Discussing the distance bias in the estimation of Hi-GAL compact source physical properties – II. Evolutionary status and star formation rate

Abstract

The derivation of the evolutionary stage and rate of star formation of star-forming sites from Galactic single-dish far-infrared and submillimetre surveys suffers from the relatively limited spatial resolution that prevents access to 'core' scales (r ≤ 0.1 pc) for heliocentric distances d 1 kpc. In a previous article, we studied the implications of this 'distance bias' for the mass-radius relationship and its ability to diagnose potential sites for high-mass star formation, using a method that simulates the appearance at large distances of nearby and well-resolved star-forming regions mapped with Herschel. In the present article, we use the same method to quantify the bias introduced in the estimate of the evolutionary stage of dense 'clumps' (r ≥ 0.1 pc) revealed from the Herschel Hi-GAL survey, focusing in particular on the L bol /M env ratio, which is widely used as an evolutionary indicator. Furthermore, we discuss how the star formation rate (SFR) and efficiency (SFE) change with distance. The location of sources extracted from the virtual distance-displaced maps in the L bol versus M env diagram provides evolutionary indications that are consistent with those derived from the underlying population of cores and do not fluctuate substantially with distance. We also show that estimates of the SFR from integrated clump properties are consistent with estimates from the underlying resolved source population and show only minor variations with virtual distance. We conclude that methodologies commonly used to infer evolutionary indicators from clump-integrated quantities from large-scale single-dish Galactic far-infrared and submillimetre surveys are robust against distance and angular-resolution bias.

Radiation Transfer of Models of Massive Star Formation. IV. The Model Grid and Spectral Energy Distribution Fitting

“…This effect will tend to cause the observed slopes to be shallower, if more luminous, typically more distant, sources tend to have more contamination from surrounding clump material. However, Baldeschi et al (2017) found that increasing distance, although causing source positions to shift in the L − M diagram, does not change the slope, on average. In addition, the luminosity used in this diagram is the true total luminosity from the source, which may differ from the luminosity directly integrated from the SEDs by an order of magnitude or more depending on the viewing inclination, since more radiation is emitted in the polar direction due to low density outflow cavities (see §2.3.3).…”

Bipolar H II regions

“…We stress that the column density of a structure can depend upon its size. For example, if the size of a structure (a clump, a core, a filament) is smaller than 18 , then this structure is smoothed out in our maps and its peak column density is underestimated; this effect can be important for distant regions 1 (see also discussions in Baldeschi et al 2017).…”

The Star Formation Rate of the Milky Way as Seen by Herschel

“…In short, the contribution of each protostellar source to the total SFR is computed through theoretical evolutionary tracks reported in the bolometric luminosity versus mass diagram (Molinari et al 2008;Baldeschi et al 2017b;Elia et al 2021). At each time step, together with the clump mass-luminosity pair, the mass of the internal protostar being formed is also computed.…”

“…Baldeschi et al (2017a) proposed a method to evaluate this possible bias by simulating the appearance of nearby star-forming regions observed by the Herschel Gould Belt Survey (André et al 2010) if they were moved to larger distances (from 0.75 to 7 kpc), comparable to those typically found in the Hi-GAL survey. Subsequently, in Baldeschi et al (2017b) this approach was applied, in particular, to the estimation of the SFR. For three nearby regions they compared the SFR obtained from YSO counts (based on an updated version of Equation (1) of Lada et al 2010) to that estimated through the method of Veneziani et al (2017) from the clumps detected in the Herschel maps "displaced" at different virtual distances.…”