Project Abstract

Project Abstract

In the past few decades, the field of computer science has witnessed two fundamental paradigm shifts. The first relates to artificial neural networks, which have proven extremely effective in tasks as diverse as language recognition, medical diagnosis, advanced automation and the most advanced artificial intelligence algorithms. The second is quantum computation, which harnesses unique quantum features such as superposition and entanglement to provide dramatic advantages for classically intractable problems.

This project aims at using the advantages of photonic quantum systems for combining both paradigms: the demonstration of quantum neural networks that exploit novel quantum memristor devices to introduce controllable nonlinear gate operations and short-time memory. The integrated photonic processor is going to be realised on a glass substrate by femtosecond laser micromachining, a technique which provides outstanding advantages such as circuit reconfigurability, low insertion losses, rapid prototyping, and three-dimensional circuit topology, all of which are critical for the success of the project. The quantum processor will be capable of executing programmable finite discrete mathematical transforms.

By combining the complementary expertise in photonic quantum computing, integrated quantum photonics and quantum information theory we will build a tunable photonic quantum memristor network. The versatility of this nonlinear processor will be shown by demonstrating real-life quantum-enhanced applications reaching from speech recognition to image identification, accelerated via quantum reservoir computing architectures.

The goals of this project will lay the foundations for new quantum technology based on the particular features of quantum memristors. Our interdisciplinary consortium and work methodology give us the best conditions to tackle the conceptual and technological challenges involved, and thus establish the first generation of quantum neuromorphic computing hardware based on a quantum photonic platform.