Double-subdivision vortex beam interferometer enhanced by DenseNet for precision displacement measurement

Area of Science:

• Optical Metrology
• Precision Measurement
• Deep Learning Applications

Background:

• Accurate micro-displacement measurement is critical in fields like semiconductor manufacturing and nanotechnology.
• Traditional interferometers face limitations in sensitivity and robustness against optical perturbations.

Purpose of the Study:

• To develop a high-precision micro-displacement measurement system.
• To enhance measurement sensitivity and accuracy using optical amplification and advanced signal processing.

Main Methods:

• A double-subdivision conjugate vortex beam interferometer with polarization modulation and a double-reflection configuration was designed.
• A DenseNet-169 deep learning model was employed for robust fringe demodulation and displacement decoding.
• The system leverages the linear relationship between fringe rotation and displacement.

Main Results:

• The interferometer achieved doubled sensitivity and produced high-contrast displacement feature maps.
• The DenseNet framework effectively preserved subtle rotational features and mitigated optical perturbations.
• Experimental results showed an average absolute error of 0.33 nm within a 1 µm range, demonstrating sub-nanometer precision.

Conclusions:

• The integrated system offers a promising non-contact solution for precision metrology.
• The combination of optical amplification and deep learning significantly improves displacement measurement accuracy and reliability.