Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the problem,...

You might also read

Related Articles

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

Sort by
Same author

An ultra-high-speed vertically illuminated self-driven lateral asymmetric InSe photodetector.

Nanoscale·2025
Same author

Short-wavelength infrared (SWIR) photodetector based on multi-layer 2D GaGeTe.

Optics express·2021
See all related articles

Related Experiment Video

Updated: Jul 3, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

High-performance delay-based photonic reservoir computing.

Kirubel Solomon Tesfaye, Solomon M Serunjogi, Mahmoud S Rasras

    Optics Express
    |July 2, 2026
    PubMed
    Summary

    This study reveals optimal performance in photonic reservoir computing occurs near, but below, chaotic dynamics. Strategies like node coupling and readout shifting enhance performance, with saturation observed beyond 50 nodes.

    Area of Science:

    • Photonics
    • Nonlinear Dynamics
    • Computational Science

    Background:

    • Delay-based reservoir computing offers hardware-efficient photonic implementations.
    • Parameter selection in these systems often relies on empirical tuning.
    • Understanding physical and dynamical factors is crucial for optimizing performance.

    Purpose of the Study:

    • To systematically study a single-node delay-based photonic reservoir computer.
    • To identify key factors governing computational performance using the nonlinear channel equalization (NCE) benchmark.
    • To establish a correspondence between operating regimes and performance metrics.

    Main Methods:

    • Experimental study of a single-node photonic reservoir computer.
    • Port-Hamiltonian formulation to map the system's bifurcation landscape.

    More Related Videos

    Generation and Coherent Control of Pulsed Quantum Frequency Combs
    06:42

    Generation and Coherent Control of Pulsed Quantum Frequency Combs

    Published on: June 8, 2018

    Quasi-light Storage for Optical Data Packets
    07:45

    Quasi-light Storage for Optical Data Packets

    Published on: February 6, 2014

    Related Experiment Videos

    Last Updated: Jul 3, 2026

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
    05:30

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

    Published on: September 8, 2023

    Generation and Coherent Control of Pulsed Quantum Frequency Combs
    06:42

    Generation and Coherent Control of Pulsed Quantum Frequency Combs

    Published on: June 8, 2018

    Quasi-light Storage for Optical Data Packets
    07:45

    Quasi-light Storage for Optical Data Packets

    Published on: February 6, 2014

  • Evaluation using the nonlinear channel equalization (NCE) benchmark.
  • Comparison of temporal optimization strategies: delay-input period desynchronization and local node coupling.

    • Main Results:

    • Optimal performance achieved near, but below, the onset of oscillatory and chaotic dynamics.
    • Symbol error rate (SER) decreases with node count, saturating beyond approximately 50 nodes.
    • A readout shifting strategy improved performance, achieving an SER of 0.003 at 19 dB SNR.

    Conclusions:

    • Physics-informed insights guide parameter selection and architectural optimization in photonic reservoir computing.
    • Optimal operation is achieved in a specific dynamical regime, avoiding full chaos.
    • Practical scaling constraints exist, but performance can be enhanced through optimization strategies.