Astronomy and Astrophysics· 2026Q1
Complex Organic Molecules in Protostars with ALMA Spectral Surveys (COMPASS)
- 5citations
- Q1SCImago
- 2026year
Short summary
The COMPASS ALMA Large Program details its observational setup, data processing pipeline, and primary data products for studying complex organic molecules in 11 protostellar regions.
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Key points
- The COMPASS program surveyed 11 protostellar regions using ALMA to investigate chemical compositions.
- This paper details the observational setup, data processing pipeline (CASA, IMAGER), and post-processing techniques.
- Strategies for mitigating data challenges like data volume and continuum subtraction are discussed.
- The use of IMAGER proved computationally efficient and yielded scientifically comparable results to CASA.
- Key data products include image cubes, extracted spectra, and continuum images for each source.
AI-generated from the title and abstract; the full text is not read.
Abstract
Context . Studying the chemical composition of the warm gas surrounding embedded solar-type protostars is one of the areas for which the Atacama Large Millimeter/submillimeter Array (ALMA) is particularly well suited. Recently, the ALMA Large Program Complex Organic Molecules in Protostars with ALMA Spectral Surveys (COMPASS) carried out an observing campaign of a sample of 11 protostellar regions to investigate the chemical impact of their environments and evolutionary stages. Aims . The aim of this paper is to provide the observational and procedural information necessary for the community to understand the analysis presented in forthcoming scientific papers by the COMPASS collaboration, and to enable archival research using the data products provided by our team and the ALMA Science Archive. Methods . This paper describes the technical setup of the observations, and it outlines the data-processing pipeline and primary data products from this initiative. The Common Astronomy Software Applications (CASA) was used for initial calibration following the standard ALMA Pipeline, and then IMAGER was used for self-calibration and imaging. We describe post-processing done with Python to achieve favorable continuum subtraction, correct for the primary beam response, and extract spectra. Results . We discuss our strategy for mitigating data challenges, including those related to data volume and continuum subtraction for spectral line analysis. The incorporation of IMAGER in our workflow was advantageous in terms of the computing efficiency which allowed us to benchmark several imaging parameters and techniques; we also demonstrate that the imaging outcomes using IMAGER or CASA are scientifically comparable. Numerous data products are generated for the program, including image cubes for the 36 spectral windows targeting each source, extracted spectra, and continuum images.
The authors' abstract, as published at the source. Astronomy and Astrophysics, 2026 · DOI ↗
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Field: Astronomy and Astrophysics
Astronomy and AstrophysicsPhysics and Astronomy