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Testing the ABS method with the simulated Planck temperature maps

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arxiv 1807.07016 v2 pith:K5NTQW4V submitted 2018-07-18 astro-ph.CO

Testing the ABS method with the simulated Planck temperature maps

classification astro-ph.CO
keywords mapsmicrowaveplanckpowerspectrumapplyapproachcases
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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In this study, we apply the Analytical method of Blind Separation (ABS) of the cosmic microwave background (CMB) from foregrounds to estimate the CMB temperature power spectrum from multi-frequency microwave maps. We test the robustness of the ABS estimator and assess the accuracy of the power spectrum recovery by using realistic simulations based on the seven-frequency Planck data, including various frequency-dependent and spatially-varying foreground components (synchrotron, free-free, thermal dust and anomalous microwave emission), as well as an uncorrelated Gaussian-distributed instrumental noise. Considering no prior information about the foregrounds, the ABS estimator can analytically recover the CMB power spectrum over almost all scales with less than $0.5\%$ error for maps where the Galactic plane region ($|b|<10^{\circ}$) is masked out. To further test the flexibility and effectiveness of the ABS approach in a variety of situations, we apply the ABS to the simulated Planck maps in three cases: (1) without any mask, (2) imposing a two-times-stronger synchrotron emission and (3) including only the Galactic plane region ($|b|<10^{\circ}$) in the analysis. In such extreme cases, the ABS approach can still provide an unbiased estimate of band powers at the level of 1 $\mu\rm{K}^2$ on average over all $\ell$ range, and the recovered powers are consistent with the input values within 1-$\sigma$ for most $\ell$ bins.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Reconstructing the Thermal Sunyaev Zeldovich Power Spectrum from Planck using the ABS Method

    astro-ph.CO 2024-12 unverdicted novelty 6.0

    The ABS method applied to Planck PR3 data yields a tSZ power spectrum amplitude 34% lower than the Planck 2015 best-fit when trispectrum is included.

  2. Fast End-to-End Framework for Cosmological Parameter Inference from CMB Data Using Machine Learning

    astro-ph.CO 2025-11 conditional novelty 5.0

    An ABS+neural-network pipeline recovers τ and r from simulated CMB maps for LiteBIRD/PICO with reported 1-σ errors of 0.0030–0.0035 (τ) and 0.0014–0.0056 (r), using held-out cosmologies sampled inside the training range.