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Artificial neural networks are efficient computing platforms inspired by the brain. Such platforms can tackle a vast area of real-life tasks ranging from image processing to language translation. Silicon photonic integrated chips (PICs), by…
We introduce a novel all-optical platform in multimode and multicore fibres. By using a low-power probe beam and a high-power counter-propagating control beam, we achieve advanced and dynamic control over light propagation within the…
Photonic integrated circuits are facilitating the development of optical neural networks, which have the potential to be both faster and more energy efficient than their electronic counterparts since optical signals are especially…
Photonic methods of radio-frequency waveform generation and processing provide performance and flexibility over electronic methods due to the ultrawide bandwidth offered by the optical carriers. However, they suffer from lack of integration…
Reconfigurability of photonic integrated circuits (PICs) has become increasingly important due to the growing demands for electronic-photonic systems on a chip driven by emerging applications, including neuromorphic computing, quantum…
Integrated optics is an engineering solution proposed for exquisite control of photonic quantum information. Here we use silicon photonics and the linear combination of quantum operators scheme to realise a fully programmable two-qubit…
The lack of interactions between single photons prohibits direct nonlinear operations in quantum optical circuits, representing a central obstacle in photonic quantum technologies. Here, we demonstrate multi-mode nonlinear photonic circuits…
Recent success in deep neural networks has generated strong interest in hardware accelerators to improve speed and energy consumption. This paper presents a new type of photonic accelerator based on coherent detection that is scalable to…
Photonic integrated circuits (PICs) play a pivotal role in many applications. Particularly powerful are circuits based on meshes of reconfigurable Mach-Zehnder interferometers as they enable active processing of light. Various possibilities…
Electronic and photonic chips revolutionized information technology through massive integration of functional elements, yet phonons as fundamental information carriers in solids remain underestimated. Here, we demonstrate large-scale…
Scalable programmable photonic integrated circuits (PICs) can potentially transform the current state of classical and quantum optical information processing. However, traditional means of programming, including thermo-optic, free carrier…
Emerging applications of photonics in computing, sensing, and security increasingly demand complex input-output behaviors, including highly nonlinear transformations of optical signals. Traditional photonic systems rely on highly structured…
We propose and analyze the design of a programmable photonic integrated circuit for high-fidelity quantum computation and simulation. We demonstrate that the reconfigurability of our design allows us to overcome two major impediments to…
The software configurable processor finds best use in the embedded systems. These processors have onchip logic like FPGA (Field Programmable Gate Array) and thus can be configured to implement custom hardware functionality. The digital…
Optics is a promising platform in which to help realise the next generation of fast, parallel and energy-efficient computation. We demonstrate a reconfigurable free-space optical multiplier that is capable of over 3000 computations in…
For decades, advances in electronics were directly driven by the scaling of CMOS transistors according to Moore's law. However, both the CMOS scaling and the classical computer architecture are approaching fundamental and practical limits,…
Photonic integrated circuits play an important role in the field of optical computing, promising faster and more energy-efficient operations compared to their digital counterparts. This advantage stems from the inherent suitability of…
Deep neural networks usually process information through multiple hidden layers. However, most hardware reservoir computing recurrent networks only have one hidden reservoir layer, which significantly limits the capability of solving…
Photonic Neural Network implementations have been gaining considerable attention as a potentially disruptive future technology. Demonstrating learning in large scale neural networks is essential to establish photonic machine learning…
Photonic computing chips have made significant progress in accelerating linear computations, but nonlinear computations are usually implemented in the digital domain, which introduces additional system latency and power consumption, and…