Related papers: Reinforcement Learning for Photonic Component Desi…

We implement a photonic crystal nanofiber device by reversibly combining an optical nanofiber and a nanofabricated grating. Using the finite-difference time-domain method, we design the system for minimal optical loss while tailoring the…

Higher-dimensional quantum systems, such as qudits, offer architectural and algorithmic advantages over qubits, but their increased spectral crowding and limited controllability render high-fidelity quantum gates particularly challenging.…

Integrated photonics has undergone tremendous development in the past few decades, transforming many fields of study in science and technology. Loss and gain are two fundamental elements in photonic circuits and have direct impacts on…

We have designed and fabricated a shallow-etched grating on gallium arsenide nanomembranes for efficient chip-to-fiber coupling in quantum photonic integrated circuits. Experimental results show that the grating provides a fiber-coupling…

The design automation of analog circuits is a longstanding challenge in the integrated circuit field. This paper presents a deep reinforcement learning method to expedite the design of analog circuits at the pre-layout stage, where the goal…

Photonic Neural Network implementations have been gaining considerable attention as a potentially disruptive future technology. Demonstrating learning in large scale neural networks is essential to establish photonic machine learning…

We report the design, fabrication in a commercial foundry, and experimental results of high-efficiency, normal incidence grating couplers for silicon photonics. We observe a maximum coupling efficiency of 85.4% (-0.69 dB) with a 1 dB…

Reinforcement learning has been successfully applied to the problem of tuning PID controllers in several applications. The existing methods often utilize function approximation, such as neural networks, to update the controller parameters…

This study focuses on the development of reinforcement learning based techniques for the design of microelectronic components under multiphysics constraints. While traditional design approaches based on global optimization approaches are…

We introduce a modular approach for efficiently interfacing photonic integrated circuits with deep-sub-wavelength hybrid plasmonic functionality. We demonstrate that an off-the-shelf silicon-on-insulator waveguide can be post-processed into…

We propose and experimentally demonstrate a photonic routing architecture that can efficiently utilize the space of multi-plane (3D) photonic integration. A wafer with three planes of amorphous silicon waveguides was fabricated and…

Efficient fiber-to-chip coupling has been a major hurdle to cost-effective packaging and scalable interconnections of photonic integrated circuits. Conventional photonic packaging methods relying on edge or grating coupling are constrained…

In Reinforcement Learning (RL), enhancing sample efficiency is crucial, particularly in scenarios when data acquisition is costly and risky. In principle, off-policy RL algorithms can improve sample efficiency by allowing multiple updates…

Hollow-core fibers offer superior loss and latency characteristics compared to solid-core alternatives, yet the geometric complexity of nested antiresonance nodeless fibers (NANFs) makes traditional optimization computationally prohibitive.…

Efficiently coupling light from optical fibers into photonic integrated circuits is a key step toward practical photonic devices. While a notable coupling can be achieved by out of plane couplers such as grating couplers, their basic planar…

We propose a practical and efficient solution for the coupling of light from integrated single-mode waveguides to supercollimating planar photonic crystals on conventional silicon-on-insulator platforms. The device consists of a rib…

Numerical simulations have become a cornerstone technology in the development of nanophotonic devices. Specifically, 3D finite difference time domain (FDTD) simulations are a widely used due to their flexibility and powerful design…

Integrated photonic circuits play a crucial role in implementing quantum information processing in the noisy intermediate-scale quantum (NISQ) era. Variational learning is a promising avenue that leverages classical optimization techniques…

Linear transformations are cornerstone operations utilized in modern computing, but are computationally expensive on current electronic platforms. Optical computing has been positioned as a new computing solution, promising high speed and…

We present a photonic coupler that exhibits effectively wavelength-agnostic performance for ultra-broadband optical interfacing. By incorporating a dual-ellipsoidal geometry, the design facilitates quasi-free-space optical propagation. We…