Statistical analysis of stochastically generated free electron laser pulses

Self-amplified spontaneous-emission (SASE) x-ray free electron lasers (XFELs) produce extremely short light pulses with very high intensity, which are pushing the boundaries of the timescales for the types of dynamics we can probe in atoms and molecules. Because SASE pulses are generated from random noise, they are very different from shot to shot, but follow well-defined statistics on average. In this poster, I will present a python implementation of the partial-coherence model of [Opt. Lett. 35, 3441 (2010)], which uses a stochastic approach to efficiently simulate SASE FEL pulses. I will also present statistical analyses of these generated pulses to gain a better understanding of their temporal and spectral properties and validate this method. Building a better understanding of the properties of SASE pulses is crucial to make the most of experimental data and will help further x-ray enabled science.