to large values in the degree of entanglement of two
quantum memristors, unveiling the close relationship between quantum
correlations and memory. Our results strengthen the possibility of using
quantum memristors as key components of neuromorphic quantum computing.