NOQIA
Financiado
NOvel Quantum simulators connectIng Areas
Quantum simulators (QS) are experimental systems that allow mimic hard to simulate models of condensed matter, high energy physics and beyond. QS have various platforms: from ultracold atoms and ions to superconducting qubits. The...
Quantum simulators (QS) are experimental systems that allow mimic hard to simulate models of condensed matter, high energy physics and beyond. QS have various platforms: from ultracold atoms and ions to superconducting qubits. They constitute the important pillar of quantum technologies (QT), and promise future applications in chemistry, material science and optimization problems. Over the last decade, QS were particularly successful in mimicking topological effects in physics (TEP) and in developing accurate quantum validation/certification (QVC) methods. NOQIA is a theory project, aimed at introducing the established field of QS+TEP+QVC into two novel areas: physics of ultrafast phenomena and attoscience (AS) on one side, and quantum machine learning (ML) and neural networks (NN) on the other. This will open up new horizons/opportunities for research both in AS and in ML/NN. For instance, in AS we will address the question if intense laser physics may serve as a tool to detect topological effects in solid state and strongly correlated systems. We will study response of matter to laser pulses carrying topological signatures, to determine if they can induce topological effects in targets. We will design/analyze QS using trapped atoms to understand and detect TEP in the AS. On the ML/NN side, we will apply classical ML to analyze, design and control QS for topological systems, in order to understand and optimize them. Conversely, we will transfer many-body techniques to ML in order to analyze and possibly improve performance of classical machine learning. We will design and analyze quantum neural network devices that will employ topology in order to achieve robust quantum memory or information processing. We will design/study attractor neural networks with topological stationary states, or feed-forward networks with topological Floquet and time-crystal states. Both in AS and ML/NN, NOQIA will rely on quantum validation and certification protocols and techniques.
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Duración del proyecto: 68 meses
Fecha Inicio: 2019-04-26
Fecha Fin: 2024-12-31
Fecha Fin: 2024-12-31
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2019-04-26
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2018-ADG:
ERC Advanced Grant
Cerrada
hace 6 años
Presupuesto
El presupuesto total del proyecto asciende a
2M€
Líder del proyecto
FUNDACIO INSTITUT DE CIENCIES FOTONIQUES
Otra investigación y desarrollo experimental en ciencias naturales y técnicas asociacion
Perfil tecnológico
TRL
4-5
50K
Perfil tecnológico
TRL
4-5
50K