Machine Learning for Maximizing the Memristivity of Single and Coupled Quantum Memristors
Abstract
Machine learning (ML) methods are proposed to characterize the memristive properties of single and coupled quantum memristors. It is shown 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. The results strengthen the possibility of using quantum memristors as key components of neuromorphic quantum computing. © 2024 The Authors. Advanced Quantum Technologies published by Wiley-VCH GmbH.
Más información
| Título según WOS: | Machine Learning for Maximizing the Memristivity of Single and Coupled Quantum Memristors |
| Título según SCOPUS: | Machine Learning for Maximizing the Memristivity of Single and Coupled Quantum Memristors |
| Título de la Revista: | Advanced Quantum Technologies |
| Editorial: | John Wiley and Sons Inc. |
| Fecha de publicación: | 2024 |
| Idioma: | English |
| DOI: |
10.1002/qute.202300294 |
| Notas: | ISI, SCOPUS |