Descrizione del progetto
La simulazione quantistica e la geometria dei fogli di gomma chiariscono i diversi sistemi quantistici
La topologia costituisce una branca della matematica che si occupa dello studio delle forme e della loro disposizione nello spazio. Talvolta, la topologia viene denominata geometria dei fogli di gomma e studia le proprietà di oggetti che vengono preservate in presenza di deformazioni continue, quali l’allungamento e la flessione. Storicamente è stata relegata al regno della matematica, eppure, la sua applicazione alla fisica dei materiali sta fornendo dettagli unici, riconosciuti in parte dalla vincita del premio Nobel per la fisica nel 2016 che attesta il suo ruolo svolto nella comprensione di forme esotiche di materia. Il progetto NOQIA, finanziato dall’UE, amplierà notevolmente tale ambito tramite l’elaborazione di approcci teorici e descrizioni innovativi. Il progetto combinerà la simulazione quantistica, gli effetti e i sistemi topologici con l’universo dei fenomeni ultraveloci e dell’attoscienza, dell’apprendimento automatico quantistico e delle reti neurali quantistiche.
Obiettivo
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.
Campo scientifico
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencescomputer and information sciencesdata sciencedata processing
- natural sciencesphysical sciencesopticslaser physics
- natural sciencesphysical sciencestheoretical physics
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Parole chiave
Programma(i)
Argomento(i)
Meccanismo di finanziamento
ERC-ADG - Advanced GrantIstituzione ospitante
08860 Castelldefels
Spagna