Quantum metrology is one of the most promising applications of quantum technologies. The
aim of this research field is the estimation of unknown parameters exploiting quantum …

Programmable optical circuits are an important tool in develo** quantum technologies
such as transceivers for quantum communication and integrated photonic chips for quantum …

Quantum reservoir computing aims at harnessing the rich dynamics of quantum systems for
machine-learning purposes. It can be used for online time series processing while having a …

Combinatorial optimization problems are crucial for widespread applications but remain
difficult to solve on a large scale with conventional hardware. Novel optical platforms, known …

In this work, we present a method to characterize the transmission matrices of complex
scattering media using a physics-informed, multi-plane neural network (MPNN) without the …

Finding optical setups producing measurement results with a targeted probability distribution
is hard, as a priori the number of possible experimental implementations grows …

Physical unclonable functions (PUFs) are complex physical objects that aim at overcoming
the vulnerabilities of traditional cryptographic keys, promising a robust class of security …

Optical neural networks process information at the speed of light and are energetically
efficient. Photonic artificial intelligence allows speech recognition, image classification, and …

In the context of quantum information, highly nonlinear regimes, such as those supporting
solitons, are marginally investigated. We miss general methods for quantum solitons …

Neuromorphic processors improve the efficiency of machine learning algorithms through the
implementation of physical artificial neurons to perform computations. However, whilst …