Data Processing Pipeline For Tianlai Experiment
arXiv:2011.10757 · doi:10.1016/j.ascom.2020.100439
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 includes utility functions needed for the data analysis, such as data selection, transformation, visualization and others. A number of new algorithms are implemented, for example the eigenvector decomposition method for array calibration and the Tikhonov regularization for -mode analysis. In this paper we describe the design and implementation of the {\tt tlpipe} and illustrate its functions with some analysis of real data. Finally, we outline directions for future development of this publicly code.
arXiv comment13 pages, 5 figures, accepted for publication on Astronomy and Computing
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Cited by in corpus (7)
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- Emission-line Stacking of 21cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
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