Removing correlated noise stripes from the Nancy Grace Roman Space Telescope survey images
Katherine Laliotis, Christopher M. Hirata, Emily Macbeth, Kaili Cao

TL;DR
This paper introduces imDestripe, a Python tool that effectively removes correlated noise stripes from Roman Space Telescope images, significantly improving the quality of weak lensing measurements by suppressing noise artifacts.
Contribution
The paper presents a novel Python module, imDestripe, which uses multiple roll angles and linear algebra to remove correlated noise stripes from space telescope images.
Findings
Power spectrum of banding suppressed by factors of 10-30
Effective removal of correlated noise in simulated images
Potential for improved weak lensing measurements
Abstract
Weak gravitational lensing has emerged as a powerful tool for investigating the matter distribution in the Universe and how it has evolved over cosmic time. The Wide Field Instrument (WFI) on the Nancy Grace Roman Space Telescope (Roman) will deliver some of the highest precision measurements of weak lensing ever made. Since weak lensing is based on statistics of faint sources, it can be biased by even tiny instrument systematics, including correlated read noise. Previous works have shown the infrared detectors used in the Roman WFI show correlations in their noise fields at a level significant for weak lensing measurements, even after application of standard reference pixel corrections; of particular concern is 1/f noise, which appears as horizontal banding in the detector frame. In this paper, we present imDestripe: a new Python module utilizing the multiple roll angles in Roman's…
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Taxonomy
TopicsPulsars and Gravitational Waves Research · Galaxies: Formation, Evolution, Phenomena · Astronomy and Astrophysical Research
