The development of machine learning methods based on deep learning boosted the field of artificial intelligence towards unprecedented achievements and application in several fields. Such prominent results were made in parallel with the first successful demonstrations of fault tolerant hardware for quantum information processing. To which extent deep learning can take advantage of the existence of a hardware based on qubits behaving as a universal quantum computer is an open question under investigation. Here I review the convergence between the two fields towards implementation of advanced quantum algorithms, including quantum deep learning.
Quantum neuromorphic hardware for quantum artificial intelligence / E. Prati. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6588. - 880(2017), pp. 012018.1-012018.7. ((Intervento presentato al 8. convegno International Workshop on Decoherence, Information, Complexity and Entropy (DICE) - Spacetime - Matter - Quantum Mechanics : September, 12 - 16 tenutosi a Castiglioncello nel 2016 [10.1088/1742-6596/880/1/012018].
Quantum neuromorphic hardware for quantum artificial intelligence
E. Prati
2017
Abstract
The development of machine learning methods based on deep learning boosted the field of artificial intelligence towards unprecedented achievements and application in several fields. Such prominent results were made in parallel with the first successful demonstrations of fault tolerant hardware for quantum information processing. To which extent deep learning can take advantage of the existence of a hardware based on qubits behaving as a universal quantum computer is an open question under investigation. Here I review the convergence between the two fields towards implementation of advanced quantum algorithms, including quantum deep learning.
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
