Related papers: Programmable and nonvolatile computing with compos…
Thin-film lithium niobate (TFLN) has enabled efficient on-chip electro-optic modulation and frequency conversion for information processing and precision measurement. Extending these capabilities with optical frequency combs unlocks…
In the past decade, lithium niobate (LiNbO3 or LN) photonics, thanks to its heat-free and fast electro-optical modulation, second-order non-linearities and low loss, has been extensively investigated. Despite numerous demonstrations of…
Recently integrated optics has become an intriguing platform for implementing machine learning algorithms and inparticular neural networks. Integrated photonic circuits can straightforwardly perform vector-matrix multiplicationswith high…
Thin-film lithium niobate (TFLN) has emerged as a versatile integrated photonics platform, combining strong electro-optic and nonlinear effects. Among TFLN devices, ring resonators play a central role in filtering, modulation, and nonlinear…
Lithium niobate (LN) is a promising material for future complex photonic-electronic circuits, with wide applications in fields like data communications, sensing, optical computation, and quantum optics. There was a great step toward LN…
Electronically reprogrammable photonic circuits based on phase-change chalcogenides present an avenue to resolve the von-Neumann bottleneck; however, implementation of such hybrid photonic-electronic processing has not achieved…
We demonstrated broadband highly efficient optical nonlinear processes in on-chip integrated lithium niobate (LN) microdisk resonators. The Q factors of the micro-resonators fabricated by femtosecond laser writing and chemo-mechanical…
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…
Lithium niobate (LN) metasurfaces exhibit remarkable Pockels effect-driven electro-optic tunability, enabling dynamic control of optical responses through external electric fields. When combined with their high second-order nonlinear…
Lithium Niobate (LN) is an important nonlinear optical material. Here we demonstrate LN microdisk resonators that feature optical quality factor ~ 100,000, realized using robust and scalable fabrication techniques, that operate over a wide…
Lithium Niobate (LN or just niobate) thin-film micro-photonic resonators have promising prospects in many applications including high efficiency electro-optic modulators, optomechanics and nonlinear optics. This paper presents free-standing…
Thin-film lithium niobate (TFLN) is a widely used platform for nonlinear frequency conversion, as its strong nonlinear susceptibility and enhanced modal confinement intensify nonlinear interactions. Frequency doubling from NIR to visible…
We present a lithium niobate multi-functional platform (LN-MFP) that integrates photoacoustic and thermoelastic spectroscopy with photodetection on a single chip. Utilizing LN's piezoelectric and thermoelastic properties and an optimized…
Superconducting cavity electro-optics (EO) presents a promising route to coherently convert microwave and optical photons and distribute quantum entanglement between superconducting circuits over long-distance through an optical network.…
Adaptable, reconfigurable and programmable are key functionalities for the next generation of silicon-based photonic processors, neural and quantum networks. Phase change technology offers proven non-volatile electronic programmability,…
Optomechanical transduction harnesses the interaction between optical fields and mechanical motion to achieve sensitive measurement of weak mechanical quantities with inherently low noise. Lithium niobate combines low optical loss, strong…
Active metasurfaces hold great promise for spatial light modulation, and electro-optic tuning using lithium niobate is particularly attractive due to its high transparency and well-established thin-film platform. In this work, we present a…
Optical approaches have made great strides towards the goal of high-speed, energy-efficient computing necessary for modern deep learning and AI applications. Read-in and read-out of data, however, limit the overall performance of existing…
Thin-film lithium niobate (TFLN) in the form of x- or z-cut lithium-niobate-on-insulator (LNOI) has recently popped up as a very promising and novel platform for developing integrated optoelectronic (nano)devices and exploring fundamental…
Low-bit quantized neural networks are of great interest in practical applications because they significantly reduce the consumption of both memory and computational resources. Binary neural networks are memory and computationally efficient…