Laser Pulse Duration Optimization With Numerical Methods

TL;DR

This paper investigates numerical optimization techniques like gradient descent, Bayesian Optimization, and genetic algorithms to minimize laser pulse duration using a feedback loop and semi-physical laser models.

Contribution

It introduces a systematic approach combining multiple iterative algorithms for optimizing laser pulse duration with a semi-physical simulation model.

Findings

Gradient descent effectively reduces pulse duration.

Bayesian Optimization finds optimal parameters efficiently.

Genetic algorithms explore diverse solutions.

Abstract

In this study we explore the optimization of laser pulse duration to obtain the shortest possible pulse. We do this by employing a feedback loop between a pulse shaper and pulse duration measurements. We apply to this problem several iterative algorithms including gradient descent, Bayesian Optimization and genetic algorithms, using a simulation of the actual laser represented via a semi-physical model of the laser based on the process of linear and non-linear phase accumulation.