Simulation of Temporally Matrix Vector Multiplication with Rayleigh Backscattering

Photonic matrix vector multiplication (MVM) has renewed interest in optical computing, which has the potential to reduce the power consumption and maintain relatively high speed. Temporally MVM (T-MVM) using distributed feedback based on the Rayleigh backscattering is one of them. Here, we established the numerical model of the T-MVM using distributed feedback based on the Rayleigh backscattering in a single-mode fiber. The feasibility of this model is proven by performing the non-linear principal component analysis (PCA). The impact of the random Rayleigh backscattering coefficient on the capability of the nonlinear PCA is also investigated. The simulation results show that the non-linear PCA can efficiently separate the points randomly distributed on 3 concentric spheres with different radii. The randomness of the Rayleigh backscattering coefficient plays an important role in improving the capability of this model.

Institutions

Publication Details

Published
2025-06-27
DOI
https://doi.org/10.1109/icwoc65853.2025.11151136
Primary Topic
Housing Market and Economics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simulation of Temporally Matrix Vector Multiplication with Rayleigh Backscattering

Housing Market and Economics
article

Simulation of Temporally Matrix Vector Multiplication with Rayleigh Backscattering

article en

Abstract

Photonic matrix vector multiplication (MVM) has renewed interest in optical computing, which has the potential to reduce the power consumption and maintain relatively high speed. Temporally MVM (T-MVM) using distributed feedback based on the Rayleigh backscattering is one of them. Here, we established the numerical model of the T-MVM using distributed feedback based on the Rayleigh backscattering in a single-mode fiber. The feasibility of this model is proven by performing the non-linear principal component analysis (PCA). The impact of the random Rayleigh backscattering coefficient on the capability of the nonlinear PCA is also investigated. The simulation results show that the non-linear PCA can efficiently separate the points randomly distributed on 3 concentric spheres with different radii. The randomness of the Rayleigh backscattering coefficient plays an important role in improving the capability of this model.

Photonic Science (United Kingdom) (GB)
Openalex Percentile: Top 34%
Housing Market and Economics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.