Description du projet
La route sinueuse (non linéaire) vers un saut quantique en puissance de calcul
L’informatique quantique stimule depuis longtemps l’imagination des scientifiques et du public, qui y voient la prochaine grande frontière, bien au-delà des supercalculateurs. S’appuyant sur des qubits plutôt que sur des bits classiques, utilisant les propriétés de la physique quantique pour stocker des données et effectuer des calculs, ces machines sont désormais construites à petite échelle. L’objectif fondamental est de parvenir à l’avantage quantique, en réalisant la promesse de l’ordinateur quantique de résoudre des problèmes insolubles avec des ordinateurs conventionnels. Le projet QU-BOSS, financé par l’UE, entend y parvenir en utilisant une nouvelle approche faisant appel à la dynamique non linéaire, intégrée à la technologie photonique.
Objectif
After decades of progress in quantum information science, it is widely expected that in the next few years the field will start to yield practical applications in quantum chemistry, materials and pharmaceutical research, information security, and finance. For these applications to pan out, a crucial intermediate goal is to reach the quantum advantage regime, where quantum devices experimentally outperform classical computers in some computational task. The Boson Sampling problem is an example of a task that is computationally hard for classical computers, but which can be solved with a specialized quantum device using single photons interfering in a multimode linear interferometer. The aim of QU-BOSS is to experimentally push towards the quantum advantage regime with integrated photonic technology. The key innovative ingredient is the introduction of non-linearities acting at the single photon level embedded within the Boson Sampling interferometer. We plan to provide an experimental research breakthrough along three main directions, including both “hardware” and “software” components. First, we will use complementary approaches to map out how the addition of non-linearity boosts the device ́s complexity, making it harder to simulate classically. We will use different approaches to implement these devices with hybrid integrated quantum photonics, a versatile and flexible route to the manipulation of high-dimensional quantum photonic states. Finally, we will deploy the developed technology to implement two different architectures demonstrating quantum machine learning: a hybrid model of quantum computation and an optical quantum neural network. QU- BOSS aims to position integrated photonics into the NISQ (noisy, intermediate-scale quantum) era, opening up truly new scientific horizons at the frontier of quantum information, quantum control, machine learning and integrated photonics.
Champ scientifique
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwarequantum computers
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencesphysical sciencesopticsnonlinear optics
- natural sciencesphysical sciencestheoretical physicsparticle physicsphotons
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
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Programme(s)
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Régime de financement
ERC-ADG - Advanced GrantInstitution d’accueil
00185 Roma
Italie