Compact wavemeter incorporating femtosecond laser-induced surface nanostructures enabled by deep learning

Area of Science:

• Optics and Photonics
• Materials Science
• Nanotechnology

Background:

• Miniature spectrometers offer portability and ease of use in various settings.
• Light scattering through disordered media produces speckle patterns sensitive to wavelength, enabling wavemeter design.
• Developing compact, high-precision wavelength measurement tools is an ongoing challenge.

Purpose of the Study:

• To design and demonstrate a compact scattering wavelength meter.
• To utilize femtosecond laser-prepared nanostructures as an effective scattering medium for spectral dispersion.
• To achieve high measurement accuracy and robustness in a portable device.

Main Methods:

• Fabrication of a self-organized nanostructure (30-50 nm) on a sapphire surface using femtosecond laser ablation.
• Utilizing the nanostructure as a scattering medium to induce spectral dispersion.
• Collecting and analyzing speckle patterns with a neural network for wavelength extraction.

Main Results:

• Successfully designed a compact scattering wavelength meter with efficient scattering properties.
• Achieved a measurement accuracy of 10 picometers across multiple wavelength ranges.
• Demonstrated high robustness against instrument and environmental noise.

Conclusions:

• The developed scattering wavelength meter offers high precision and portability.
• The use of laser-prepared nanostructures is effective for inducing spectral dispersion.
• This work advances the development of compact, high-precision wavemeters for diverse applications.