Recipient organisationCardiff UniversitySource-published name: Cardiff University
Funding£446K
PeriodJun 2025 — Jun 2028
In plain English
AI plain-English summary
Astronomers have just secured one of the largest observing programmes in ALMA’s history—700 hours of telescope time—to watch how star-forming clumps break free from their parent gas clouds and collapse into clusters of new stars. This matters because the physics that turns a diffuse interstellar cloud into a burning star remains surprisingly unsettled. For 50 years, theorists have disagreed about whether collapse begins at the scale of a small core (roughly 0.1 parsecs) or an entire molecular cloud (100 parsecs). The difference determines why the Milky Way forms stars so inefficiently—only a tiny fraction of its gas ever becomes stars. The team’s earlier work on a handful of infrared dark clouds suggested that collapse starts at the intermediate “clump” scale, where star clusters are born. This project tests that idea on 136 clumps, using automated line-fitting and 3D filament identification to measure how fast and how large the collapsing regions really are. This is fundamental science. There is no immediate practical application. But understanding why star formation is so inefficient shapes everything from galaxy evolution models to theories of planetary system formation. Past fundamental work on star formation physics has fed into models of interstellar chemistry, dust dynamics, and even the behaviour of turbulent flows used in industrial mixing processes. A clearer paradigm here could eventually inform how we model gas dynamics in other contexts—or simply settle a half-century-old argument about how the universe builds its stars.
View original technical description
Star formation is a central process to many areas of Astrophysics, from the evolution of galaxies to the formation of planetary systems. But despite its importance, the physics that leads to the gradual concentration of diffuse interstellar clouds into nuclear-burning spheres of gas is still very much debated. One key element of this star formation process is the size (and mass) of the region, within a given molecular cloud, that become gravitationally unstable and collapse uninterruptedly. Theoretical and numerical predictions in that regard vary widely, from core size regions (i.e. ~0.1pc) up to entire molecular clouds (i.e. ~100pc), feeding a 50-year-old debate on the origin of the Milky Way’s low star formation efficiency. In this context, we have recently made a decisive step towards solving this puzzle. Via a multi-scale and multi-tracer analysis, we showed that clumps, i.e. the parsec-size molecular cloud over-densities that will typically host the formation of a star cluster, are dynamically decoupled from their parent molecular clouds. We thus proposed that, at least for the few infrared dark clouds that have been investigated so far, collapse is initiated at clump scale. This project aims at consolidating this result by extending the study to a much larger and unbiased sample of clumps with the goal of constraining the physics behind the dynamical decoupling of star cluster progenitors. The data at the centre of this project is a unique set of ALMA cycle 9 and 10 observations that mosaiced 136 clumps in N2H+(1-0), for a total of 7m/12m/TP time of ~700h, one of the largest ALMA programmes ever observed. Combined with Cardiff-made NEATH synthetic observations of cloud/clump formation and evolution, our automated line-fitting tool mwydyn, and a new 3D filament identification code, we will be able to measure how the size and mass of the decoupled regions evolve in time, and determine how rapid clump collapse really is. This project relies on data that have just been secured and on a methodology that has been already tested for most parts, which highlights its feasibility. Finally, while the outcome of the project will pave the way for a new star cluster formation paradigm, it will also provide along the way some of the strongest constraints there are on the origin of Milky Way’s low star formation efficiency.
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