[HTML][HTML] Applications and techniques for fast machine learning in science

AMC Deiana, N Tran, J Agar, M Blott… - Frontiers in big …, 2022 - frontiersin.org
In this community review report, we discuss applications and techniques for fast machine
learning (ML) in science—the concept of integrating powerful ML methods into the real-time …

Delocalized photonic deep learning on the internet's edge

A Sludds, S Bandyopadhyay, Z Chen, Z Zhong… - Science, 2022 - science.org
Advanced machine learning models are currently impossible to run on edge devices such
as smart sensors and unmanned aerial vehicles owing to constraints on power, processing …

Coherent SAT solvers: a tutorial

S Reifenstein, T Leleu, T McKenna… - Advances in Optics …, 2023 - opg.optica.org
The coherent Ising machine (CIM) is designed to solve the NP-hard Ising problem quickly
and energy efficiently. Boolean satisfiability (SAT) and maximum satisfiability (Max-SAT) are …

The diamond mesh, a phase-error-and loss-tolerant field-programmable MZI-based optical processor for optical neural networks

F Shokraneh, S Geoffroy-Gagnon… - Optics …, 2020 - opg.optica.org
This paper presents the performance analysis of a phase error-and loss-tolerant multiport
field-programmable MZI-based structure for optical neural networks (ONNs). Compared to …

Addressing the programming challenges of practical interferometric mesh based optical processors

KHR Mojaver, B Zhao, E Leung, SMR Safaee… - Optics express, 2023 - opg.optica.org
We demonstrate a novel mesh of Mach-Zehnder interferometers (MZIs) for programmable
optical processors. We thoroughly analyze the benefits and drawbacks of previously known …

Photonic-aware neural networks

E Paolini, L De Marinis, M Cococcioni… - Neural Computing and …, 2022 - Springer
Photonics-based neural networks promise to outperform electronic counterparts,
accelerating neural network computations while reducing power consumption and footprint …

Multidimensional convolution operation with synthetic frequency dimensions in photonics

L Fan, Z Zhao, K Wang, A Dutt, J Wang, S Buddhiraju… - Physical Review …, 2022 - APS
The convolution operation is widely used in signal and image processing and represents the
most computationally intensive step in convolutional neural networks. We introduce a …

Increasing ising machine capacity with multi-chip architectures

A Sharma, R Afoakwa, Z Ignjatovic… - Proceedings of the 49th …, 2022 - dl.acm.org
Nature has inspired a lot of problem solving techniques over the decades. More recently,
researchers have increasingly turned to harnessing nature to solve problems directly. Ising …

On-chip optical phase monitoring in multi-transverse-mode integrated silicon-based optical processors

KR Mojaver… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
We design a Multi-Transverse-Mode Optical Processor (MTMOP) on 220 nm thick Silicon
Photonics exploiting the first two quasi-transverse electric modes (TE0 and TE1). The …

A comprehensive survey on nanophotonic neural networks: Architectures, training methods, optimization, and activations functions

K Demertzis, GD Papadopoulos, L Iliadis, L Magafas - Sensors, 2022 - mdpi.com
In the last years, materializations of neuromorphic circuits based on nanophotonic
arrangements have been proposed, which contain complete optical circuits, laser …