ASAI observations

IRAM-30m Large Program "Astrochemical Surveys At IRAM" (ASAI)

(PI: Bertrand Lefloch & Rafael Bachiller, 400 hours allocated)


The ASAI project addresses the question of our “chemical origins”, namely the chemical evolution of the matter during the long process that brought it from prestellar core to protostars and their associated outflows, protoplanetary disks, and ultimately to the bodies of the Solar System. This project is led by B. Lefloch (IPAG, France) and R. Bachiller (OAN, Spain) and joins the efforts of nearly all specialists in Astrochemistry in Spain and France.

Systematic spectral line surveys constitute the most powerful diagnostic tool to carry out a comprehensive study of the chemical evolution of star-forming regions. ASAI makes full use of the EMIR receivers at the IRAM 30-meter telescope to carry out an unbiased spectral exploration of a carefully selected sample of 10 template sources, covering the full formation process of solar-type stars, from prestellar cores to solar-type protostars (including jets and outflows) to protoplanetary disks. The main goal is to obtain a complete, high-sensitivity census of the gas chemical composition, including pre-biotic molecules, and its evolution along the main stages of the star formation process, from prestellar cores and protostars to protoplanetary disks. The resulting data set will remain as a reference database for astrochemists (astronomers, chemists, and theoreticians), while triggering many follow-up studies. It constitutes a big step forward in the understanding of molecular complexity of the infancy of our own solar system. Our goal is to determine the chemical composition in all the ASAI source sample and compare with chemical models in order to understand how the molecular complexity builds up and what it depends on. The measured abundances will then be compared to state of the art astrochemical models, providing a laboratory where the various parameters which any model depends on, are covered by the selected sources. Source inter-comparison will permit to better constrain the parameter space, in particular assess the importance of age and/or the physical conditions.

DOI linked publication: 10.1093/mnras/sty937

IRAM 30-m ASAI Data here