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Electronic Distance Measuring Instruments01:30

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Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over short distances...

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    Area of Science:

    • Photonics and Materials Science
    • Optical Computing
    • Nonvolatile Memory Devices

    Background:

    • Optical neural networks (ONNs) require energy-efficient and scalable computing cores.
    • Existing solutions face challenges in reconfigurability and power consumption.
    • Phase-change materials offer promising nonvolatile characteristics for optical devices.

    Purpose of the Study:

    • To introduce a programmable nonvolatile convolutional core for optical computing.
    • To leverage sub-wavelength phase-change digital meta-surfaces for enhanced performance.
    • To enable energy-efficient and scalable optical neural networks.

    Main Methods:

    • Utilized sub-wavelength Sb2Se3 cylindrical arrays for meta-surface fabrication.
    • Implemented a digital architecture for nonvolatile programmability.
    • Employed laser direct-writing techniques for system validation and trimming.

    Main Results:

    • Achieved enhanced weight distinguishability and reduced insertion loss.
    • Demonstrated a wide weight range (0.1 to 0.93) with over six levels per unit.
    • Validated 2-bit digital reconfigurability and post-trimming functionality with zero static power.

    Conclusions:

    • The developed convolutional core offers a promising pathway for high-accuracy optical computing.
    • Integration of phase-change materials and digital architectures addresses key ONN requirements.
    • This technology enables scalable and energy-efficient solutions for applications like image recognition.