Related papers: Nonvolatile electrically reconfigurable integrated…
Neuromorphic photonics has recently emerged as a promising hardware accelerator, with significant potential speed and energy advantages over digital electronics, for machine learning algorithms such as neural networks of various types.…
We propose advancing photonic in-memory computing through three-dimensional photonic-electronic integrated circuits using phase-change materials (PCM) and AlGaAs-CMOS technology. These circuits offer high precision (greater than 12 bits),…
Phase changing materials (PCM) are widely used for optical data recording, sensing, all-optical switching, and optical limiting. Our focus here is on the case when the change in the transmission characteristics of the optical material is…
Recent advances in photonic integrated circuits (PICs) have enabled a new generation of "programmable many-mode interferometers" (PMMIs) realized by cascaded Mach Zehnder Interferometers (MZIs) capable of universal linear-optical…
Topological photonic insulators pave the way toward efficient integrated photonic devices with minimized scattering losses. Optical properties of the majority of topological structures proposed to date are fixed by design such that no…
We challenge the current thinking and approach to the design of photonic integrated circuits (PICs) for applications in communications, quantum information and sensing. The standard PICs are based on directional couplers, that provide a…
The synergy between metasurfaces and non-volatile phase change materials (PCMs) has created many reconfigurable photonic devices for applications in optical memory, optical computing and optical communications. But these advances have been…
In the past decades, silicon photonic integrated circuits (PICs) have been considered as a promising approach to solve the bandwidth bottleneck in optical communications and interconnections. Despite significant advances, large-scale PICs…
With a rapidly growing amount of data generated and processed, a search for more efficient components and architectures such as neuromorphic computing that are able to perform a more and more complex operations in more efficient way…
The integration of computing with memory is essential for distributed, massively parallel, and adaptive architectures such as neural networks in artificial intelligence (AI). Accelerating AI can be achieved through photonic computing, but…
Ultra-violet (UV) and near-UV wavelengths are necessary for many important optical transitions for quantum technologies and various sensing mechanisms for biological and chemical detection. However, all well-known photonic platforms have…
In the last decade phase change materials (PCM) research has switched from practical application in optical data storage toward electrical phase change random access memory technologies (PCRAM). As these devices are commercialised, we…
Photonic integrated circuits (PICs) at cryogenic temperatures enable a wide range of applications in scalable classical and quantum systems for computing and sensing. A promising application of cryogenic PICs is to provide optical…
The Artificial Intelligence models pose serious challenges in intensive computing and high-bandwidth communication for conventional electronic circuit-based computing clusters. Silicon photonic technologies, owing to their high speed, low…
Inducing a large refractive-index change is the holy grail of reconfigurable photonic structures, a goal that has long been the driving force behind the discovery of new optical material platforms. Recently, the unprecedentedly large…
Programmable photonic integrated circuits (PICs) have recently emerged as an important technology for quantum information science and artificial neural networks. In particular, PICs with MEMS-based modulators have the advantages of…
Optical neural networks (ONNs) based on programmable photonic integrated circuits (PICs) offer a promising route toward low-latency and energy-efficient deep learning. However, conventional photonic implementations of matrix-vector…
Quantum photonic integrated circuits, composed of linear-optical elements, offer an efficient way for encoding and processing quantum information on-chip. At their core, these circuits rely on reconfigurable phase shifters, typically…
Integrated quantum photonics offers a promising path to scale up quantum optics experiments by miniaturizing and stabilizing complex laboratory setups. Central elements of quantum integrated photonics are quantum emitters, memories,…
We propose an all-photonic, non-volatile memory and processing element based on phase-change thin-films deposited onto nanophotonic waveguides. Using photonic microring resonators partially covered with Ge2Sb2Te5 (GST) multi-level memory…