Related papers: Monolithically Integrated Optical Convolutional Pr…
Optical and hybrid convolutional neural networks (CNNs) recently have become of increasing interest to achieve low-latency, low-power image classification and computer vision tasks. However, implementing optical nonlinearity is challenging,…
All-optical diffractive neural networks (DNNs) offer a promising alternative to electronics-based neural network processing due to their low latency, high throughput, and inherent spatial parallelism. However, the lack of reconfigurability…
Hybrid integrated quantum photonics combines solid-state artificial atoms with reconfigurable photonic circuits, enabling scalable chip-based quantum networks. Self-assembled quantum dots (QDs) are ideal for this goal due to their ability…
Lithium niobate photonic chip could realize diverse optical engineering for various applications benefiting from its excellent optical performances. In this letter, we demonstrate monolithic photonic chips for multi-channel sum-frequency…
Most modern convolutional neural networks (CNNs) used for object recognition are built using the same principles: Alternating convolution and max-pooling layers followed by a small number of fully connected layers. We re-evaluate the state…
Future quantum information networks operated on telecom channels require qubit transfer between different wavelengths while preserving quantum coherence and entanglement. Qubit transfer is a nonlinear optical process, but currently the…
Narrow-linewidth lasers at short/visible wavelengths are crucial for quantum and atomic applications, such as atomic clocks, quantum computing, atomic and molecular spectroscopy, and quantum sensing. However, such lasers are often only…
Optical imaging is commonly used for both scientific and technological applications across industry and academia. In image sensing, a measurement, such as of an object's position, is performed by computational analysis of a digitized image.…
Convolutional neural networks (CNNs), inspired by biological visual cortex systems, are a powerful category of artificial neural networks that can extract the hierarchical features of raw data to greatly reduce the network parametric…
Thin-film lithium tantalate (TFLT) has recently emerged as a promising photonic platform for chip-scale nonlinear optics due to its weaker photorefraction, higher optical damage threshold, broader transparency window, and lower…
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…
Squeezed states of light play a key role in quantum-enhanced sensing and continuous-variable quantum information processing. Realizing integrated squeezed light sources is crucial for developing compact and scalable photonic quantum…
Neural Networks (NNs) have become the mainstream technology in the artificial intelligence (AI) renaissance over the past decade. Among different types of neural networks, convolutional neural networks (CNNs) have been widely adopted as…
Deep neural networks (DNNs) utilized recently are physically deployed with computational units (e.g., CPUs and GPUs). Such a design might lead to a heavy computational burden, significant latency, and intensive power consumption, which are…
Integrated photonics has emerged as a promising platform for quantum communication and quantum computation. Thin-film lithium niobate (TFLN) has gained significant attention in this field due to its exceptional optical properties, enabling…
While classical convolutional neural networks (CNNs) have revolutionized image classification, the emergence of quantum computing presents new opportunities for enhancing neural network architectures. Quantum CNNs (QCNNs) leverage quantum…
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…
Lithium niobate (LN) based devices are widely used in integrated and nonlinear optics. This material is robust and resistive to high temperatures, which makes the LN-based devices table, but challenging to fabricate. In this work we report…
Integrated photonic platforms can greatly enhance the efficiency of nonlinear frequency conversion processes by tightly confining light on a sub-micron scale. However, this advantage is often reduced by large fiber-to-chip coupling losses…
This paper presents a compact dual-arm thin film lithium niobate (TFLN) electro-optic phase modulator fabricated using the photolithography-assisted chemo-mechanical etching (PLACE) technique. The design of the device allows for complete…