AI-Assisted Inverse Design Methods of Few-Mode Multi-Core Fiber

We propose two machine learning-based inverse design methods for few-mode multi-core fiber, utilizing neural networks and particle swarm optimization algorithms to achieve high design accuracy and efficiency.

Authors

Xujun Tang
Jiajing Tu
Ziwen Liu (ORCID: https://orcid.org/0000-0002-4081-6923)
Weiping Liu

Institutions

Jinan University (CN)
PLA Information Engineering University (CN)

Publication Details

Published: 2025-06-29
DOI: https://doi.org/10.23919/oecc/psc62146.2025.11109184
Primary Topic: Advanced Fiber Optic Sensors
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

AI-Assisted Inverse Design Methods of Few-Mode Multi-Core Fiber

Xujun Tang, Jiajing Tu, Ziwen Liu, Weiping Liu

Jun 29, 2025

5 links

Advanced Fiber Optic Sensors

article

AI-Assisted Inverse Design Methods of Few-Mode Multi-Core Fiber

Xujun Tang, Jiajing Tu, Ziwen Liu, Weiping Liu

June 29, 2025article en

Abstract

Jinan University (CN), PLA Information Engineering University (CN)

Affordable and clean energy

Openalex Percentile: Top 80%

Advanced Fiber Optic Sensors

DOI Source OpenAlex

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.

AI-Assisted Inverse Design Methods of Few-Mode Multi-Core Fiber — Xujun Tang, Jiajing Tu, et al. · (2025) | TGRS Research Map | TGRS