Description du projet
Quand l’IA rencontre la physique quantique
L’essor de l’intelligence artificielle (IA) et de l’apprentissage automatique (AA) gagne du terrain dans la science et la recherche fondamentale. L’AA est déjà employé dans différents domaines de la physique (traitement et classification des mégadonnées). L’application de l’informatique quantique à l’IA et à l’AA est une application future passionnante de la recherche quantique. Dans ce contexte, QuantAI, financé par l’UE, étudiera l’utilisation de l’IA dans les sciences fondamentales, en mettant l’accent sur l’information quantique. Le projet développera des modèles d’agence artificielle bénéfiques pour la recherche fondamentale et faciliteront les applications vers l’expérimentation quantique et la découverte scientifique pilotées par l’IA. Par exemple, des agents d’apprentissage artificiels classiques seront développés pour être utilisés dans des schémas adaptatifs de correction d’erreurs quantiques et intégrés dans des architectures de calcul quantique à grande échelle.
Objectif
Quantum mechanics is our most fundamental theory of physics. It has formed, and often challenged, our understanding of physical reality. We use quantum mechanics to manipulate and control matter and light at the atomic scale, and it provides the basis for many new technologies. At the same time, the rise of artificial intelligence (AI) and machine learning (ML) is gaining momentum in science and basic research. ML is already employed in different areas of physics, mostly for big data processing and classification. But the development of AI is heading much further and is likely to transform basic science in the near future. In this project, we will investigate the use of AI in basic science, with a focus on quantum physics and, more specifically, quantum information. We will develop models of artificial agency which are beneficial for basic research, both from a practical and a foundational perspective. We will develop classical artificial learning agents that can be used, e.g. for adaptive schemes of quantum error correction and integrated in large-scale quantum computing architectures, the design of complex quantum communication networks, and the study of novel computational phases of matter. The models of learning agents that we develop will facilitate applications towards AI-driven quantum experiment and scientific discovery. Our focus will be on transparent and interpretable models for artificial agency that are beneficial if not needed for basic science. These models can be used in future hybrid laboratories where human researchers will interact with AI assistant systems. On the foundational side, we will investigate quantum agents and the role of agency in quantum theory. These investigations will shed light not only on the possible ways of learning in a quantum environment, but also on the physical dimension of AI, the explainability of quantum AI, and the consistency of quantum theory.
Champ scientifique
- natural sciencesphysical sciencesquantum physics
- natural sciencescomputer and information sciencesdata sciencebig data
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwarequantum computers
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencescomputer and information sciencesdata sciencedata processing
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Thème(s)
Régime de financement
HORIZON-ERC - HORIZON ERC GrantsInstitution d’accueil
6020 Innsbruck
Autriche