Learning exotic phases of matter via hidden Born Machines
Khadijeh Najafi, Abigail McClain Gomez, et al.
APS March Meeting 2022
Neural networks are computing models that have been leading progress in Machine Learning (ML) and Artificial Intelligence (AI) applications. In parallel, the first small-scale quantum computing devices have become available in recent years, paving the way for the development of a new paradigm in information processing. Here we give an overview of the most recent proposals aimed at bringing together these ongoing revolutions, and particularly at implementing the key functionalities of artificial neural networks on quantum architectures. We highlight the exciting perspectives in this context, and discuss the potential role of near-term quantum hardware in the quest for quantum machine learning advantage.
Khadijeh Najafi, Abigail McClain Gomez, et al.
APS March Meeting 2022
David Peral-garcía, Juan Cruz-Benito, et al.
ICIST 2023
Julien Gacon, Jannes Nys, et al.
PRResearch
Kenny Jing Choo, Antonio Mezzacapo, et al.
APS March Meeting 2020