Skip to main content

STARs that 'R' Young : When do stars form in clustered environments?

Periodic Reporting for period 2 - STARRY (STARs that 'R' Young : When do stars form in clustered environments?)

Reporting period: 2018-02-01 to 2020-01-31

"Among the main questions being posed throughout our existence are those that concern our origin and roots such as “where do we come from?” and “how did the Sun, stars and planets form?” Progress in answering them has been remarkable, but many important questions regarding star formation still exist.

More than 100 years ago, Sir James Jeans considered the formation of the Solar System and proposed that it began as a huge gaseous cloud containing only atoms and molecules. He showed that if such a cloud exceeded a certain mass, the mutual gravitational attraction between these particles would be sufficient to cause the cloud to shrink to ever smaller sizes and higher densities. As the contracting gas can heat up, the net result of this ""gravitational contraction"" is an enormously hot, dense, object where the conditions are extreme enough for nuclear fusion to begin. A star is born. Such clouds had in fact been discovered already back in the 18th century, when Sir William Herschel found well-defined dark patches on the sky. His first reaction was one of shock, ""My God, here truly is a hole in the sky!"", but we now know that in these places there are so many dust particles that they can block the light from the background stars just as fog blocks our view on a misty day. These dark clouds turn out to be massive enough to provide the material to build one or more stars. The cradles of stars were found.

An additional finding is that many stars are not alone, but are often clustered in groups of dozens to even hundreds of stars. The STARRY project focussed on the clustering properties of young stars and is based on research in the nineties which reported that young massive stars were mostly found in clusters, while lower mass young stars were not. We address this issue using the results of an on-going European Space Agency’s space telescope mission, Gaia.

STARRY consists of two related projects, that were each carried out by an Early Stage Researcher. The first project's objectives were studying the properties of the known young stars from a statistical point of view using the new information thanks to Gaia, and aimed at discovering more such stars in the huge dataset. Its results fed into the second project, whose objective it was to study clusters around these young massive stars.

The project was very timely, as it started when the results of the Gaia satellite were released. Gaia measured parallaxes for more than a billion stars, a 10,000 fold increase to what was available previously. These data allow the distances to objects and their properties such as mass and brightness to be determined."
First we presented an in-depth study of the currently known young stars, the so-called Herbig Ae/Be stars, named after the famous astronomer George Herbig who was the first to describe these objects. Our study was the first to be able to analyse the properties of all known Herbig Ae/Be stars as function of their mass and brightness. This allowed us us to demonstrate that there are different formation processes at work for the lower mass and higher mass objects respectively.

As the currently known such stars form a rather diverse set, the time was ripe to discover new such objects. The Gaia database with more than 1 billion objects constitutes the perfect starting point, and to cope with such an enormous dataset, it was decided to let the computers do the thinking, and artificial neural networks were set up to do so. The project discovered more than 2000 new Herbig Ae/Be stars, an order of magnitude improvement on that sample hitherto known. The selection was validated when follow-on spectroscopic observations using ground-based telescopes confirmed that the selected objects had spectral types as expected and also displayed emission lines that reveal the presence of ionised, accreting gas around the objects.

In parallel, the second project started off with the development of a code that is able to detect a cluster when only provided with only the astrometric information provided by Gaia: the location, parallax and the space motion of a star that would be associated with it. When applied to the Herbig Ae/Be stars, around 20% showed clear signs of being associated with a cluster. Given the observational constraints, it is not ruled out that most, if not all, Herbig stars are in clusters. An important new result is not only that the more massive Herbig Be stars are located in clusters, but that an equal number of the lower mass Herbig Ae stars are in clusters too. This was not reported earlier in the literature and was only possible due to the advancements possible with Gaia.

Further studies indicate that the Herbig Be stars are predominately located in the center of their respective clusters, while the Herbig Ae stars lie at the periphery of their cluster. This strongly suggests that there is a critical mass above which an object will be the most massive star in their cluster and below which it will be accompanied by more massive objects. This new insight will be crucial input for modern models of star and cluster formation.

Overall, the STARRY work was disseminated widely, having been published in 7 journal publications and presented at a large number of international conferences. The work has gained wide attention, with a larger than normal citation rate in the field while its associated press release was widely published.
The basis of the science projects in STARRY was the exploitation of the very recent data from the European Gaia satellite. Its major Data Release (DR2) was made available in April 2018. The project used its 2 years prior to this date preparing for this release. To this end, STARRY has produced software tools that have been applied to the study of young stars, but they also have wider application to other types of star and different science questions. The codes that resulted from this effort are twofold.

The first code concerns the development of an artificial network that was optimised to select for young objects in the Gaia database which was supplemented by a variety of other large databases to cover variability, infrared emission and hydrogen line emission. Based on a training set of known Herbig Ae/Be stars it identified a large number of objects with similar properties. The code is easily adaptable to other classes of object, as was already demonstrated in a successful application to find new “classical Be stars”, objects that have many, but not all, characteristics in common with Herbig Ae/Be stars.

Secondly, we developed tailor-made algorithms for the Gaia data to find clusters surrounding these young objects. The fact that this could be done in 5 dimensions; positions in two directions, proper motions in two directions and parallaxes, as opposed to earlier work that only used the 2-dimensional positions on the sky, gives an indication of the improvement in the field. Several dozens of clusters were detected around the Herbig Ae/Be stars. The cluster code is also easily adaptable to other types of object as it only requires the parameters of the central location of a putative cluster.

Both software tools YODA (Young Object Discoverer Algorithm) and CEREAL (ClustER detEction Algorithm) have been made available on the Github platform.