Dynamics of dusty radiation-pressure-driven shells and clouds: fast outflows from galaxies, star clusters, massive stars, and AGN
Bibliographic record
Abstract
It is typically assumed that radiation-pressure-driven winds are accelerated to an asymptotic velocity of v∞ ≃ vesc, where vesc is the escape velocity from the central source. We note that this is not the case for dusty shells and clouds. Instead, if the shell or cloud is initially optically thick to the UV emission from the source of luminosity L, then there is a significant boost in v∞ that reflects the integral of the momentum absorbed as it is accelerated. For shells reaching a generalized Eddington limit, we show that v∞ ≃ (4RUVL/Mshc)1/2, in both point-mass and isothermal-sphere potentials, where RUV is the radius where the shell becomes optically thin to UV photons, and Msh is the mass of the shell. The asymptotic velocity significantly exceeds vesc for typical parameters, and can explain the ∼1000–2000 km s−1 outflows observed from rapidly star-forming galaxies and active galactic nuclei (AGN) if the surrounding halo has low gas density. Similarly fast outflows from massive stars can be accelerated on ∼few–103 yr time-scales. These results carry over to clouds that subtend only a small fraction of the solid angle from the source of radiation and that expand as a consequence of their internal sound speed. We further consider the dynamics of shells that sweep up a dense circumstellar or circumgalactic medium. We calculate the ‘momentum ratio’ |$\dot{M} v/(L/c)$| in the shell limit and show that it can only significantly exceed ∼2 if the effective optical depth of the shell to re-radiated far-infrared photons is much larger than unity. We discuss simple prescriptions for the properties of galactic outflows for use in large-scale cosmological simulations. We also briefly discuss applications to the dusty ejection episodes of massive stars, the disruption of giant molecular clouds, and AGN.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".