Authors: A. Bayo, D. Barrado, N. Huélamo, M. Morales-Calderón, C. Melo, J. Stauffer, B. Stelzer
First Author’s Institution: European Southern Observatory, Chile
Introduction You can think of a star-forming region as a family. If you look at the kids and the parents in a family, you might be able to tell some characteristics in common, but you might not immediately see how the kids will grow up to be more like the parents, or you might not be able to tell what the parents were like as kids. Even among the kids, you will find some differences. Now imagine you want to tell a story about the family’s past and future, based only on some subset of the information about the family, such as hair color, height or favorite food. How would the story differ if it were based on DNA samples? The different types of information will lead you to tell very different stories, with the most thorough story combining as much data as possible.
Just like a family, a star-forming region can be very diverse, with objects at different stages of their evolution, and young objects evolving in different ways towards different ends. Since stars are a basic component of our universe, many astronomers are interested in understanding how and where stars form and evolve. The authors of today’s paper have embarked on a thorough observing campaign of the Lambda Orionis Star Forming Region (LOSFR), at the head of the Orion constellation. They have observed with a variety of telescopes, including at Mauna Kea (Hawaii), Las Campanas (Chile), Calar Alto (Spain) and the Very Large Telescope at Cerro Paranal (Chile), over seven years with the goal of studying sources in star-forming regions over a range of ages, masses and other characteristics.
Most generally, objects within a star-forming region can be classified according to whether or not they have a disk (see this post about the role of a disk in the star forming process), and whether or not they have reached the minimum mass of about 0.1 solar masses required to burn hydrogen. Throughout the paper, and this post, most trends are divided among disk- and diskless-objects, and stellar- and substellar-objects.
Results To better understand the region, the authors study its ~100 constituent members. In summary, they show that more than half of substellar objects have disks, while less than half of stellar objects have disks, with most objects losing their disks before reaching 0.6 solar masses. Of the objects with disks, many are accreting material, but not all, which challenges the commonly accepted picture of disk accretion that is important for star formation. These discoveries, and more which I highlight below, are presented in the paper in a logical and straightforward way using many plots to show the impressive amount of data the group have gathered. The paper demonstrates how a single cluster can be a great way to understand many important components of the star formation process.
Velocity: The authors measure the rotational velocity of sources, and find that generally the younger objects are rotating faster.
Disks: Which sources have disks? This is determined based on whether the object emits stronger at longer infrared wavelengths (called an IR excess, which Nick explains well in his astrobite). This IR excess can be explained because disks are composed of dust, and the dust absorbs optical light emitted from the central source and re-emits infrared radiation. In this region, 26% of stellar objects have disks, while 58% of substellar objects have disks. As a function of mass, this is shown in the figure below (left panel).
Mass: Next the authors determine the mass function of sources, which I show and explain in the figure below. Moreover, they show that there is a difference between the mass function for sources with and without disks. Below 0.6 solar masses, most sources have disks, but sources more massive than 0.6 solar masses have lost their disks, which can be seen by the flattening of the mass function beyond 0.6 solar masses in the figure below (right). The authors make the conclusion that disk lifetime depends on the mass of the object.
Accretion: They use spectra of hydrogen Hα emission to determine (a) whether a source is accreting, and (b) if so, what is the accretion rate of mass onto the source. The accretion rate can be determined by measuring the width of the Hα emission line. For more information about hydrogen and other spectral features, check out this glossary. Of all the sources (156), 9% are found to be accreting. When considering only objects with masses less than 0.1 solar masses and with disks, 38% are accreting.
With such a broad collection of data, the authors are able to compare spectra for certain sources over several years, and they find a few cases of spectral lines which vary in shape among the different observations. They discuss these objects in more detail, but a couple of explanations are “flares” or multiple systems.
Accretion vs. Mass: The authors make a plot of mass accretion rate versus mass of the central object for all of the objects that are accreting. Overall, more massive sources are accreting at a higher rate than less massive sources. Or, looking at it the other way, higher accretion rates are building up more massive sources, while lower accretion rates are building less massive sources.
Relating accretion and disks: In theory, since accretion and disks are both considered vital elements to the star forming process, then sources with disks should also be simultaneously accreting. But, in some cases disks are found around sources that aren’t accreting, called “quiet” disks. This might imply that a planet is dissipating the inner disk of a particular source. However, the exact mechanism is unknown, and the main point is that just by looking at a disk, there seems to be no obvious way to tell whether the source is actively accreting or not.
X-ray identification: The authors have done a thorough job of observing objects in this region, mostly with optical and infrared wavelengths. They also utilize X-ray data, obtained with XMM-Newton (see papers by Barrado et al 2011, Franciosini & Sacco 2011), and they show that the X-ray data were able to identify most of the objects identified in this work using spectroscopy, but that generally the X-ray observations are not able to detect objects with disks.
Spatial Distribution: Finally, the authors study how the objects are distributed spatially throughout the region, and find that disk-sources are found more densely packed towards the center of the cluster than the diskless-sources. This is inconsistent with the scenario in which a supernova triggered star formation in the region, because in that case star-formation is first triggered at the center and then triggered towards the outer regions, resulting in older (disk-less) sources more concentrated at the center and younger (disk) sources more dispersed throughout the region. Further studies are needed to test the different triggering scenarios in star-forming regions.