Descripción del proyecto
El encuentro entre la inteligencia artificial y la física cuántica
El auge de la inteligencia artificial (IA o AI, por sus siglas en inglés) y el aprendizaje automático (AA) está ganando terreno en la investigación científica y la básica. El AA ya se emplea en diferentes ámbitos de la física (procesamiento y clasificación de datos masivos). La aplicación de la computación cuántica a la IA y el AA es un emocionante uso futuro de la investigación cuántica. En este contexto, el equipo del proyecto QuantAI, financiado con fondos europeos, estudiará el uso de la IA en la ciencia básica, centrándose en la información cuántica. Asimismo, desarrollará modelos de agencia artificial que sean beneficiosos para la investigación básica y faciliten las aplicaciones hacia la experimentación cuántica y el descubrimiento científico impulsados por la IA. Por ejemplo, se desarrollarán agentes de aprendizaje artificial clásicos para utilizarlos en esquemas adaptativos de corrección de errores cuánticos e integrarlos en arquitecturas de computación cuántica a gran escala.
Objetivo
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.
Ámbito científico
- 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
Palabras clave
Programa(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Régimen de financiación
HORIZON-ERC - HORIZON ERC GrantsInstitución de acogida
6020 Innsbruck
Austria