Beam Profiling with Noise Reduction From Computer Vision and Principal Component Analysis for the MAGIS-100 Experiment
Abstract
MAGIS-100 is a long-baseline atom interferometer that operates as a quantum sensor. It will search for dark matter, probe fundamental quantum science, and serve as a prototype gravitational wave detector in the 0.3 to 3~Hz frequency range. The experiment uses light-pulse atom interferometry where pulses of light create the atom optics equivalents of beamsplitters and mirrors. Laser beam aberrations are a key source of systematic error for MAGIS-100, and accurately characterizing the laser beam spatial profile is therefore essential. In this paper, we describe a new and efficient beam profiling technique. We use a low-cost CMOS camera affixed to a translating and rotating optomechanical mount to image the beam, then employ computer vision and principal component analysis to minimize background noise and produce accurate beam profiles for a laser incident on a variety of aberration-inducing optical elements.
Cite
@article{arxiv.2203.03380,
title = {Beam Profiling with Noise Reduction From Computer Vision and Principal Component Analysis for the MAGIS-100 Experiment},
author = {Joseph Jachinowski and Natasha Sachdeva and Tim Kovachy},
journal= {arXiv preprint arXiv:2203.03380},
year = {2022}
}
Comments
6 pages, 4 figures, 2021 IEEE Conference on Antenna Measurements & Applications (CAMA)