7 papers
Quantum and classical processing with photonic quantum machine learning
J. C. López Carreño, S. Åwierczewski, A. Opala +3
Artificial intelligence and machine learning have been widely adopted both in the industry and in everyday life, but at the cost of high compute demands. Recent studies show that i…
Quantum reservoir computing with classical and nonclassical states in an integrated optical circuit
S. Åwierczewski, W. Verstraelen, P. Deuar +3
Quantum reservoir computing (QRC) is a hardware-implementation-friendly quantum neural network scheme with minimal physical system requirements and a proven advantage over classica…
Quantum Light Detection with Enhanced Photonic Neural Network
StanisÅaw Åwierczewski, Dogyun Ko, Amir Rahmani +7
Advances in quantum technologies are accelerating the demand for optical quantum state sensors that combine high precision, versatility, and scalability within a unified hardware p…
Spectroscopy on a single nonlinear mode recognizes quantum states
Wouter Verstraelen, StanisÅaw Åwierczewski, Andrzej Opala +7
Characterising optical quantum states is essential for the development of quantum technologies. While traditional approaches to perform full quantum state tomography are often expe…
Phase-Space Framework for Noisy Intermediate-Scale Quantum Optical Neural Networks
StanisÅaw Åwierczewski, Wouter Verstraelen, Piotr Deuar +4
Quantum optical neural networks (QONNs) enable information processing beyond classical limits by exploiting the advantages of classical and quantum optics. However, simulation of l…
Estimation of the second-order coherence function using quantum reservoir and ensemble methods
Dogyun Ko, StanisÅaw Åwierczewski, Andrzej Opala +2
We propose a machine learning-based approach enhanced by quantum reservoir computing (QRC) to estimate the zero-time second-order correlation function g2(0). Typically, measuring g…