ALMACAL XII. Data characterisation and products
Victoria Bollo, Martin Zwaan, Celine Peroux, Aleksandra Hamanowicz,, Jianhang Chen, Simon Weng, Rob J. Ivison, Andrew Biggs

TL;DR
The ALMACAL survey compiles and characterizes a comprehensive dataset of ALMA calibration scans, enabling large-scale, high-sensitivity sub-millimetre observations for diverse astrophysical research.
Contribution
This paper presents the first extensive data characterization and product generation from the ALMACAL survey, covering over 1000 square arcmin and 2000 hours of observations across multiple ALMA bands.
Findings
ALMACAL is one of the largest ALMA surveys to date.
It overcomes previous limitations in sky coverage and cosmic variance.
The dataset enhances studies of dusty galaxies, absorption lines, and galaxy evolution.
Abstract
The ALMACAL survey is based on a database of reprocessed ALMA calibration scans suitable for scientific analysis, observed as part of regular PI observations. We present all the data accumulated from the start of ALMA operations until May 2022 for 1047 calibrator fields across the southern sky spanning ALMA Bands 3 to 10 (~ 84 - 950 GHz), so-called ALMACAL-22. Encompassing over 1000 square arcmin and accumulating over 2000 hours of integration time, ALMACAL is not only one of the largest ALMA surveys to date, but it continues to grow with each new scientific observation. We outline the methods for processing and imaging a subset of the highest-quality data ('pruned sample'). Using deconvolution techniques within the visibility data (uv plane), we created data cubes as the final product for further scientific analysis. We describe the properties and shortcomings of ALMACAL and compare…
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