Avoiding local minima in FROG retrievals with a convergence evaluation metric

Area of Science:

• Optics and Photonics
• Laser Physics
• Nonlinear Optics

Background:

• Accurate ultrashort laser pulse characterization is crucial for many scientific applications.
• Existing frequency-resolved optical gating (FROG) algorithms can suffer from local convergence, leading to inaccurate pulse reconstructions.
• Developing robust methods to overcome these limitations is an active area of research.

Purpose of the Study:

• To introduce a novel supervised evaluation step, the Sigma Check, for FROG algorithms.
• To detect and mitigate erroneous convergence to local minima in pulse retrieval.
• To enhance the overall accuracy and reliability of FROG-based ultrashort laser pulse reconstruction.

Main Methods:

• The Sigma Check evaluates discrepancies between measured and retrieved FROG spectrograms.
• Targeted perturbations are applied when significant spectral differences are identified.
• The method is integrated and tested with multiple FROG algorithms, including line-search FROG, extended ptychographic iterative engine, and principal components generalized projections algorithm.

Main Results:

• Numerical simulations and experimental measurements confirm the effectiveness of the Sigma Check.
• The Sigma Check significantly enhances retrieval accuracy across various tested FROG algorithms.
• The method provides a systematic approach to improving the fidelity of FROG pulse reconstructions.

Conclusions:

• The Sigma Check is a valuable addition to FROG algorithms, improving the accuracy of ultrashort laser pulse characterization.
• This novel evaluation step effectively addresses the challenge of local convergence in FROG.
• The Sigma Check offers a reliable strategy for more precise and robust pulse reconstruction.