Performance forecasts for the primordial gravitational wave detection pipelines for AliCPT-1
Shamik Ghosh, Yang Liu, Le Zhang, Siyu Li, Junzhou Zhang, Jiaxin Wang,, Jiazheng Dou, Jiming Chen, Jacques Delabrouille, Mathieu Remazeilles, Chang, Feng, Bin Hu, Zhi-Qi Huang, Hao Liu, Larissa Santos, Pengjie Zhang, Zhaoxuan, Zhang, Wen Zhao, Hong Li, Xinmin Zhang

TL;DR
This paper evaluates the performance of different data analysis pipelines for detecting primordial gravitational waves via CMB B-mode polarization with AliCPT-1, demonstrating consistent sensitivity around 0.02 in tensor-to-scalar ratio estimation.
Contribution
It compares five different pipelines for component separation and parameter estimation, showing their robustness and potential for precise PGW detection with AliCPT-1.
Findings
Pipelines achieve sensitivity of σ(r) ≈ 0.02.
Consistent constraints across different analysis methods.
Effective handling of systematics enhances detection robustness.
Abstract
AliCPT is the first Chinese cosmic microwave background (CMB) experiment which will make the most precise measurements of the CMB polarization in the northern hemisphere. The key science goal for AliCPT is the detection of primordial gravitational waves (PGWs). It is well known that an epoch of cosmic inflation, in the very early universe, can produce PGWs, which leave an imprint on the CMB in form of odd parity -mode polarization. In this work, we study the performance of the component separation and parameter estimation pipelines in context of constraining the value of the tensor-to-scalar ratio. Based on the simulated data for one observation season, we compare five different pipelines with different working principles. Three pipelines perform component separation at map or spectra level before estimating from the cleaned spectra, while the other two pipelines performs a…
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