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BEYONDPLANCK

Authors :
Galloway, M
Galloway, M
Reinecke, M
Andersen, KJ
Aurlien, R
Banerji, R
Bersanelli, M
Bertocco, S
Brilenkov, M
Carbone, M
Colombo, LPL
Eriksen, HK
Eskilt, JR
Foss, MK
Franceschet, C
Fuskeland, U
Galeotta, S
Gerakakis, S
Gjerløw, E
Hensley, B
Herman, D
Iacobellis, M
Ieronymaki, M
Ihle, HT
Jewell, JB
Karakci, A
Keihänen, E
Keskitalo, R
Maggio, G
Maino, D
Maris, M
Mennella, A
Paradiso, S
Partridge, B
San, M
Suur-Uski, A-S
Svalheim, TL
Tavagnacco, D
Thommesen, H
Watts, DJ
Wehus, IK
Zacchei, A
Galloway, M
Galloway, M
Reinecke, M
Andersen, KJ
Aurlien, R
Banerji, R
Bersanelli, M
Bertocco, S
Brilenkov, M
Carbone, M
Colombo, LPL
Eriksen, HK
Eskilt, JR
Foss, MK
Franceschet, C
Fuskeland, U
Galeotta, S
Gerakakis, S
Gjerløw, E
Hensley, B
Herman, D
Iacobellis, M
Ieronymaki, M
Ihle, HT
Jewell, JB
Karakci, A
Keihänen, E
Keskitalo, R
Maggio, G
Maino, D
Maris, M
Mennella, A
Paradiso, S
Partridge, B
San, M
Suur-Uski, A-S
Svalheim, TL
Tavagnacco, D
Thommesen, H
Watts, DJ
Wehus, IK
Zacchei, A
Publication Year :
2023

Abstract

We introduce a new formulation of the Conviqt convolution algorithm in terms of spin harmonics, and apply this to the problem of sidelobe correction for BEYONDPLANCK, the first end-to-end Bayesian Gibbs sampling framework for CMB analysis. We compare our implementation to the previous Planck LevelS implementation, and find good agreement between the two codes in terms of accuracy, but with a speed-up reaching a factor of 3-10, depending on the frequency bandlimits, lmax and mmax. The new algorithm is significantly simpler to implement and maintain, since all low-level calculations are handled through an external spherical harmonic transform library. We find that our mean sidelobe estimates for Planck LFI are in good agreement with previous efforts. Additionally, we present novel sidelobe rms maps that quantify the uncertainty in the sidelobe corrections due to variations in the sky model.

Details

Database :
OAIster
Notes :
application/pdf
Publication Type :
Electronic Resource
Accession number :
edsoai.on1410330879
Document Type :
Electronic Resource