Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Imaging Biological Samples with Optical Microscopy

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Deciphering optical coupled resonant systems with physics-data co-driven deep neural networks.

Light, science & applications·2026

Same author

Upconversion optical entropy encoding for infrared complex-amplitude imaging.

Light, science & applications·2026

Same author

Deep learning enhanced light sheet fluorescence microscopy for in vivo 4D imaging of zebrafish heart beating.

Light, science & applications·2025

Same author

Deep empirical neural network for optical phase retrieval over a scattering medium.

Nature communications·2025

Same author

Experimental demonstration of 8190-km long-haul semiconductor-laser chaos synchronization induced by digital optical communication signal.

Light, science & applications·2025

Same author

Wireless-Channel Key Distribution Based on Laser Synchronization.

Entropy (Basel, Switzerland)·2024

Same journal

Demonstration of a quantum C-NOT gate in a time-multiplexed fully reconfigurable photonic processor.

Nature communications·2026

Same journal

Nonlinear quantum light source with van der Waals ferroelectric NbOX<sub>2</sub> (X = Br, I).

Nature communications·2026

Same journal

Antagonistic histone H2A variants and autonomous heterochromatin formation shape epigenomic patterns in Arabidopsis.

Nature communications·2026

Same journal

The long tail of nitrate pollution in groundwater challenges governance of global water quality.

Nature communications·2026

Same journal

Select microbial metabolites promote tau aggregation in a murine tauopathy model.

Nature communications·2026

Same journal

Warming climate has lengthened global intense tropical cyclone seasons.

Nature communications·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 5, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Non-orthogonal optical multiplexing empowered by deep learning.

Tuqiang Pan^1,2, Jianwei Ye^1,2, Haotian Liu^1,2

¹Key Laboratory of Photonic Technology for Integrated Sensing and Communication, Ministry of Education, Guangzhou, 510006, China.

Nature Communications

|February 21, 2024

Summary

This summary is machine-generated.

This study introduces non-orthogonal optical multiplexing using a deep neural network (SLRnet) to overcome capacity limits. The SLRnet successfully retrieves multiple signals from a single output, achieving 98% fidelity for high-capacity optical communication.

More Related Videos

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

Demonstration of Spin-Multiplexed and Direction-Multiplexed All-Dielectric Visible Metaholograms

Demonstration of Spin-Multiplexed and Direction-Multiplexed All-Dielectric Visible Metaholograms

Published on: September 25, 2020

Related Experiment Videos

Last Updated: May 5, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

Demonstration of Spin-Multiplexed and Direction-Multiplexed All-Dielectric Visible Metaholograms

Demonstration of Spin-Multiplexed and Direction-Multiplexed All-Dielectric Visible Metaholograms

Published on: September 25, 2020

Area of Science:

Optical Communications
Signal Processing
Machine Learning

Background:

Orthogonal channels in optical multiplexing limit capacity.
Non-orthogonal multiplexing offers higher capacity but poses signal retrieval challenges.

Purpose of the Study:

To develop a method for non-orthogonal optical multiplexing over multimode fiber (MMF).
To leverage deep learning for retrieving multiple signals from a single output.

Main Methods:

A deep neural network, the speckle light field retrieval network (SLRnet), was developed.
SLRnet learns the complex mapping between non-orthogonal input light fields and a single intensity output.
Proof-of-principle experimental demonstration was conducted.

Main Results:

SLRnet effectively solves the ill-posed problem of non-orthogonal multiplexing in MMF.
Multiple non-orthogonal input signals were retrieved with up to 98% fidelity.
Successful retrieval was achieved from a single-shot speckle output.

Conclusions:

Non-orthogonal optical multiplexing can be harnessed for high-capacity communication.
Deep learning provides a powerful tool for signal retrieval in complex optical systems.
This approach represents a significant step towards advanced optical multiplexing techniques.