Speckle wavemeter based on a multi-core fiber and compressive imaging

Area of Science:

• Optical Physics
• Fiber Optics
• Metrology

Background:

• Speckle patterns in multimode fibers (MMF) offer valuable light information.
• Traditional speckle-based spectrometers/wavemeters often rely on costly and slow cameras.
• Limitations of cameras hinder applications in optical communications, metrology, and sensing.

Purpose of the Study:

• To develop a cost-effective and robust wavemeter using fiber optics.
• To overcome the limitations of camera-based speckle analysis.
• To enhance wavelength measurement capabilities for optical sensing and metrology.

Main Methods:

• Fused a seven-core fiber (SCF) with an MMF to capture speckle patterns.
• Utilized SCF's space division multiplexing with an optical switch for diverse speckle generation.
• Employed a convolutional neural network (CNN) regression algorithm for speckle data analysis.

Main Results:

• Achieved high wavelength resolution, resolving adjacent wavelengths of 1 pm.
• Demonstrated a low measurement error of approximately 0.2 pm.
• Investigated the impact of MMF length on wavelength resolution.

Conclusions:

• Presented a robust and cost-effective wavelength measurement device.
• Successfully utilized SCF and CNN for advanced speckle analysis.
• The proposed method offers a viable alternative to camera-based systems for optical sensing.