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QUantum advantage via non-linear BOSon Sampling

Descrizione del progetto

La strada tortuosa (non lineare) verso un salto quantistico nella potenza di calcolo

Da tempo il calcolo quantistico alimenta le fantasie degli scienziati e del pubblico come la prossima grande frontiera, ben oltre il supercalcolo. Basandosi su qubit e non su bit convenzionali, usando le proprietà della fisica quantistica per immagazzinare dati ed eseguire calcoli, queste macchine sono state ora realizzate su piccola scala. L’obiettivo fondamentale è arrivare al vantaggio quantistico, realizzando la promessa del computer quantistico di risolvere problemi non risolvibili con quelli convenzionali. Il progetto QU-BOSS, finanziato dall’UE, prevede di farlo utilizzando un nuovo approccio che coinvolge dinamiche non lineari incorporate nella tecnologia fotonica integrata.

Obiettivo

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.

Meccanismo di finanziamento

ERC-ADG - Advanced Grant
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Coordinatore

UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA
Contribution nette de l'UE
€ 2 305 000,00
Indirizzo
Piazzale aldo moro 5
00185 Roma
Italia

Mostra sulla mappa

Regione
Centro (IT) Lazio Roma
Tipo di attività
Higher or Secondary Education Establishments
Collegamenti
Altri finanziamenti
€ 0,00

Beneficiari (3)