Optimized fringe removal algorithm for absorption images

TL;DR

This paper introduces an optimized fringe removal algorithm for absorption imaging that reduces noise and improves measurement accuracy by generating ideal reference light fields and applying principal component analysis.

Contribution

The paper presents a novel algorithm that enhances absorption image quality by noise suppression and optimal reference field generation, outperforming conventional methods.

Findings

Reduces atomic temperature variance by over three times

Suppresses noise to the theoretical limit

Improves reliability of absorption imaging results

Abstract

Optical absorption imaging is a basic detection technique for obtaining information from matter waves, in which the absorption signal can be obtained by comparing the recorded detection light field with the light field in the presence of absorption, thereby giving the spatial distribution of the atoms. The noise in detection arises mainly from differences between the two recorded light field distributions, which is difficult to avoid in experiments. In this work, we present an optimized fringe removal algorithm, developing a method to generate an ideal reference light field, avoiding the noise generated by the light field difference, and suppressing the noise signal to the theoretical limit. Using principal component analysis, we explore the optimal calculation area and how to remove noise information from the basis to allow optimal performance and speed. As an example, we consider scattering atomic peaks with a small number of atoms in a triangular lattice. Compared with the conventional processing method, our algorithm can reduce the measured atomic temperature variance by more than three times, giving a more reliable result.