Project description
Quantum simulation and rubber sheet geometry shed new light on diverse quantum systems
Topology is a branch of mathematics concerned with the study of shapes and their arrangement in space. Sometimes called rubber sheet geometry, it is concerned with the properties of objects that are preserved under continuous deformations like stretching and bending. It was historically confined to the realm of mathematics. Still, its application to the physics of materials is providing unique insight, recognised in part by the 2016 Nobel Prize in Physics for the role of topology in understanding exotic forms of matter. The EU-funded NOQIA project will expand this crossroads significantly by developing novel theoretical approaches and descriptions. The project will unite quantum simulation and topological effects and systems with the realm of ultrafast phenomena and attoscience, quantum machine learning and quantum neural networks.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencesmathematicspure mathematicstopology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwarequantum computers
- natural sciencesphysical sciencesopticslaser physics
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Funding Scheme
ERC-ADG - Advanced GrantHost institution
08860 Castelldefels
Spain