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May 9, 20260 citations

Combining cosmic microwave background datasets with consistent foreground modelling

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MTM. TristramMDM. DouspisAGA. Gorce

Key Points

  • This analysis aims to improve the estimation of cosmological parameters by combining CMB datasets and modeling foregrounds.
  • Jointly model temperature and polarisation power spectra with data from multiple telescopes.
  • Construct a unified likelihood to account for foregrounds and instrumental systematics.
  • Marginalise over foreground template choices to enhance parameter estimation.
  • LCDM parameters remain stable under varying foreground models.
  • Uncertainties in cosmological extensions increase by up to 35% in the neutrino sector after foreground adjustment.
  • Foreground parameter determinations are significantly influenced by assumptions about the underlying models.

Abstract

We present a joint cosmological analysis combining data from the satellite, the Atacama Cosmology Telescope, and the South Pole Telescope. We construct a unified likelihood that reproduces the measured temperature and polarisation power spectra by jointly modelling the cosmic microwave background (CMB) signal, Galactic and extragalactic foregrounds, and instrumental systematics across all datasets. We reduce reliance on external priors by combining datasets and improve the robustness of parameter estimation by marginalising over the choice of foreground templates. Within this joint analysis, łcdm parameters exhibit remarkable stability with respect to variations in foreground modelling. Parameters for cosmological extensions are more sensitive to these assumptions, with uncertainties increased by up to 35% in the neutrino sector after marginalising over foreground models. In contrast, the determination of foreground parameters depends more strongly on the assumptions made about the underlying foreground models. Overall, this work demonstrates the feasibility and reliability of a fully joint analysis of current CMB experiments and emphasises the importance of consistent and accurate foreground modelling for the scientific goals of next-generation, high-sensitivity CMB surveys.

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Cite This Study

Tristram et al. (2026) studied this question.

synapsesocial.com/papers/69fecfafb9154b0b82876b32https://doi.org/10.1051/0004-6361/202558015/pdf
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