标题： 天籁实验的数据处理流程 显示英文标题

标题： Data Processing Pipeline For Tianlai Experiment

摘要： 天籁项目是一个21厘米强度映射实验，旨在通过测量大尺度结构功率谱中的重子声学振荡（BAO）特征来探测暗能量。 该实验为测试宇宙学21厘米信号提取的数据处理方法提供了一个机会，这仍然是当前射电天文学研究中的一个重大挑战。 21厘米信号比前景噪声要弱得多，并且容易受到仪器响应不完善的影响。 此外，处理大量干涉仪数据带来了实际挑战。 我们开发了一种名为{\tt tlpipe}的数据处理管道软件，用于处理天籁实验的漂移扫描观测数据。 它执行离线数据处理任务，如射频干扰（RFI）标记、阵列校准、分箱和地图制作等。 它还包括数据分析所需的各种实用功能，如数据选择、转换、可视化等。 实现了一些新算法，例如用于阵列校准的特征向量分解方法和用于$m$模分析的Tikhonov正则化。 在本文中，我们描述了{\tt tlpipe}的设计和实现，并通过一些真实数据的分析来说明其功能。 最后，我们概述了该公开代码未来发展的方向。 显示英文摘要

摘要： 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 $m$-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.