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Related Concept Videos

Semiconductors01:22

Semiconductors

2.0K
There is variation in the electrical conductivity of materials - metals, semiconductors, and insulators that are showcased with the help of the energy band diagrams.
Metals such as copper (Cu), zinc (Zn), or lead (Pb) have low resistivity and feature conduction bands that are either not fully occupied or overlap with the valence band, making a bandgap non-existent. This allows electrons in the highest energy levels of the valence band to easily transition to the conduction band upon gaining...
2.0K

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Microwave Photonics Systems Based on Whispering-gallery-mode Resonators
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Software-defined reconfigurable microwave photonics processor.

Daniel Pérez, Ivana Gasulla, José Capmany

    Optics Express
    |June 16, 2015
    PubMed
    Summary
    This summary is machine-generated.

    We introduce a novel, chip-integrable software-defined reconfigurable microwave photonics signal processor. This architecture performs key functions through programmable control signals, advancing signal processing capabilities.

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    Area of Science:

    • Photonics
    • Microwave Engineering
    • Signal Processing

    Background:

    • Traditional signal processors lack reconfigurability.
    • Integrating photonic and RF components presents design challenges.

    Purpose of the Study:

    • To propose a novel software-defined reconfigurable microwave photonics signal processor architecture.
    • To develop a comprehensive design model for this integrated system.

    Main Methods:

    • Design of a basic reconfigurable architecture.
    • Derivation of an end-to-end model considering photonic and RF interdependencies.
    • Demonstration through application examples.

    Main Results:

    • A versatile, chip-integrable microwave photonics signal processor architecture.
    • A validated design model accounting for system-level performance.
    • Proof of concept via diverse application scenarios.

    Conclusions:

    • The proposed architecture offers unprecedented flexibility in microwave photonics signal processing.
    • The developed model enables accurate prediction and optimization of integrated system performance.
    • This work paves the way for advanced, programmable photonic signal processing solutions.