Versatile multimode fiber network with high capacity enabled by deep learning

Author:

Xiao Qirong1ORCID,Zhang Hailong1,Wang Lele1ORCID,He Zhaofan1,Cai Xin2,Meng Yuan1,Ma Jianshe3

Affiliation:

1. Tsinghua University

2. The Chinese University of Hong Kong

3. Tsinghua Shenzhen International Graduate School

Abstract

Abstract

In the realm of spatial information transmission in multimode fiber (MMF), the MMF-based endoscopes and information encryption technologies have garnered considerable attention. However, existing designs are limited to establishing a single connection between one input node and one output node, thus constraining the capacity and application scenarios of MMF spatial information transmission. Here, we demonstrate a new concept of MMF-based physical networking for spatial information transmission, and develop a physical model and implementation method for establishing multi-node networking with various topological structures via cascading MMFs.We experimentally verify the feasibility of parallel transmission of spatial information at multiple nodes in an exemplary three-node MMF network with chain topology, showcasing its capability in transmitting color images through "node multiplexing" with significantly enhanced communication security through long-distance reprogrammable optical encryption. Designing MMF networks based on different node quantities and topological structures can significantly expand the scenarios for MMF spatial information transmission, providing valuable paradigms for various applications such as minimally invasive panoramic endoscopy, low-cost distributed sensing, and scaling optical reservoir computing.

Publisher

Research Square Platform LLC

Reference45 articles.

1. Network science of biological systems at different scales: A review;Gosak M;Phys Life Rev,2018

2. Peterson LL, Davie BS (2007) Computer networks: a systems approach. Elsevier

3. Central dogma of molecular biology;Crick F;Nature,1970

4. Hunt EB (2014) Artificial intelligence. Academic

5. Computational intelligence in wireless sensor networks: A survey;Kulkarni RV;IEEE Commun Surv tutorials,2010

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3