TESTING 24 μm AND INFRARED LUMINOSITY AS STAR FORMATION TRACERS FOR GALACTIC STAR-FORMING REGIONS

Vutisalchavakul, Nalin; Evans, Neal J.

doi:10.1088/0004-637x/765/2/129

Cited by 23 publications

(45 citation statements)

References 67 publications

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“…The slope is nearly identical to that found by analysis of a more limited sample, while the coefficient is a bit less, but within the uncertainties: (a = 0.53 ± 0.17 and b = 0.83 ± 0.08) (Vutisalchavakul & Evans 2013); that fit is shown as a red line in Figure 1. The slightly sub-linear fits and the larger discrepancies at low SFR can result from the fact that the radio emission is more sensitive to the upper end of the IMF (as is also true for Hα or any diagnostic requiring ionized gas), as can be seen from Table 1 of Kennicutt & Evans (2012).…”

Section: Comparing Sfr From Radio Continuum and Mirsupporting

confidence: 76%

“…For this reason, we use SFR(MIR) in further analysis. This tracer also begins to underestimate the SFR for SFRs less than about 5 M ⊙ Myr −1 , corresponding to a total far-infrared luminosity of 10 4.5 L ⊙ (Vutisalchavakul & Evans 2013;Wu et al 2005). Consequently, we limit further investigation to those sources with SFR above this value, leaving 51 sources.…”

Section: Comparing Sfr From Radio Continuum and Mirmentioning

confidence: 99%

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Star Formation Relations in the Milky Way

Vutisalchavakul¹,

Evans²

2016

ApJ

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111

141

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The relations between star formation and properties of molecular clouds are studied based on a sample of star forming regions in the Galactic Plane. Sources were selected by having radio recombination lines to provide identification of associated molecular clouds and dense clumps. Radio continuum and mid-infrared emission were used to determine star formation rates, while 13 CO and submillimeter dust continuum emission were used to obtain masses of molecular and dense gas, respectively. We test whether total molecular gas or dense gas provides the best predictor of star formation rate. We also test two specific theoretical models, one relying on the molecular mass divided by the free-fall time, the other using the free-fall time divided by the crossing time. Neither is supported by the data. The data are also compared to those from nearby star forming regions and extragalactic data. The star formation "efficiency," defined as star formation rate divided by mass, spreads over a large range when the mass refers to molecular gas; the standard deviation of the log of the efficiency decreases by a factor of three when the mass of relatively dense molecular gas is used rather than the mass of all the molecular gas.

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Section: Comparing Sfr From Radio Continuum and Mirsupporting

confidence: 76%

Section: Comparing Sfr From Radio Continuum and Mirmentioning

confidence: 99%

Star Formation Relations in the Milky Way

Vutisalchavakul¹,

Evans²

2016

ApJ

Self Cite

111

141

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“…The origin of the weak dust emission in NGC 346 is not the same as the weak emission in the Gould-belt star-formation regions reported by Vutisalchavakul & Evans (2013). These authors have compared the SFR one would derive from Spitzer/MIPS 24 µm measurements or TIR with SFR derived from counting YSOs.…”

Section: Star Formation Rate Surface Densitiesmentioning

confidence: 89%

Star formation rates from young-star counts and the structure of the ISM across the NGC 346/N66 complex in the SMC★

Hony¹,

Gouliermis²,

Galliano³

et al. 2015

Monthly Notices of the Royal Astronomical Society

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The rate at which interstellar gas is converted into stars, and its dependence on environment, is one of the pillars on which our understanding of the visible Universe is build. We present a comparison of the surface density of young stars (Σ ) and dust surface density (Σ dust ) across NGC 346 (N66) in 115 independent pixels of 6×6 pc 2 . We find a correlation between Σ and Σ dust with a considerable scatter. A power law fit to the data yields a steep relation with an exponent of 2.6±0.2. We convert Σ dust to gas surface density (Σ gas ) and Σ to star formation rate (SFR) surface densities (Σ SFR ), using simple assumptions for the gas-to-dust mass ratio and the duration of star formation. The derived total SFR (4±1·10 −3 M yr −1 ) is consistent with SFR estimated from the H α emission integrated over the H α nebula. On small scales the Σ SFR derived using H α systematically underestimates the count-based Σ SFR , by up to a factor of 10. This is due to ionizing photons escaping the area, where the stars are counted. We find that individual 36 pc 2 pixels fall systematically above integrated disc-galaxies in the Schmidt-Kennicutt diagram by on average a factor of ∼7. The NGC 346 average SFR over a larger area (90 pc radius) lies closer to the relation but remains high by a factor of ∼3. The fraction of the total mass (gas plus young stars) locked in young stars is systematically high (∼10 per cent) within the central 15 pc and systematically lower outside (2 per cent), which we interpret as variations in star formation efficiency. The inner 15 pc is dominated by young stars belonging to a centrally condensed cluster, while the outer parts are dominated by a dispersed population. Therefore, the observed trend could reflect a change of star formation efficiency between clustered and non-clustered star-formation.

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“…Between ∼ 100 pc and 1 kpc, the observed correlation between SFR and molecular gas progressively worsens as one moves to smaller scales, reaching multiple order of magnitudelevel scatter at ∼ 100 pc scales (Onodera et al 2010;Schruba et al 2010). Similarly, within the Milky Way, the amount of infrared or ionizing luminosity per unit molecular mass varies by several orders of magnitude from one giant molecular cloud to another (Mooney & Solomon 1988;Murray & Rahman 2010;Vutisalchavakul & Evans 2013). The scatter is not random: samples that select star-forming regions by ionizing luminosity or some other selection based on star formation rate tend to give ff ∼ 0.1 − 0.2, while those that select based on tracers of molecular gas mass instead find ff ∼ 0.001 or less.…”

Section: Sub-galactic Scalesmentioning

confidence: 98%

The big problems in star formation: The star formation rate, stellar clustering, and the initial mass function

2014

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Star formation lies at the center of a web of processes that drive cosmic evolution: generation of radiant energy, synthesis of elements, formation of planets, and development of life. Decades of observations have yielded a variety of empirical rules about how it operates, but at present we have no comprehensive, quantitative theory. In this review I discuss the current state of the field of star formation, focusing on three central questions: what controls the rate at which gas in a galaxy converts to stars? What determines how those stars are clustered, and what fraction of the stellar population ends up in gravitationally-bound structures? What determines the stellar initial mass function, and does it vary with star-forming environment? I use these three question as a lens to introduce the basics of star formation, beginning with a review of the observational phenomenology and the basic physical processes. I then review the status of current theories that attempt to solve each of the three problems, pointing out links between them and opportunities for theoretical and numerical work that crosses the scale between them. I conclude with a discussion of prospects for theoretical progress in the coming years.

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TESTING 24 μm AND INFRARED LUMINOSITY AS STAR FORMATION TRACERS FOR GALACTIC STAR-FORMING REGIONS

Cited by 23 publications

References 67 publications

Star Formation Relations in the Milky Way

Star Formation Relations in the Milky Way

Star formation rates from young-star counts and the structure of the ISM across the NGC 346/N66 complex in the SMC★

The big problems in star formation: The star formation rate, stellar clustering, and the initial mass function

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