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Surface states generally degrade semiconductor device performance by raising the charge injection barrier height, introducing localized trap states, inducing surface leakage current, and altering the electric potential. Therefore, there has…
Whether it is for transmitting information or for controlling intensity, light modulation is among the essential functions commonly used in complex optical systems. In integrated optics, modulation principles usually include the use of…
Surface Nanoscale Axial Photonic (SNAP) microresonators are fabricated on silica optical fibers, leveraging silica's outstanding material and mechanical properties. These properties allow for precise control over the microresonator…
Laser-based manufacturing has emerged as a promising alternative to conventional thermal and mechanical processing owing to its precision, versatility, and ability to work across diverse materials. In particular, tailoring the spatial…
On-chip photonic processors for neural networks have potential benefits in both speed and energy efficiency but have not yet reached the scale at which they can outperform electronic processors. The dominant paradigm for designing on-chip…
Gradient clipping is a standard training technique used in deep learning applications such as large-scale language modeling to mitigate exploding gradients. Recent experimental studies have demonstrated a fairly special behavior in the…
We theoretically propose and experimentally demonstrate optically tunable nonlinear mechanical damping in a cavity optomechanical system utilizing a partly resolved sideband regime. Optomechanical coupling provides a delayed nonlinear…
In this work, we propose to leverage a deep-learning (DL) based reconstruction framework for high quality Swept-Source Optical Coherence Tomography (SS-OCT) images, by incorporating wavelength ({\lambda}) space interferometric fringes.…
This paper proposes a novel scalable reinforcement learning approach for simultaneous routing and spectrum access in wireless ad-hoc networks. In most previous works on reinforcement learning for network optimization, the network topology…
We demonstrate optomechanically-mediated electromagnetically-induced transparency and wavelength conversion in silicon nitride (Si3N4) microdisk resonators. Fabricated devices support whispering gallery optical modes with a quality factor…
Photoacoustic imaging (PAI) has been applied to many biomedical applications over the past decades. However, the received PA signal usually suffers from poor signal-to-noise ratio (SNR). Conventional solution of employing higher-power…
Adaptive impedance matching between antennas and radio frequency front-end modules is critical for maximizing power transmission efficiency in mobile communication systems. Conventional numerical and analytical methods struggle with a…
Lenses that can collect the perfect image of an object must restore propagative and evanescent waves. However, for efficient information transfer, e.g., in compressed sensing, it is often desirable to detect only the fast spatial variations…
Spiking Neural Networks (SNNs) offer notable advantages in biological plausibility and energy efficiency, making them promising candidates for building low-power Transformers. However, existing Spiking Transformers largely adhere to a…
The merger between integrated photonics and quantum optics promises new opportunities within photonic quantum technology with the very significant progress on excellent photon-emitter interfaces and advanced optical circuits. A key missing…
The quest for an integrated quantum optics platform has motivated the field of semiconductor quantum dot research for two decades. Demonstrations of quantum light sources, single photon switches, transistors, and spin-photon interfaces have…
We propose a method for spatially re-routing single photons or light in a coherent state with small average photon number by purely electronic means, i.e. without using mechanical devices such as micro-mirror arrays. The method is based on…
Spiking Neural Networks (SNNs) may offer an energy-efficient alternative for implementing deep learning applications. In recent years, there have been several proposals focused on supervised (conversion, spike-based gradient descent) and…
Over the past few decades, optical manipulation has emerged as a highly successful tool in various fields, such as biology, micro/nanorobotics, and physics. Among the different techniques, the transverse slot optical waveguide has shown…
Optical forces in guided-wave nanostructures have recently been proposed as an effective means of mechanically actuating and tuning optical components. In this work, we study the properties of a photonic crystal optomechanical cavity…