The Simons Observatory: Pipeline comparison and validation for large-scale B-modes

Kevin Wolz, Susanna Azzoni, Carlos Hervías-Caimapo, Josquin Errard, Nicoletta Krachmalnicoff, David Alonso, Carlo Baccigalupi, Antón Baleato Lizancos, Michael L. Brown, Erminia Calabrese, Jens Chluba, Jo Dunkley, Giulio Fabbian, Nicholas Galitzki, Baptiste Jost, Magdy Morshed, Federico Nati

Research output: Contribution to journalArticlepeer-review


Context. The upcoming Simons Observatory Small Aperture Telescopes aim at achieving a constraint on the primordial tensor-to-scalar ratio r at the level of σ (r = 0)≤0.003, observing the polarized CMB in the presence of partial sky coverage, cosmic variance, inhomogeneous non-white noise, and Galactic foregrounds. Aims. We present three different analysis pipelines able to constrain r given the latest available instrument performance, and compare their predictions on a set of sky simulations that allow us to explore a number of Galactic foreground models and elements of instrumental noise, relevant for the Simons Observatory. Methods. The three pipelines employ different combinations of parametric and non-parametric component separation at the map and power spectrum levels, and use B-mode purification to estimate the CMB B-mode power spectrum. We applied them to a common set of simulated realistic frequency maps, and compared and validated them with focus on their ability to extract robust constraints on the tensor-to-scalar ratio r. We evaluated their performance in terms of bias and statistical uncertainty on this parameter. Results. In most of the scenarios the three methodologies achieve similar performance. Nevertheless, several simulations with complex foreground signals lead to a > 2σ bias on r if analyzed with the default versions of these pipelines, highlighting the need for more sophisticated pipeline components that marginalize over foreground residuals. We show two such extensions, using power-spectrum-based and map-based methods, that are able to fully reduce the bias on r below the statistical uncertainties in all foreground models explored, at a moderate cost in terms of σ (r).

Original languageEnglish (US)
Article numberA16
JournalAstronomy and Astrophysics
StatePublished - Jun 1 2024

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science


  • Cosmic background radiation
  • Cosmological parameters
  • Early Universe
  • Inflation
  • Methods: data analysis
  • Methods: statistical


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