Gaussian process regression for foreground removal in hi intensity mapping experiments

Simple item page
dc.contributor.authorSoares, Paula S.
dc.contributor.authorWatkinson, Catherine A.
dc.contributor.authorPourtsidou, Alkistis
dc.date.accessioned2022-10-06T09:56:17Z
dc.date.available2022-10-06T09:56:17Z
dc.date.issued2022
dc.description.abstractWe apply for the first time Gaussian Process Regression (GPR) as a foreground removal technique in the context of single-dish, low redshift H I intensity mapping, and present an open-source PYTHON toolkit for doing so. We use MeerKAT and SKA1-MID-like simulations of 21 cm foregrounds (including polarization leakage), H I cosmological signal, and instrumental noise. We find that it is possible to use GPR as a foreground removal technique in this context, and that it is better suited in some cases to recover the H I power spectrum than principal component analysis (PCA), especially on small scales.en_US
dc.identifier.citationSoares, P. S. et al. (2022). Gaussian process regression for foreground removal in hi intensity mapping experiments. Monthly Notices of the Royal Astronomical Society, 510,(4), 5872–5890. https://doi.org/10.1093/mnras/stab2594en_US
dc.identifier.issn1365-2966
dc.identifier.urihttps://doi.org/10.1093/mnras/stab2594
dc.identifier.urihttp://hdl.handle.net/10566/8026
dc.language.isoenen_US
dc.publisherOxford University Pressen_US
dc.subjectAstronomyen_US
dc.subjectAstrophysicsen_US
dc.subjectCosmologyen_US
dc.subjectRadio linesen_US
dc.subjectMeerKATen_US
dc.titleGaussian process regression for foreground removal in hi intensity mapping experimentsen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
soares_gaussian process regression_2022.pdf
Size:
2.71 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Research Articles (Physics)