Projets QI

Équipe : QI

• Applications and Hardware for Photonic Quantum Information Processing

  AppQInfo will provide a world class training in photonic Quantum Information Processing (pQIP), and prepare an excellent cohort of Early Stage Researchers (ESRs) to become the future R&D staff of Europe’s emerging markets in this area. Quantum Information Processing (QIP) is a key ingredient in Europe’s future Quantum Communication Infrastructure; it underpins quantum communications and quantum simulations, the first two pillars of the H2020 Quantum Flagship. QIP will revolutionise information technology, providing higher quality, speed and unconditional security, not possible with classical technologies. AppQInfo focusses on QIP in state-of-the-art integrated photonics, one of five Key Enabling Technologies for European Industry. Integrated photonics permits the creation, manipulation and readout of photonic quantum states in a highly controlled manner, with high speeds and low losses. The broad objectives of AppQInfo are: to create an excellent training of ESRs in the field of pQIP that is both interdisciplinary and intersectoral; to develop innovative, entrepreneurial ESRs with great career prospects; to maximise the exploitation and dissemination of our research; to engage the public through several outreach activities; to consolidate a wide expertise in the field of pQIP; to create a long-lasting collaboration network of top-class research units and industrial entities. Together, our 15 interdisciplinary research projects will work towards feasible long- distance quantum communications from urban-scale networks to satellite-based systems using various data encoding; study quantum photonic circuits towards their quantum transport properties and quantum transforms they implement; exploit these platforms for machine learning applications, such as building all-optical artificial neural networks, and applying them for quantum simulations; develop enabling technologies of sources and detectors of multiphoton quantum states and polaritonic logic gates.

  Responsable : Eleni Diamanti
  10/06/2021
  
• PHOQUSING - Photonics Quantum Sampling Machine - H2020

  Randomness is a resource that enables applications such as efficient probabilistic algorithms, numerical integration, simulation, and optimization. In the last few years it was realized that quantum devices can generate probability distributions that are inaccessible with classical means. Hybrid Quantum Computational models combine classical processing with these quantum sampling machines to obtain computational advantage in some tasks. Moreover, NISQ (Noisy, Intermediate-Scale Quantum) technology may suffice to obtain this advantage in the near term, long before we can build large-scale, universal quantum computers. PHOQUSING aims to implement PHOtonic Quantum SamplING machines based on large, reconfigurable interferometers with active feedback, and state-of-the-art photon sources based both on quantum dots and parametric down-conversion. We will overview the different architectures enabling the generation of these hard-to-sample distributions using integrated photonics, optimizing the designs and studying the tolerance to errors. We will build two quantum sampling machines with different technologies, as a way to do cross-checks while exploiting all advantages of each platform. These machines will establish a new state-of-the-art in photonic reconfigurability, system complexity, and integration. Finally, we plan to perform first, proof-of-principle demonstrations of Hybrid Quantum Computation applications in optimization, machine learning, and graph theory. The PHOQUSING team includes long-term scientific collaborators who were among the first to demonstrate quantum photonic samplers; two of the leading European start-ups in the relevant quantum technologies; and theoretical experts in photonics and quantum information science. This project will help establish photonics as a leading new quantum computational technology in Europe, addressing the science-to-technology transition towards a new industrial sector with a large foreseeable economic impact.

  Responsable : Elham Kashefi
  01/09/2020