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Astrochemical Study of Early Embedded Disks (iSEEDs) aims to infer the physical and chemical structure of young embedded disks to address the following open questions:
1. How much mass is available in the disk for planet formation?
2. What is the chemical composition of disks, inherited by forming planets?
3. When and how do dust grains grow in the disk midplane to form planetesimals?
Astrochemistry is currently in a golden age marked by significant advancements in our understanding of the processes responsible for molecules formation, leading ultimately to the emergency of Life.
Large surveys performed with powerful instruments, such as the ALMA, NOEMA and VLA telescopes, have generated extensive public data archives still to be fully exploited. Although individual proposals target specific scientific goals, the resulting data often hold valuable unexplored information, especially in the case of molecular lines from complex molecules, where specialised expertise is necessary for analysis.
iSEEDs employs data mining and machine learning techniques to enhance data utilisation and achieve a systematic characterisation of planet-forming systems.
iSEEDs proposes an innovative interdisciplinary approach, combining astrochemistry, data mining and machine learning, to unveil the physical and chemical structure of a large number of young embedded disks, the birthplaces of planets. This has significant implications for star and planet formation, astrochemistry, exoplanets, and extragalactic star formation.
THE FORMATION OF A PLANETARY SYSTEM
THE FORMATION OF A PLANETARY SYSTEM
The picture shows the different components of the protostellar system, including outer and inner protostellar envelope, the large-scale outflow and the keplerian disk. On the right there are dust and gas observations of protostellar disks at different evolutionary stages. Protoplanets start to form in young embedded disks, cave gaps and cavities until the final planetary system forms after ~ few Myr.
iSEEDs ORGANISATION
iSEEDs ORGANISATION
iSEEDs is organised in three main research lines: MASS, CHEM and DUST, supported by three dedicated, fully transversal infrastructures: DATA, ABUNDANCES and MODELLING.
The high spectral line density in a young embedded disk requires specialised expertise to enable automatic and precise line identification.
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