31 August 2026 to 18 September 2026
Albano Building 3
Europe/Stockholm timezone

Application of Bayesian Inference to disentangle dust and CIB emission

17 Sept 2026, 14:30
15m
Albano Building 3

Albano Building 3

Hannes Alfvéns väg 12, 10691 Stockholm, Sweden

Speaker

Tuhin Ghosh (NISER Bhubaneswar)

Description

Galactic dust emission and Cosmic Infrared Background (CIB) anisotropies are the dominant foreground signals in CMB observations at frequencies above 217 GHz. Since Galactic dust and CIB exhibit a similar spectral energy distribution, separating the two components poses a significant challenge. A reliable estimate of the CIB map serves as an external tracer of the CMB lensing potential, which can aid in detecting the primordial scalar-to-tensor ratio (r) through the delensing process.

In our work, we employ a Bayesian inference framework to separate the dust and CIB emission, utilizing Galactic HI emission as an external tracer of the dust component. A key outcome of this study is the estimation of the zero offset levels of the Planck intensity maps, accounting for pixel-dependent dust emissivities. The offset values derived in this analysis are found to be in good agreement with the official Planck offset values up to 545 GHz, while showing notable discrepancies at the 857 GHz frequency band.

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