Related papers: Perfect Linear Optics using Silicon Photonics
Recent progress in photonic information processing has spurred strong demand in scalable and reconfigurable photonic circuitry. Conventional spatially-meshed multi-port interferometers require a number of components growing quadratically…
We present an overview of the performances of a plenoptic microscope which combines the high sensitivity of a laser optical feedback imaging setup , the high resolution of optical synthetic aperture and a shot noise limited signal to noise…
We propose to use high numerical aperture single mode optical fibers like photonic crystal fiber for lensless in-line holographic microscopy. Highly divergent beam helps to overcome the spatial sampling limitation of the image sensor. In…
We propose a linear-optical implementation of a hyperentanglement-assisted quantum error-correcting code. The code is hyperentanglement-assisted because the shared entanglement resource is a photonic state hyperentangled in polarization and…
With the continuous increase in the size and complexity of machine learning models, the need for specialized hardware to efficiently run such models is rapidly growing. To address such a need, silicon-photonic-based neural network (SP-NN)…
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…
As an optical processor, a Diffractive Deep Neural Network (D2NN) utilizes engineered diffractive surfaces designed through machine learning to perform all-optical information processing, completing its tasks at the speed of light…
The computational demands of modern AI have spurred interest in optical neural networks (ONNs) which offer the potential benefits of increased speed and lower power consumption. However, current ONNs face various challenges,most…
This work introduces the first closed-loop adaptive optics (AO) system capable of optically correcting aberrations in real-time without a guidestar or a wavefront sensor. Nearly 40 years ago, Cederquist et al. demonstrated that asymmetric…
We previously established that in principle, it is possible to quantum compute using passive linear optics with photo-detectors (quant-ph/0006088). Here we describe techniques based on error detection and correction that greatly improve the…
Neural networks are one of the first major milestones in developing artificial intelligence systems. The utilisation of integrated photonics in neural networks offers a promising alternative approach to microelectronic and hybrid…
The realization of lossless metasurfaces with true chirality crucially requires the fabrication of three-dimensional structures, constraining their feasibility for experiments and hampering practical implementations. Even though the…
Photonic integrated circuits (PICs) offer ultra-broad optical bandwidths that enable unprecedented data throughputs for signal processing applications. Dynamic reconfigurability enables compensation of fabrication flaws and fluctuating…
Tailoring critical light-matter coupling is a fundamental challenge of nanophotonics, impacting diverse fields from higher harmonic generation and energy conversion to surface-enhanced spectroscopy. Plasmonic perfect absorbers (PAs), where…
The realisation of quantum networks requires local quantum information processing at the network nodes and highly efficient transmission of quantum information across the network. Integrated photonics, based on silicon-on-insulator, is a…
The on-chip creation of coherent light at visible wavelengths is crucial to field-level deployment of spectroscopy and metrology systems. Although on-chip lasers have been implemented in specific cases, a general solution that is not…
Optical neural networks present distinct advantages over traditional electrical counterparts, such as accelerated data processing and reduced energy consumption. While coherent light is conventionally employed in optical neural networks,…
Over the past decade, artificial intelligence (AI) has led to disruptive advancements in fundamental sciences and everyday technologies. Among various machine learning algorithms, deep neural networks have become instrumental in revealing…
The growing maturity of photonic integrated circuit (PIC) fabrication technology enables the high integration of an increasing number of optical components onto a single chip. With the incremental circuit complexity, the calibration of…
Optical nonlinearity plays a pivotal role in quantum information processing using photons, from heralded single-photon sources, coherent wavelength conversion to long-sought quantum repeaters. Despite the availability of strong dipole…