Remote dispersion scan: transformer-network retrieval of ultrafast pulses after non-linear propagation

TL;DR

This paper introduces a transformer neural network-based remote dispersion scan method for ultrafast pulse characterization, enabling accurate, real-time measurement of femtosecond laser pulses at the interaction site with minimal setup complexity.

Contribution

The work presents a novel remote pulse characterization technique using a transformer neural network, reducing the need for extensive scanning and enabling live-view ultrafast pulse measurement.

Findings

Reconstruction accuracy comparable to full 2D scans.

Successful experimental compression of a 1.3 ps pulse to 100 fs.

Robust, alignment-insensitive measurement method.

Abstract

Accurate and rapid characterization of broadband electric fields is essential for all ultrafast applications and remains an active field of research. In this work, we introduce remote dispersion scan, a transformer neural network enabled dispersion scan based pulse characterization method that can characterize femtosecond laser pulses. A local scan of the non-linear spectral phase before several linear and nonlinear processes, including amplification, compression, and self phase modulation, allows for the field retrieval remotely at the interaction region. We show that the reconstruction accuracy obtained from a single measurement of the fundamental and second harmonic is comparable to that of a full two dimensional scan. We confirm the technique experimentally by compressing a 300 W, 1.3 ps, 1030 nm pulse in a hollow core fiber to 100 fs and measuring the fundamental and second harmonic spectra while scanning the second order phase in a pulse shaper before power amplification. These results establish a simple, robust, alignment insensitive live-view pulse reconstruction modality.