The Varying Mass Distribution of Molecular Clouds Across M83


The work of Adamo et al. (2015) identified characteristic mass scales in the mass distributions of young massive clusters in the nearby galaxy M83. Here, here we present a cloud-based analysis of ALMA CO(\(1\to 0\)) data to search for such characteristic mass scales in the molecular cloud population. We identify a population of molecular clouds in M83 that is largely similar to those found in the Milky Way and Local Group galaxies, however clouds in the center of the galaxy show high surface densities and enhanced turbulence, as is common for clouds in high density nuclear environments. Like the work on young massive clusters, we find a characteristic mass scale for the populations that decreases radially in the galaxy. We find the most massive young massive cluster tracks the most massive molecular cloud radially with the cluster mass being \(\sim 0.01\) that of the most massive molecular cloud. The maximum mass of the molecular cloud distribution also corresponds well to the value expected from shear instabilities, particularly in regions outside the nuclear and bar regions, where our simple shear model is inappropriate. Outside the nuclear region of M83 (\(R_{\mathrm{gal}}>0.5\)), there is no evidence for changing internal conditions in the population of molecular clouds, with the average internal pressures, densities, and free-fall times remaining constant for the cloud population over the galaxy. Thus, the observed variation in the fraction of star formation that results in bound clusters must result from the changing fragmentation process of the molecular gas.


Molecular gas is the host of all known star formation in the local and distant Universe. The average properties of the star formation process point to roughly constant star formation rate per unit free fall time (e.g., Krumholz et al., 2007). However, there is emerging evidence, particularly in dense gas environments, of variations in the molecular gas depletion timescale (\(\tau_{\mathrm{dep}} \equiv \Sigma_{\mathrm{H2}}/\dot{\Sigma}_{\star}\), where \(\Sigma_{\mathrm{H2}}\) is the molecular gas surface density and \(\dot{\Sigma}_{\star}\) is the star formation rate surface density). Recent work in the local (Usero et al., 2015; Bigiel et al., 2015; Pereira-Santaella et al., 2016; Bigiel et al., 2016) and high-redshift (Genzel et al., 2015; Aravena et al., 2016; Scoville et al., 2016) Universe point to significant variation in depletion times, converging to the sense that higher density environments have shorter depeletion times. Whether the changes in depletion time reflect a different mode of star formation or a variation along a continuum (e.g., Krumholz et al., 2011) remains unsettled.

Star formation is often parameterized as uniform mass rate of star production, but the organization of the resulting stellar structures also shows significant evolution with star formation rate, and by correlation, with the molecular gas (surface) density. In particular, the fraction of stars formed in bound clusters (\(\Gamma\)) is seen to correlate with star formation rate (Larsen, 2002; Bastian, 2008). The origin of this correlation has been attributed to the evolution of the underlying properties of the molecular (star forming) interstellar medium (ISM) (Kruijssen, 2014). This assumes that there is a correlation between the structure of the star forming ISM and the resulting clusters that evolve. In particular, the upper end of the cluster mass function appears to be truncated at a characteristic mass scale (Larsen, 2009; Bastian et al., 2011; Konstantopoulos et al., 2013) and that mass scale evolves with galactic environment (Adamo et al., 2015).

When the molecular ISM is partitioned into molecular clouds, the mass distribution of the population also shows a characteristic truncation mass (Williams et al., 1997; Rosolowsky, 2005) and the characteristic mass also evolves with the changing properties of the galactic environment (Rosolowsky 2007, Colombo 2014, Hughes 2015). While assumed that these two characteristic masses are linked, this correlation has yet to be demonstrated. Furthermore, the characteristic masses of the molecular clouds and clusters have not been well linked back to the cloud formation process, though models of cloud formation should predict the resulting characteristic mass (e.g., Duarte-Cabral et al., 2016; Pan et al., 2016). Several different cloud formation scenarios have been proposed (Dobbs 2014) and the evolving characteristic mass provides a clear observational handle for evaluating those formation mechanisms.

The nearby galaxy M83 provides an excellent opportunity to evaluate the evolving mass distribution of molecular clouds in conjunction with the changing cluster properties. As the nearest (\(D=4.5\) Mpc)(Thim et al., 2003), face-on, massive spiral galaxy, M83 is an obvious target for exploring molecular cloud properties. Archival Hubble Space Telescope data have already been analyzed, showing a significant change in both the fraction of star formation that results in bound clusters (Silva-Villa et al., 2013) and the changing characteristic masses of young massive cluster populations (Adamo et al., 2015). This latter work found that the cluster mass distribution followed a Schechter function, i.e. a power-law mass distribution with an index of -2 and an exponential truncation at a characteristic mass. We therefore investigate whether the molecular cloud population, which must serve as the progenitors of these clouds a similar mass distribution with truncation. To explore this question, we utilize archival data from the Atacama Millimeter/Submillimeter Array (ALMA), which can providing exceptional imaging data of this nearby galaxy. In particular, we use the high-quality \(^{12}\)CO(\(1\to0\)) data set observed as part of ALMA project 2012.1.00762.S (PI: A. Hirota).

In this paper, we present a cloud-based analysis of the molecular emission in M83, searching for environmental variation in the cloud populations. In Section \ref{sec:data}, we present the ALMA data and report on the relevant limitations that affect our analysis. In Section \ref{sec:cprops}, we use the cprops algorithm (Rosolowsky et al., 2006) to decompose the molecular emission into the population of molecular clouds. We compare the properties of these clouds to the populations seen in the Milky Way and nearby galaxies. For comparison to the studies of clusters, we also analyze the mass distributions of the clouds. In Section \ref{sec:discussion}, we interpret the results of the analysis