How efficently do stars form?
Stars form from giant clouds of molecular gas and dust over millions of years, but how much of the initial material in a cloud actually ends up in a star? In the above figure, we see that stars undergo many different observational stages before they begin hydrogen fusion and start their journey on the main sequence. There are many places along this journey where the number of stars made from this gas can be changed.
At the core stage (going from the upper left panel to the upper middle), cores can be formed and ripped apart by turbulent motions within the gas, before they can go from starless to pre-stellar.
In the protostar stage (upper right to lower left) the accretion onto the central source can cause fragmentation into multiple star systems, and the strong outflows can increase turblence in the area making it more difficult to form stars, and blow away material that was being accreted onto the central star. Indeed, many processes can impact the shift seen from the core mass function to the initial mass function.
My work focuses on connecting the amount of gas within a given region to the number of protostars within that region. Understanding the number of stars we can finally expect from a given cloud, and how that might vary with environment, can help us to understand the relative impact of different feedback effects on the star formation rate.
The efficiency issue
In a previous work by Pokhrel et al. (2021), it was found that the star formation efficiency (how many stars are made from the available gas) is fairly steady at about 2.6%, up to a gas column density of about 1×1022 particles cm-2. After this density, the number of protostars within the gas surface density contours drops off precipitously, causing a similar drop in star forming efficiency. The cause? A couple possibilities:
- Observational Bias
- Feedback Effects
On the other hand, feedback, as noted before, is capable of disrupting core formation and can blow out material from accreting onto protostars. To differentiate between these effects, we require a telescope which is unhindered by observational biases: cue the James Webb Space Telescope (JWST). JWST has a resolution 10x that of Spitzer (the previous infra-red space telescope), and can detect objects that are 60x dimmer (based on their mirror sizes alone). The picture to the right shows the JWST field of Serpens Main, with density contours increasing from 10 magnitudes of visual extinction, all the way to 100. The YSOs identifiable from Spitzer are indicated by gold stars, while even this short exposure from JWST shows many more objects embedded in the densest regions of Serpens Main. Furthermore, JWST has filters specifically tuned to signatures arising from outflows, thus allowing for the accurate determination of feedback effects. With the data from this telescope, we will be able to determine what the true star formation efficiency is in dense environments, and how it might change with environment.
Star formation efficiency in the Cosmic Cliffs
We analyzed the JWST Early Release Observations of the Cosmic Cliffs NIRCam data to determine the star formation efficiency in the region. The main results of this work were:
- We found 450 candidate YSOs in the region, whose surface density was largely coincident with the gas surface density from Herschel observations.
- We found a significant fraction of young sub-stellar objects in the region.
- The size of this sub-stellar population is large enough to imply the star formation efficiency in the region has been previously underestimated.
A tool for finding Young Stellar Objects
I created the Stellar Evolutionary Stage Heuristic Assessment Tool (SESHAT) for identifying YSOs, galaxies, brown dwarfs, white dwarfs, and other field stars in JWST data. The key uses of this tool include classifying catalogs and testing JWST filter selections for proposals.