Asynchronous nonlinear optical sampling with parallelized signal reconstruction.

Area of Science:

• Optoelectronics
• Signal Processing
• Computational Physics

Background:

• High-speed optical signals often exceed conventional electronic bandwidth limitations.
• Asynchronous sampling introduces challenges in signal reconstruction and synchronization.
• Efficient processing of long measurement records is crucial for advanced optical diagnostics.

Purpose of the Study:

• To develop a scalable software framework for synchronizing and reconstructing waveforms from asynchronous nonlinear optical sampling.
• To enable efficient processing of bandwidth-constrained, long optical measurement data.
• To achieve picosecond-scale temporal resolution for waveform-level diagnostics.

Main Methods:

• Utilizing nonlinear optical sampling with four-wave mixing and a low-bandwidth photodetector.
• Employing software-based resynchronization via spectral peak refinement and zero-padded Fourier transforms.
• Implementing parallel execution, including GPU acceleration, for efficient processing.

Main Results:

• Experimental validation using 10-GHz laser pulses and 10-Gb/s PRBS signals.
• Quantitative assessment of reconstruction quality (extinction ratio, Q-factor, pulse width, timing jitter).
• Demonstrated ~10x processing time reduction with GPU parallelization, enabling scalability to long datasets.

Conclusions:

• The developed framework provides a robust solution for asynchronous optical sampling reconstruction.
• Achieved picosecond temporal resolution is suitable for waveform-level diagnostics in ultra-high-speed communication systems.
• The software framework is inherently scalable and avoids iterative optimization, facilitating practical application.