QU-BOSS
QUantum advantage via non-linear BOSon Sampling
After decades of progress in quantum information science, it is widely expected that in the next few years this 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 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.
Total Eligible Budget
2,875,000.00 €
INL Eligible Budget
190,000.00 €
INL Funding
190,000.00 €
Start Date
01-08-2020
End Date
31-07-2026
Type of action
AdG Advanced Grant
Grant Agreement Id
884676
Funding Agency
European Commission
Programme
ERC – European Research Council
Funding Framework
HORIZON 2020
INL Role
Partner
Approval Date
19-03-2020
Main Objective