May 15 – 17, 2026
College of Hakka Studies at NYCU, Zhubei, Hsinchu County 國立陽明交通大學客家學院(竹北六家校區)
Asia/Taipei timezone

Turbulence and star formation in M33

May 16, 2026, 11:00 AM
15m
HK106

HK106

Speaker

Raffaele Rani (NTHU)

Description

Understanding the turbulent structure of molecular clouds is essential for linking galactic environment to the regulation of star formation. While the turbulent properties of Galactic molecular clouds have been extensively investigated, direct observational constraints on turbulence modes in external galaxies remain limited.

In this work, we apply the statistical framework developed by Brunt and Federrath to quantify the relative fraction of solenoidal and compressive turbulent motions within a sample of 128 $^{13}$CO(2-1) molecular clouds in the nearby spiral galaxy M33. We measure the relative fraction of turbulent power contained in solenoidal modes (the solenoidal fraction, $R$) and investigate its variation with galactocentric distance, spiral structure, and tracers of recent star formation.

The solenoidal fraction spans $R \approx 0.05$-$0.8$, with mean and median values of $R \approx 0.29$ and $0.23$, respectively. The distribution is systematically shifted toward lower values compared to Galactic measurements obtained using the same methodology, indicating that compressive motions dominate the turbulent energy budget of M33 molecular clouds. The solenoidal fraction exhibits modest but systematic radial variations, with a minimum at $R_{\rm gal} \sim 2$-$4$~kpc, but shows no clear association with spiral arms or far-infrared tracers of recent star formation.

These results suggest that, while the balance between compressive and solenoidal modes varies weakly across the disk, the turbulent structure of molecular clouds is largely decoupled from large-scale galactic features and instead evolves primarily under local cloud-scale processes.

This work represents the first application of the Brunt \& Federrath statistical framework to molecular clouds in an external galaxy, demonstrating that turbulence mode analysis can now be extended beyond the Milky Way using spectroscopic data alone.

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