dc.date.accessioned | 2023-09-15T16:33:38Z | |
dc.date.available | 2023-09-15T16:33:38Z | |
dc.date.created | 2023-09-01T10:57:36Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Keihänen, Elina Suur-Uski, A.-S. Andersen, Kristian Joten Aurvik, Ragnhild Banerji, Ranajoy Basyrov, Artem Bersanelli, M. Bertocco, S. Brilenkov, Maksym Carbone, M. Colombo, L.P.L. Eriksen, Hans Kristian Kamfjord Eskilt, Johannes Røsok Foss, Marie Kristine Franceschet, C. Fuskeland, Unni Galeotta, S. Galloway, Mathew Gerakakis, S. Gjerløw, Eirik Hensley, B. Herman, Daniel Christopher Iacobellis, M. Ieronymaki, M. Ihle, Håvard Tveit Jewell, J.B. Karakci, Ata Keskitalo, R. Maggio, G. Maino, D. Maris, M. Mennella, A. Paradiso, S. Partridge, B. Reinecke, M. San, Metin Svalheim, Trygve Leithe Tavagnacco, D. Thommesen, Harald Watts, Duncan Wehus, Ingunn Kathrine Zacchei, A. . BeyondPlanck: II. CMB mapmaking through Gibbs sampling. Astronomy and Astrophysics (A & A). 2023, 675 | |
dc.identifier.uri | http://hdl.handle.net/10852/105048 | |
dc.description.abstract | We present a Gibbs sampling solution to the mapmaking problem for cosmic microwave background (CMB) measurements that builds on existing destriping methodology. Gibbs sampling breaks the computationally heavy destriping problem into two separate steps: noise filtering and map binning. Considered as two separate steps, both are computationally much cheaper than solving the combined problem. This provides a huge performance benefit as compared to traditional methods and it allows us, for the first time, to bring the destriping baseline length to a single sample. Here, we applied the Gibbs procedure to simulated Planck 30 GHz data. We find that gaps in the time-ordered data are handled efficiently by filling them in with simulated noise as part of the Gibbs process. The Gibbs procedure yields a chain of map samples, from which we are able to compute the posterior mean as a best-estimate map. The variation in the chain provides information on the correlated residual noise, without the need to construct a full noise covariance matrix. However, if only a single maximum-likelihood frequency map estimate is required, we find that traditional conjugate gradient solvers converge much faster than a Gibbs sampler in terms of the total number of iterations. The conceptual advantages of the Gibbs sampling approach lies in statistically well-defined error propagation and systematic error correction. This methodology thus forms the conceptual basis for the mapmaking algorithm employed in the B EYOND P LANCK framework, which implements the first end-to-end Bayesian analysis pipeline for CMB observations. | |
dc.language | EN | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.title | BeyondPlanck: II. CMB mapmaking through Gibbs sampling | |
dc.title.alternative | ENEngelskEnglishBeyondPlanck: II. CMB mapmaking through Gibbs sampling | |
dc.type | Journal article | |
dc.creator.author | Keihänen, Elina | |
dc.creator.author | Suur-Uski, A.-S. | |
dc.creator.author | Andersen, Kristian Joten | |
dc.creator.author | Aurvik, Ragnhild | |
dc.creator.author | Banerji, Ranajoy | |
dc.creator.author | Basyrov, Artem | |
dc.creator.author | Bersanelli, M. | |
dc.creator.author | Bertocco, S. | |
dc.creator.author | Brilenkov, Maksym | |
dc.creator.author | Carbone, M. | |
dc.creator.author | Colombo, L.P.L. | |
dc.creator.author | Eriksen, Hans Kristian Kamfjord | |
dc.creator.author | Eskilt, Johannes Røsok | |
dc.creator.author | Foss, Marie Kristine | |
dc.creator.author | Franceschet, C. | |
dc.creator.author | Fuskeland, Unni | |
dc.creator.author | Galeotta, S. | |
dc.creator.author | Galloway, Mathew | |
dc.creator.author | Gerakakis, S. | |
dc.creator.author | Gjerløw, Eirik | |
dc.creator.author | Hensley, B. | |
dc.creator.author | Herman, Daniel Christopher | |
dc.creator.author | Iacobellis, M. | |
dc.creator.author | Ieronymaki, M. | |
dc.creator.author | Ihle, Håvard Tveit | |
dc.creator.author | Jewell, J.B. | |
dc.creator.author | Karakci, Ata | |
dc.creator.author | Keskitalo, R. | |
dc.creator.author | Maggio, G. | |
dc.creator.author | Maino, D. | |
dc.creator.author | Maris, M. | |
dc.creator.author | Mennella, A. | |
dc.creator.author | Paradiso, S. | |
dc.creator.author | Partridge, B. | |
dc.creator.author | Reinecke, M. | |
dc.creator.author | San, Metin | |
dc.creator.author | Svalheim, Trygve Leithe | |
dc.creator.author | Tavagnacco, D. | |
dc.creator.author | Thommesen, Harald | |
dc.creator.author | Watts, Duncan | |
dc.creator.author | Wehus, Ingunn Kathrine | |
dc.creator.author | Zacchei, A. | |
cristin.unitcode | 185,15,3,0 | |
cristin.unitname | Institutt for teoretisk astrofysikk | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |
dc.identifier.cristin | 2171587 | |
dc.identifier.bibliographiccitation | info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Astronomy and Astrophysics (A & A)&rft.volume=675&rft.spage=&rft.date=2023 | |
dc.identifier.jtitle | Astronomy and Astrophysics (A & A) | |
dc.identifier.volume | 675 | |
dc.identifier.pagecount | 11 | |
dc.identifier.doi | https://doi.org/10.1051/0004-6361/202142799 | |
dc.subject.nvi | VDP::Astrofysikk, astronomi: 438 | |
dc.type.document | Tidsskriftartikkel | |
dc.type.peerreviewed | Peer reviewed | |
dc.source.issn | 0004-6361 | |
dc.type.version | PublishedVersion | |
cristin.articleid | A2 | |