BEYONDPLANCK II. CMB mapmaking through Gibbs sampling
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 advantagesmore »
- Authors:
-
[1];
more »
- University of Helsinki (Finland)
- University of Oslo (Norway)
- Università degli Studi di Milano (Italy); Istituto Nazionale di Astrofisica (INAF)/Istituto di Astrofisica Spaziale e Fisica (IASF), Milano (Italy); Istituto Nazionale di Fisica Nucleare (INFN), Milano (Italy)
- Istituto Nazionale di Astrofisica (INAF), Trieste (Italy)
- Planetek Hellas, Marousi (Greece)
- Università degli Studi di Milano (Italy)
- Università degli Studi di Milano (Italy); Istituto Nazionale di Fisica Nucleare (INFN), Milano (Italy)
- Princeton University, NJ (United States)
- California Institute of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Laboratory (JPL)
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Computational Cosmology Center
- Haverford College Astronomy Department, PA (United States)
- Max-Planck-Institut für Astrophysik, Garching (Germany)
- Istituto Nazionale di Astrofisica (INAF), Trieste (Italy); Università degli Studi di Trieste (Italy)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), High Energy Physics (HEP); Academy of Finland; Research Council of Norway (RCN)
- OSTI Identifier:
- 2234090
- Grant/Contract Number:
- AC02-05CH11231; 295113; 263011; 274990
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Astronomy and Astrophysics
- Additional Journal Information:
- Journal Volume: 675; Journal ID: ISSN 0004-6361
- Publisher:
- EDP Sciences
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; 79 ASTRONOMY AND ASTROPHYSICS; cosmic background radiation; methods: numerical; methods: data analysis
Citation Formats
Keihänen, Elina, Suur-Uski, A. -S., Andersen, K. J., Aurlien, R., Banerji, R., Basyrov, A., Bersanelli, M., Bertocco, S., Brilenkov, M., Carbone, M., Colombo, L. P. L., Eriksen, H. K., Eskilt, J. R., Foss, M. K., Franceschet, C., Fuskeland, U., Galeotta, S., Galloway, M., Gerakakis, S., Gjerløw, E., Hensley, B., Herman, D., Iacobellis, M., Ieronymaki, M., Ihle, H. T., Jewell, J. B., Karakci, A., Keskitalo, R., Maggio, G., Maino, D., Maris, M., Mennella, A., Paradiso, S., Partridge, B., Reinecke, M., San, M., Svalheim, T. L., Tavagnacco, D., Thommesen, H., Watts, D. J., Wehus, I. K., and Zacchei, A. BEYONDPLANCK II. CMB mapmaking through Gibbs sampling. United States: N. p., 2023.
Web. doi:10.1051/0004-6361/202142799.
Keihänen, Elina, Suur-Uski, A. -S., Andersen, K. J., Aurlien, R., Banerji, R., Basyrov, A., Bersanelli, M., Bertocco, S., Brilenkov, M., Carbone, M., Colombo, L. P. L., Eriksen, H. K., Eskilt, J. R., Foss, M. K., Franceschet, C., Fuskeland, U., Galeotta, S., Galloway, M., Gerakakis, S., Gjerløw, E., Hensley, B., Herman, D., Iacobellis, M., Ieronymaki, M., Ihle, H. T., Jewell, J. B., Karakci, A., Keskitalo, R., Maggio, G., Maino, D., Maris, M., Mennella, A., Paradiso, S., Partridge, B., Reinecke, M., San, M., Svalheim, T. L., Tavagnacco, D., Thommesen, H., Watts, D. J., Wehus, I. K., & Zacchei, A. BEYONDPLANCK II. CMB mapmaking through Gibbs sampling. United States. https://doi.org/10.1051/0004-6361/202142799
Keihänen, Elina, Suur-Uski, A. -S., Andersen, K. J., Aurlien, R., Banerji, R., Basyrov, A., Bersanelli, M., Bertocco, S., Brilenkov, M., Carbone, M., Colombo, L. P. L., Eriksen, H. K., Eskilt, J. R., Foss, M. K., Franceschet, C., Fuskeland, U., Galeotta, S., Galloway, M., Gerakakis, S., Gjerløw, E., Hensley, B., Herman, D., Iacobellis, M., Ieronymaki, M., Ihle, H. T., Jewell, J. B., Karakci, A., Keskitalo, R., Maggio, G., Maino, D., Maris, M., Mennella, A., Paradiso, S., Partridge, B., Reinecke, M., San, M., Svalheim, T. L., Tavagnacco, D., Thommesen, H., Watts, D. J., Wehus, I. K., and Zacchei, A. Wed .
"BEYONDPLANCK II. CMB mapmaking through Gibbs sampling". United States. https://doi.org/10.1051/0004-6361/202142799. https://www.osti.gov/servlets/purl/2234090.
@article{osti_2234090,
title = {BEYONDPLANCK II. CMB mapmaking through Gibbs sampling},
author = {Keihänen, Elina and Suur-Uski, A. -S. and Andersen, K. J. and Aurlien, R. and Banerji, R. and Basyrov, A. and Bersanelli, M. and Bertocco, S. and Brilenkov, M. and Carbone, M. and Colombo, L. P. L. and Eriksen, H. K. and Eskilt, J. R. and Foss, M. K. and Franceschet, C. and Fuskeland, U. and Galeotta, S. and Galloway, M. and Gerakakis, S. and Gjerløw, E. and Hensley, B. and Herman, D. and Iacobellis, M. and Ieronymaki, M. and Ihle, H. T. and Jewell, J. B. and Karakci, A. and Keskitalo, R. and Maggio, G. and Maino, D. and Maris, M. and Mennella, A. and Paradiso, S. and Partridge, B. and Reinecke, M. and San, M. and Svalheim, T. L. and Tavagnacco, D. and Thommesen, H. and Watts, D. J. and Wehus, I. K. and Zacchei, A.},
abstractNote = {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 BEYONDPLANCK framework, which implements the first end-to-end Bayesian analysis pipeline for CMB observations.},
doi = {10.1051/0004-6361/202142799},
journal = {Astronomy and Astrophysics},
number = ,
volume = 675,
place = {United States},
year = {Wed Jun 28 00:00:00 EDT 2023},
month = {Wed Jun 28 00:00:00 EDT 2023}
}
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