Quantitative Pulse Shape-Instability Analysis Using 2D-Runs FROG

TL;DR

This paper introduces a quantitative method using 2D runs FROG and the RANA algorithm to reliably detect and measure pulse-shape instability in laser pulse trains.

Contribution

It develops a new instability parameter R based on a 2D extension of the runs test, enabling systematic quantification of pulse-shape instability.

Findings

The R parameter effectively distinguishes stable from unstable pulse trains.

The method reliably detects systematic errors in 2D FROG traces.

The approach minimizes false positives from algorithm stagnation.

Abstract

We present a method for quantifying pulse-shape instability in a train of pulses using multi-shot Second-Harmonic-Generation Frequency-Resolved Optical Gating (SHG FROG). All versions of multi-shot FROG have previously shown the ability to distinguish stable from unstable pulse trains, as systematic differences appear between measured and retrieved traces when instability is present. This has proved possible because the recently introduced Retrieved-Amplitude N-grid Algorithmic (RANA) approach provides highly reliable pulse retrieval, even for unstable pulse trains and in the presence of noise, thus eliminating the possibility that algorithm stagnation, which mimics the effects of pulse-shape instability, could be confused for it. In other words, RANAs excellent performance ensures that any non-random discrepancies between measured and retrieved FROG traces reflect physical pulse-shape instability, rather than algorithmic stagnation. To begin to quantify such instability, we now introduce an instability parameter, R. It involves the use of the well-known statistical Runs test, which tests for systematic error in fits to one-dimensional (1D) data. A runs test counts the runs consecutive points in the plot of the difference between the data and fit with the same sign evaluating the goodness of the fit while minimizing the effects of random error. However, because FROG traces are functions of two variables, we must extend the usual 1D runs test to two dimensions, that is, to enumerate 2D runs hills and valleys in the difference between measured and retrieved 2D FROG traces. Many small 2D runs indicate only random noise-like differences and hence a stable pulse train, whereas few large runs reflect additional systematic error and hence pulse-shape instability.