SIMBAD references

2024PASP..136a5001R - Publ. Astron. Soc. Pac., 136, part no 1, 5001 (2024/January-0)

NSClean: An Algorithm for Removing Correlated Noise from JWST NIRSpec Images.

RAUSCHER B.J.

Abstract (from CDS):

NSClean is an algorithm and python package for removing faint vertical banding and “picture frame noise” from JWST Near Infrared Spectrograph (NIRSpec) images. NSClean uses known dark areas to fit a background model to each exposure in Fourier space. When the model is subtracted, it removes nearly all correlated noise. Compared to simpler strategies like subtracting the rolling median, NSClean is more thorough and uniform. NSClean has been developed and tested for NIRSpec IFU mode data, although it can be used on other NIRSpec modes as well. NSClean is computationally undemanding, requiring only a few seconds to clean an image on a typical laptop. The NSClean package is freely available from the NASA JWST website.

Abstract Copyright: © 2024. The Author(s). Published by IOP Publishing Ltd on behalf of the Astronomical Society of the Pacific (ASP). All rights reserved

Journal keyword(s): Astronomical instrumentation - Calibration - Algorithms - Analytical mathematics - Astronomical detectors

Status at CDS : Objects in title, abstract, text, figures, and all or part of small table(s) being processed in SIMBAD.

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