The Single-cloud Star Formation Relation

Pokhrel, Riwaj; Gutermuth, Robert; Krumholz, Mark R.; Federrath, Christoph; Khullar, Shivan; Megeath, S. Thomas; Myers, Philip C.; Offner, Stella S. R.; Pipher, J. L.; Fischer, William J.; Henning, Thomas; Hora, Joseph

doi:10.3847/2041-8213/abf564

Cited by 46 publications

(97 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where the effective freefall time 𝑡 eff ff = √︁ 3π/32𝐺 𝜌 eff is computed from the time-varying half-mass volume-averaged density 𝜌 eff . This can be compared to recent measurements from Pokhrel et al (2021). The age cuts of < 0.5Myr and < 2Myr in Eqs 4-5 correspond to the commonly-assumed lifetimes of Class 0+I and II YSOs, respectively (Dunham et al 2014).…”

Section: Star Formation Efficiencymentioning

confidence: 91%

The dynamics and outcome of star formation with jets, radiation, winds, and supernovae in concert

Grudić,

Guszejnov,

Offner

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

We analyze the first giant molecular cloud (GMC) simulation to follow the formation of individual stars and their feedback from jets, radiation, winds, and supernovae, using the STARFORGE framework in the GIZMO code. We evolve the GMC for ∼ 9Myr, from initial turbulent collapse to dispersal by feedback. Protostellar jets dominate feedback momentum initially, but radiation and winds cause cloud disruption at ∼ 8% star formation efficiency (SFE), and the first supernova at 8.3Myr comes too late to influence star formation. The per-freefall SFE is dynamic, accelerating from 0 to ∼ 18% before dropping quickly to <1%, but the estimate from YSO counts compresses it to a narrower range. The primary cluster forms hierarchically and condenses to a brief (∼ 1 Myr) compact (∼ 1pc) phase, but does not virialize before the cloud disperses, and the stars end as an unbound expanding association. The initial mass function resembles the Chabrier ( 2005) form with a high-mass slope 𝛼 = −2 and a maximum mass of 55𝑀 . Stellar accretion takes ∼ 400kyr on average, but 1Myr for > 10𝑀 stars, so massive stars finish growing latest. The fraction of stars in multiples increases as a function of primary mass, as observed. Overall, the simulation much more closely resembles reality, compared to variations which neglect different feedback physics entirely. But more detailed comparison with synthetic observations is necessary to constrain the theoretical uncertainties.

show abstract

Section: Star Formation Efficiencymentioning

confidence: 91%

The dynamics and outcome of star formation with jets, radiation, winds, and supernovae in concert

Grudić,

Guszejnov,

Offner

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Unlike taking an average value of , which requires measured values of and an assumption as to how they should be weighted, this method directly uses the available data to estimate the parameter. Given this difference in methodology, it is interesting how similar this value is to the weighted mean = 2.06 ± 0.14 (with 95 per cent confidence intervals) for these regions and the mean value of = 2.0 for the 12 regions studied in Pokhrel et al (2020Pokhrel et al ( , 2021.…”

Section: Measured Yso Surface Density Relationsmentioning

confidence: 92%

“…Observationally, the smaller numbers of prestellar cores observed with higher densities also suggest that lifetime decreases with increasing density (Jessop & Ward-Thompson 2000;Könyves et al 2015). Finally, normalising the column density by the free-fall time results in a linear relationship between Σ gas / ff and Σ SFR (Pokhrel et al 2021). Hence it is likely that PC is lower at higher column densities.…”

Section: Changing Evolutionary Timescales With Column Densitymentioning

confidence: 93%

“…8 that different regions which have the same value of can have different values of r . Such differences in r are due to factors independent of column density that cause different amounts of star-formation, in particular the free-fall time (Pokhrel et al 2021). And so, while r is important for estimating the YSO densities using Eqn.…”

Section: Measured Yso Surface Density Relationsmentioning

confidence: 99%

“…There is some overlap between the regions tested in this paper and those tested in other works: Ophiuchus with a of 1.78 is exceptionally close to the value of 1.87 and 1.9 measured by Gutermuth et al (2011) and Pokhrel et al (2020) respectively, and IC348, within the Perseus molecular cloud shows a similar power law to Gutermuth et al (2011), though NGC1333 does not. Some of the variation in may be an indication of deviations from a = 2.0 power law at higher column densities (Pokhrel et al 2021). It is interesting that these power laws show such similarity given the differences in the methods of measuring the power law, the column density measures, identifying the YSOs and the star-forming regions used.…”

Section: Measured Yso Surface Density Relationsmentioning

confidence: 99%

See 2 more Smart Citations

Spatial statistics in star-forming regions: is star formation driven by column density alone?

Retter

Hatchell

Naylor

2021

Monthly Notices of the Royal Astronomical Society

View full text Add to dashboard Cite

Star formation is known to occur more readily where more raw materials are available. This is often expressed by a ‘Kennicutt–Schmidt’ relation where the surface density of Young Stellar Objects (YSOs) is proportional to column density to some power, μ. The aim of this work was to determine if column density alone is sufficient to explain the locations of Class 0/I YSOs within Serpens South, Serpens Core, Ophiuchus, NGC 1333 and IC348, or if there is clumping or avoidance that would point to additional influences on the star formation. Using the O-ring test as a summary statistic, 95 per cent confidence envelopes were produced for different values of μ from probability models made using the Herschel column density maps. The YSOs were tested against four distribution models: the best-estimate of μ for the region, μ = 0 above a minimum column density threshold and zero probability elsewhere, μ = 1, and the power-law that best represents the five regions as a collective, μ = 2.05 ± 0.20. Results showed that μ = 2.05 model was consistent with the majority of regions and, for those regions, the spatial distribution of YSOs at a given column density is consistent with being random. Serpens South and NGC 1333 rejected the μ = 2.05 model on small scales of ∼0.15 pc which implies that small-scale interactions may be necessary to improve the model. On scales above 0.15 pc, the positions of YSOs in all five regions can be well described using column density alone.

show abstract

Filament coalescence and hub structure in Mon R2

Kumar

Arzoumanian

Palmeirim

et al. 2022

A&A

View full text Add to dashboard Cite

There is growing evidence of the role of hub-filament systems (HFS) in the formation of stars from low to high masses. As of today, however, the detailed structures of these systems are still not well described. Here we study the Mon R2 star-forming region, which has a rich network of filaments joining in a star cluster forming hub, and aim to understand the hub structure and to examine the mass fraction residing in the hub and in the filaments, which is a key factor that influences massive star formation. We conducted a multi-scale, multi-component analysis of the Herschel column density maps (resolution of 18.2′′ or ~0.07 pc at 830 pc) of the region using a newly developed algorithm getsf to identify the structural components, namely, extended cloud, filaments, and sources. We find that cascades of lower column density filaments coalesce to form higher-density filaments eventually merging inside the hub (0.8 pc radius). As opposed to the previous view of the hub as a massive clump with ~1 pc radius, we find it to be a network of short high-density filaments. We analyse the orientations and mass per unit length (M∕L) of the filaments as a function of distance from the hub centre. The filaments are radially aligned towards the centre of the hub. The total mass reservoir in the Mon R2 HFS (5 pc × 5 pc) is split between filaments (54%), an extended cloud (37%), and sources (9%). The M∕L of filaments increases from ~10 M⊙ pc−1 at 1.5 pc from the hub to ~100 M⊙ pc−1 at its centre, while the number of filaments per annulus of 0.2 pc width decreases from 20 to two in the same range. The observed radial column density structure of the HFS (filament component only) displays a power-law dependence of NH2 ∝ r−2.17 up to a radius of ~2.5 pc from the central hub, resembling a global collapse of the HFS. We present a scenario where the HFS can be supported by magnetic fields which interact, merge, and reorganise themselves as the filaments coalesce. We plotted the plane-of-the-sky magnetic field line geometry using archival Planck data to support our scenario. In the new view of the hub as a network of high-density filaments, we suggest that only the stars located in the network can benefit from the longitudinal flows of gas to become massive, which may explain the reason for the formation of many low-mass stars in cluster centres. We show the correlation of massive stars in the region to the intertwined network-like hub, based on which we updated the implications of the filaments to clusters (F2C) model for massive star formation.

show abstract

The Single-cloud Star Formation Relation

Cited by 46 publications

References 74 publications

The dynamics and outcome of star formation with jets, radiation, winds, and supernovae in concert

The dynamics and outcome of star formation with jets, radiation, winds, and supernovae in concert

Spatial statistics in star-forming regions: is star formation driven by column density alone?

Filament coalescence and hub structure in Mon R2

Contact Info

Product

Resources

About