Revealing buried information: Statistical processing techniques for ultracold gas image analysis

TL;DR

This paper applies principal and independent component analysis to ultracold atom images, enabling rapid, model-independent extraction of phase information crucial for calibration and phase analysis in BEC interferometry.

Contribution

It introduces the use of PCA and ICA techniques for ultracold gas image analysis, providing algorithms for phase determination and experiment calibration.

Findings

Effective phase extraction from large image sets

Improved calibration of ultracold atom experiments

Insights into phase randomization phenomena

Abstract

The techniques of principal and independent component analysis are applied to images of ultracold atoms. As an illustrative example, we present the use of these model-independent methods to rapidly determine the differential phase of a BEC interferometer from large sets of images of interference patterns. These techniques have been useful in the calibration of the experiment and in the investigation of phase randomization. The details of the algorithms are provided.