Hidden views of vast stellar nurseries

Using ESO's Visible and Infrared Survey Telescope for Astronomy (VISTA), astronomers have created a vast infrared atlas of five nearby stellar nurseries by piecing together more than one million images. These large mosaics reveal young stars in the making, embedded in thick clouds of dust. Thanks to these observations, astronomers have a unique tool with which to decipher the complex puzzle of stellar birth.

"In these images we can detect even the faintest sources of light, like stars far less massive than the Sun, revealing objects that no one has ever seen before," says Stefan Meingast, an astronomer at the University of Vienna in Austria and lead author of the new study published today in Astronomy & Astrophysics. "This will allow us to understand the processes that transform gas and dust into stars."

Stars form when clouds of gas and dust collapse under their own gravity, but the details of how this happens are not fully understood. How many stars are born out of a cloud? How massive are they? How many stars will also have planets?

To answer these questions, Meingast's team surveyed five nearby star-forming regions with the VISTA telescope at ESO's Paranal Observatory in Chile. Using VISTA's infrared camera VIRCAM, the team captured light coming from deep inside the clouds of dust. "The dust obscures these young stars from our view, making them virtually invisible to our eyes. Only at infrared wavelengths can we look deep into these clouds, studying the stars in the making," explains Alena Rottensteiner, a PhD student also at the University of Vienna and co-author of the study.

The survey, called VISIONS, observed star-forming regions in the constellations of Orion, Ophiuchus, Chamaeleon, Corona Australis and Lupus. These regions are less than 1500 light-years away and so large that they span a huge area in the sky. The diameter of VIRCAM's field of view is as wide as three full Moons, which makes it uniquely suited to map these immensely big regions.

The team obtained more than one million images over a period of five years. The individual images were then pieced together into the large mosaics released here, revealing vast cosmic landscapes. These detailed panoramas feature dark patches of dust, glowing clouds, newly-born stars and the distant background stars of the Milky Way.

Since the same areas were observed repeatedly, the VISIONS data will also allow astronomers to study how young stars move. "With VISIONS we monitor these baby stars over several years, allowing us to measure their motion and learn how they leave their parent clouds," explains João Alves, an astronomer at the University of Vienna and Principal Investigator of VISIONS. This is not an easy feat, as the apparent shift of these stars as seen from Earth is as small as the width of a human hair seen from 10 kilometres away. These measurements of stellar motions complement those obtained by the European Space Agency's Gaia mission at visible wavelengths, where young stars are hidden by thick veils of dust.

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Supermassive black holes put a brake on stellar births

Black holes with masses equivalent to millions of suns do put a brake on the birth of new stars, say astronomers. Using machine learning and three state of the art simulations to back up results from a large sky survey, the researchers resolve a 20-year long debate on the formation of stars. Joanna Piotrowska, a PhD student at the University of Cambridge, will present the new work today (Tuesday 20 July) at the virtual National Astronomy Meeting (NAM 2021).

Star formation in galaxies has long been a focal point of astronomy research. Decades of successful observations and theoretical modelling resulted in our good understanding of how gas collapses to form new stars both in and beyond our own Milky Way. However, thanks to all-sky observing programmes like the Sloan Digital Sky Survey (SDSS), astronomers realised that not all galaxies in the local Universe are actively star-forming -- there exists an abundant population of "quiescent" objects which form stars at significantly lower rates.

The question of what stops star formation in galaxies remains the biggest unknown in our understanding of galaxy evolution, debated over the past 20 years. Piotrowska and her team set up an experiment to find out what might be responsible.

Using three state-of-the-art cosmological simulations -- EAGLE, Illustris and IllustrisTNG -- the astronomers investigated what we would expect to see in the real Universe as observed by the SDSS, when different physical processes were halting star formation in massive galaxies.

The astronomers applied a machine learning algorithm to classify galaxies into star-forming and quiescent, asking which of three parameters: the mass of the supermassive black holes found at the centre of galaxies (these monster objects have typically millions or even billions of times the mass of our Sun), the total mass of stars in the galaxy, or the mass of the dark matter halo around galaxies, best predicts how galaxies turn out.

These parameters then enabled the team to work out which physical process: energy injection by supermassive black holes, supernova explosions or shock heating of gas in massive halos is responsible for forcing galaxies into semi-retirement.

The new simulations predict the supermassive black hole mass as the most important factor in putting the brakes on star formation. Crucially, the simulation results match observations of the local Universe, adding weight to the researchers' findings.

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