TL;DR
This paper introduces two open-source Python packages, HIDE and SEEK, designed to simulate and process radio survey data, enabling better understanding of systematic effects and improving data analysis pipelines for upcoming large-scale radio surveys.
Contribution
The paper presents novel, modular tools for end-to-end simulation and processing of radio survey data, adaptable to different instruments and datasets.
Findings
Successful application to a Galactic survey at 990-1260 MHz
Achieved median SNR of 5-6 in clean channels
Identified challenges with RFI contamination and baseline removal
Abstract
As several large single-dish radio surveys begin operation within the coming decade, a wealth of radio data will become available and provide a new window to the Universe. In order to fully exploit the potential of these data sets, it is important to understand the systematic effects associated with the instrument and the analysis pipeline. A common approach to tackle this is to forward-model the entire system - from the hardware to the analysis of the data products. For this purpose, we introduce two newly developed, open-source Python packages: the HI Data Emulator (HIDE) and the Signal Extraction and Emission Kartographer (SEEK) for simulating and processing single-dish radio survey data. HIDE forward-models the process of collecting astronomical radio signals in a single-dish radio telescope instrument and outputs pixel-level time-ordered-data. SEEK processes the time-ordered-data,…
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