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Related Experiment Video

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Photonic digital-to-analog conversion using a blue frequency chirp in a semiconductor optical amplifier.

Takuya Okada, Ryuichi Kobayashi, Wang Rui

    Optics Letters
    |March 13, 2020
    PubMed
    Summary

    We developed a photonic digital-to-analog converter (DAC) using blue-chirp spectral slicing in a semiconductor optical amplifier. This technique converts 10 Gb/s digital signals into analog signals with high resolution.

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    Area of Science:

    • Photonics
    • Optical Communications
    • Signal Processing

    Background:

    • Photonic digital-to-analog converters (DACs) are crucial for high-speed signal processing.
    • Existing photonic DACs face challenges in achieving high resolution and speed.
    • Semiconductor optical amplifiers (SOAs) offer potential for novel photonic device applications.

    Purpose of the Study:

    • To present a novel photonic digital-to-analog conversion (DAC) technique.
    • To demonstrate a 10 Gb/s, 2-bit photonic DAC using blue-chirp spectral slicing.
    • To evaluate the resolution performance of the proposed photonic DAC.

    Main Methods:

    • Utilizing a semiconductor optical amplifier (SOA) to induce a blue-chirp spectral shift in probe signals.
    • Employing spectral slicing with rectangular filters to extract logic-level-dependent probe signals.
    • Experimentally demonstrating the DAC with a 10 Gb/s digital input signal and various data patterns.

    Main Results:

    • Successfully demonstrated a 10 Gb/s, 2-bit photonic DAC.
    • Converted a 10 Gb/s digital signal to a four-level amplitude analog signal.
    • Evaluated resolution using differential nonlinearity (DNL), integral nonlinearity (INL), and effective number of bits (ENOB).

    Conclusions:

    • The blue-chirp spectral slicing technique in SOAs is a viable method for photonic DACs.
    • The demonstrated photonic DAC achieves high-speed conversion with potential for high resolution.
    • This technique offers a promising approach for future optical signal processing applications.