Self-referenced spectral interferometry for ultra-short laser pulse characterization

For ultrashort laser pulses, accurately characterizing their temporal characteristics (temporal width and phase) is crucial for their generation and application. Self-referenced spectral interferometry (SRSI), first proposed in 2010, utilizes the measured light itself to generate suitable reference light through third-order nonlinear optical processes, and employs Fourier transform spectral interferometry algorithms to reconstruct the input pulse. It has the advantages of single-shot, accuracy, and high sensitivity. This article provides an overview of the implementation of SRSI from two main aspects: the optical path and the reconstruction algorithm. On the optical path level, from the earliest proposed self-referenced spectral interferometry based on cross-polarization wave generation (XPW-SRSI) to the self-referenced spectral interferometry based on transient grating effect (TG-SRSI) with a compact total reflection configuration, the sensitivity, wavelength coverage, and compactness of the implementation path have been continuously iteratively upgraded. On the algorithm level, from pulse reconstruction methods targeting near Fourier transform limits to reconstruction algorithms for large chirp pulses with temporal broadening exceeding twice the Fourier transform limit, three evolutionary paths are discussed: spectral stitching schemes, reconstruction schemes incorporating supervised deep learning, and neural networks without training embedded in physical forward models. The latter achieves single-shot accurate reconstruction in large chirp and high noise scenarios without any pre-training dataset. In the face of emerging new beam characterization demands, the temporal measurement of ultrashort laser pulses still require significant attention in the future.