Data Processing Pipeline For Tianlai Experiment
Shifan Zuo, Jixia Li, Yichao Li, Das Santanu, Albert Stebbins, Kiyoshi, W. Masui, Richard Shaw, Jiao Zhang, Fengquan Wu, Xuelei Chen

TL;DR
The paper presents 'tlpipe', a comprehensive data processing pipeline for the Tianlai 21cm intensity mapping experiment, addressing challenges in foreground removal, calibration, and large data volume handling to aid cosmological signal detection.
Contribution
It introduces new algorithms like eigenvector decomposition for calibration and Tikhonov regularization for m-mode analysis within a versatile processing pipeline.
Findings
Successful processing of real Tianlai data demonstrating pipeline capabilities.
Implementation of novel calibration and analysis algorithms.
Facilitates future improvements in 21cm cosmology data analysis.
Abstract
The Tianlai project is a 21cm intensity mapping experiment aimed at detecting dark energy by measuring the baryon acoustic oscillation (BAO) features in the large scale structure power spectrum. This experiment provides an opportunity to test the data processing methods for cosmological 21cm signal extraction, which is still a great challenge in current radio astronomy research. The 21cm signal is much weaker than the foregrounds and easily affected by the imperfections in the instrumental responses. Furthermore, processing the large volumes of interferometer data poses a practical challenge. We have developed a data processing pipeline software called {\tt tlpipe} to process the drift scan survey data from the Tianlai experiment. It performs offline data processing tasks such as radio frequency interference (RFI) flagging, array calibration, binning, and map-making, etc. It also…
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Taxonomy
TopicsRadio Astronomy Observations and Technology · Scientific Research and Discoveries · Astrophysics and Cosmic Phenomena
