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Register a new userOn the Indeterministic Nature of Star Formation on the Cloud Scale
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Molecular clouds are turbulent structures whose star formation efficiency (SFE) is strongly affected by internal stellar feedback processes. In this paper we determine how sensitive the SFE of molecular clouds is to randomised inputs in the star formation feedback loop, and to what extent relationships between emergent cloud properties and the SFE can be recovered. We introduce the yule suite of 26 radiative magnetohydrodynamic (RMHD) simulations of a 10,000 solar mass cloud similar to those in the solar neighbourhood. We use the same initial global properties in every simulation but vary the initial mass function (IMF) sampling and initial cloud velocity structure. The final SFE lies between 6 and 23 percent when either of these parameters are changed. We use Bayesian mixed-effects models to uncover trends in the SFE. The number of photons emitted early in the clusters life and the length of the cloud provide are the strongest predictors of the SFE. The HII regions evolve following an analytic model of expansion into a roughly isothermal density field. The more efficient feedback is at evaporating the cloud, the less the star cluster is dispersed. We argue that this is because if the gas is evaporated slowly, the stars are dragged outwards towards surviving gas clumps due to the gravitational attraction between the stars and gas. While star formation and feedback efficiencies are dependent on nonlinear processes, statistical models describing cloud-scale processes can be constructed.
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How do stars manage to form within low-density, HI-dominated gas? Such environments provide a laboratory for studying star formation with physical conditions distinct from starbursts and the metal-rich disks of spiral galaxies where most effort has been invested. Here we outline fundamental open questions about the nature of star formation at low-density. We describe the wide-field, high-resolution UV-optical-IR-radio observations of stars, star clusters and gas clouds in nearby galaxies needed in the 2020s to provide definitive answers, essential for development of a complete theory of star formation.
We compare the structure of molecular gas at $40$ pc resolution to the ability of gas to form stars across the disk of the spiral galaxy M51. We break the PAWS survey into $370$ pc and $1.1$ kpc resolution elements, and within each we estimate the molecular gas depletion time ($tau_{rm Dep}^{rm mol}$), the star formation efficiency per free fall time ($epsilon_{rm ff}$), and the mass-weighted cloud-scale (40 pc) properties of the molecular gas: surface density, $Sigma$, line width, $sigma$, and $bequivSigma/sigma^2proptoalpha_{rm vir}^{-1}$, a parameter that traces the boundedness of the gas. We show that the cloud-scale surface density appears to be a reasonable proxy for mean volume density. Applying this, we find a typical star formation efficiency per free-fall time, $epsilon_{ff} left( left< Sigma_{40pc} right> right) sim 0.3{-}0.36%$, lower than adopted in many models and found for local clouds. More, the efficiency per free fall time anti-correlates with both $Sigma$ and $sigma$, in some tension with turbulent star formation models. The best predictor of the rate of star formation per unit gas mass in our analysis is $b equiv Sigma / sigma^2$, tracing the strength of self gravity, with $tau_{rm Dep}^{rm mol} propto b^{-0.9}$. The sense of the correlation is that gas with stronger self-gravity (higher $b$) forms stars at a higher rate (low $tau_{rm Dep}^{rm mol}$). The different regions of the galaxy mostly overlap in $tau_{rm Dep}^{rm mol}$ as a function of $b$, so that low $b$ explains the surprisingly high $tau_{rm Dep}^{rm mol}$ found towards the inner spiral arms found by by Meidt et al. (2013).
One of the most important and well-established empirical results in astronomy is the Kennicutt-Schmidt (KS) relation between the density of interstellar gas and the rate at which that gas forms stars. A tight correlation between these quantities has long been measured at galactic scales. More recently, using surveys of YSOs, a KS relationship has been found within molecular clouds relating the surface density of star formation to the surface density of gas; however, the scaling of these laws varies significantly from cloud to cloud. In this Letter, we use a recently developed, high-accuracy catalog of young stellar objects from $textit{Spitzer}$ combined with high-dynamic-range gas column density maps of twelve nearby ($<$1.5 kpc) molecular clouds from $textit{Herschel}$ to re-examine the KS relation within individual molecular clouds. We find a tight, linear correlation between clouds star formation rate per unit area and their gas surface density normalized by the gas free-fall time. The measured intracloud KS relation, which relates star formation rate to the volume density, extends over more than two orders of magnitude within each cloud and is nearly identical in each of the twelve clouds, implying a constant star formation efficiency per free-fall time $epsilon_{rm ff}approx 0.026$. The finding of a universal correlation within individual molecular clouds, including clouds that contain no massive stars or massive stellar feedback, favors models in which star formation is regulated by local processes such as turbulence or stellar feedback such as protostellar outflows, and disfavors models in which star formation is regulated only by galaxy properties or supernova feedback on galactic scales.
We have used the ratio of column densities (CDR) derived independently from the 850-$mu$m continuum JCMT Plane Survey (JPS) and the $^{13}$CO/C$^{18}$O $(J=3-2)$ Heterodyne Inner Milky Way Plane Survey (CHIMPS) to produce maps of the dense-gas mass fraction (DGMF) in two slices of the Galactic Plane centred at $ell$=30$^{circ}$ and $ell$=40$^{circ}$. The observed DGMF is a metric for the instantaneous clump-formation efficiency (CFE) in the molecular gas. We split the two fields into velocity components corresponding to the spiral arms that cross them, and a two-dimensional power-spectrum analysis of the spiral arm DGMF maps reveals a break in slope at the approximate size scale of molecular clouds. We interpret this as the characteristic scale of the amplitude of variations in the CFE and a constraint on the dominant mechanism regulating the CFE and, hence, the star-formation efficiency in CO-traced clouds.
Diffuse emission is observed in galaxies in many tracers across the electromagnetic spectrum, including tracers of star formation, such as H$alpha$ and ultraviolet (UV), and tracers of gas mass, such as carbon monoxide (CO) transition lines and the 21-cm line of atomic hydrogen (HI). Its treatment is key to extracting meaningful information from observations such as cloud-scale star formation rates. Finally, studying diffuse emission can reveal information about the physical processes taking place in the ISM, such as chemical transitions and the nature of stellar feedback (through the photon escape fraction). We present a physically-motivated method for decomposing astronomical images containing both diffuse emission and compact regions of interest, such as HII regions or molecular clouds, into diffuse and compact component images through filtering in Fourier space. We have previously presented a statistical method for constraining the evolutionary timeline of star formation and mean separation length between compact star forming regions with galaxy-scale observations. We demonstrate how these measurements are biased by the presence of diffuse emission in tracer maps and that by using the mean separation length as a critical length scale to separate diffuse emission from compact emission, we are able to filter out this diffuse emission, thus removing its biasing effect. Furthermore, this method provides, without the need for interferometry or ancillary spectral data, a measurement of the diffuse emission fraction in input tracer maps and decomposed diffuse and compact emission maps for further analysis.
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