Project description
The winding (non-linear) road toward a quantum leap in computational power
Quantum computing has long held the imagination of scientists and the public alike as the next great frontier, far beyond supercomputing. Relying on qubits rather than conventional bits, using the properties of quantum physics to store data and perform computations, these machines have now been realised at small scales. The fundamental goal is getting to the quantum advantage, realising the quantum computer's promise to solve problems intractable with conventional ones. The EU-funded QU-BOSS project is planning to do so using a novel approach involving non-linear dynamics embedded within integrated photonics technology.
Objective
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.
Fields of science
- 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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Funding Scheme
ERC-ADG - Advanced GrantHost institution
00185 Roma
Italy