The growing maturity of integrated photonic technology makes it possible to build
increasingly large and complex photonic circuits on the surface of a chip. Today, most of …

Machine learning (ML) encompasses a broad range of algorithms and modeling tools used
for a vast array of data processing tasks, which has entered most scientific disciplines in …

Complex-valued neural networks have many advantages over their real-valued
counterparts. Conventional digital electronic computing platforms are incapable of executing …

Matrix computation, as a fundamental building block of information processing in science
and technology, contributes most of the computational overheads in modern signal …

Growing interest in quantum computing for practical applications has led to a surge in the
availability of programmable machines for executing quantum algorithms,. Present-day …

Integrated photonic neural networks provide a promising platform for energy-efficient, high-
throughput machine learning with extensive scientific and commercial applications. Photonic …

Large-scale, highly integrated and low-power-consuming hardware is becoming
progressively more important for realizing optical neural networks (ONNs) capable of …

Controlling and programming quantum devices to process quantum information by the unit
of quantum dit, ie, qudit, provides the possibilities for noise-resilient quantum …

Photons have been a flagship system for studying quantum mechanics, advancing quantum
information science, and develo** quantum technologies. Quantum entanglement …

The ability to control multidimensional quantum systems is central to the development of
advanced quantum technologies. We demonstrate a multidimensional integrated quantum …