The simultaneous advances in artificial neural networks and photonic integration
technologies have spurred extensive research in optical computing and optical neural …

Quantum information processing is nowadays an established branch of quantum mechanics
applications. Recent results in different areas, ranging from communications to computing …

Quantum computing aims at exploiting quantum phenomena to efficiently perform
computations that are unfeasible even for the most powerful classical supercomputers …

Integrated photonics is an essential technology for optical quantum computing. Universal,
phase-stable, reconfigurable multimode interferometers (quantum photonic processors) …

Waveguide lattices offer a compact and stable platform for a range of applications, including
quantum walks, condensed matter system simulation, and classical and quantum …

All-optical nonlinear activation functions (NAFs) are crucial for enabling rapid optical neural
networks (ONNs). As linear matrix computation advances in integrated ONNs, on-chip all …

In the context of a doomed end of the Moore's law, various new types of computing
architectures have been emerging, aiming to meet the demands of intractable computation …

Harnessing high-dimensional entangled states of light presents a frontier for advancing
quantum information technologies, from fundamental tests of quantum mechanics to …

Over the past decade, integrated quantum photonic technologies have shown great
potential as a platform for studying quantum phenomena and realizing large-scale quantum …

The data-embedding process is one of the bottlenecks of quantum machine learning,
potentially negating any quantum speedups. In light of this, more effective data-encoding …