Efficiently Cooled Stellar Wind Bubbles in Turbulent Clouds. II. Validation of Theory with Hydrodynamic Simulations
TL;DR: In this paper, the authors developed a theory for the evolution of stellar wind driven bubbles in dense, turbulent clouds and validated their theory with three-dimensional, hydrodynamic simulations, showing that extreme cooling is not only possible, but is generic to star formation in turbulent clouds over more than three orders of magnitude in density.
Abstract: In a companion paper, we develop a theory for the evolution of stellar wind driven bubbles in dense, turbulent clouds. This theory proposes that turbulent mixing at a fractal bubble-shell interface leads to highly efficient cooling, in which the vast majority of the input wind energy is radiated away. This energy loss renders the majority of the bubble evolution momentum-driven rather than energy-driven, with expansion velocities and pressures orders of magnitude lower than in the classical Weaver77 solution. In this paper, we validate our theory with three-dimensional, hydrodynamic simulations. We show that extreme cooling is not only possible, but is generic to star formation in turbulent clouds over more than three orders of magnitude in density. We quantify the few free parameters in our theory, and show that the momentum exceeds the wind input rate by only a factor ~ 1.2-4. We verify that the bubble/cloud interface is a fractal with dimension ~ 2.5-2.7. The measured turbulent amplitude (v_t ~ 200-400 km/s) in the hot gas near the interface is shown to be consistent with theoretical requirements for turbulent diffusion to efficiently mix and radiate away most of the wind energy. The fraction of energy remaining after cooling is only 1-\Theta ~ 0.1-0.01, decreasing with time, explaining observations that indicate low hot-gas content and weak dynamical effects of stellar winds.
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TL;DR: In this article, the authors developed a theory for the evolution of bubbles driven by the collective winds from star clusters early in their lifetimes, which involves interaction with the turbulent, dense interstellar medium of the surrounding natal molecular cloud.
Abstract: Winds from massive stars have velocities of 1000 km/s or more, and produce hot, high pressure gas when they shock. We develop a theory for the evolution of bubbles driven by the collective winds from star clusters early in their lifetimes, which involves interaction with the turbulent, dense interstellar medium of the surrounding natal molecular cloud. A key feature is the fractal nature of the hot bubble's surface. The large area of this interface with surrounding denser gas strongly enhances energy losses from the hot interior, enabled by turbulent mixing and subsequent cooling at temperatures T = 10^4-10^5 K where radiation is maximally efficient. Due to the extreme cooling, the bubble radius scales differently (R ~ t^1/2) from the classical Weaver77 solution, and has expansion velocity and momentum lower by factors of 10-10^2 at given R, with pressure lower by factors of 10^2 - 10^3. Our theory explains the weak X-ray emission and low shell expansion velocities of observed sources. We discuss further implications of our theory for observations of the hot bubbles and cooled expanding shells created by stellar winds, and for predictions of feedback-regulated star formation in a range of environments. In a companion paper, we validate our theory with a suite of hydrodynamic simulations.
44 citations
TL;DR: The radiation from stars and active galactic nuclei (AGNs) creates photodissociation regions (PDRs) and X-ray-dominated regions (XDRs), where the chemistry or heating are dominated by far-ultraviolet (FUV) radiation or Xray radiation, respectively as discussed by the authors .
Abstract: The radiation from stars and active galactic nuclei (AGNs) creates photodissociation regions (PDRs) and X-ray-dominated regions (XDRs), where the chemistry or heating are dominated by far-ultraviolet (FUV) radiation or X-ray radiation, respectively. PDRs include a wide range of environments, from the diffuse interstellar medium to dense star-forming regions. XDRs are found in the center of galaxies hosting AGNs, in protostellar disks, and in the vicinity of X-ray binaries. In this review, we describe the dominant thermal, chemical, and radiation transfer processes in PDRs and XDRs, as well as give a brief description of models and their use for analyzing observations. We then present recent results from Milky Way, nearby extragalactic, and high-redshift observations. Several important results include the following: ▪ Velocity-resolved PDR lines reveal the kinematics of the neutral atomic gas and provide constraints on the stellar feedback process. Their interpretation is, however, in dispute, as observations suggest a prominent role for stellar winds, whereas they are much less important in theoretical models. ▪ A significant fraction of molecular mass resides in CO-dark gas especially in low-metallicity and/or highly irradiated environments. ▪ The CO ladder and [Ci][Formula: see text][Cii] ratios can determine if FUV or X rays dominate the ISM heating of extragalactic sources. ▪ With Atacama Large Millimeter/submillimeter Array, PDR and XDR tracers are now routinely detected on galactic scales over cosmic time. This makes it possible to link the star-formation history of the Universe to the evolution of the physical and chemical properties of the gas. Expected final online publication date for the Annual Review of Astronomy and Astrophysics Volume 60 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
32 citations
TL;DR: In this article , the authors analyze the first giant molecular cloud 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.
Abstract: 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 significantly. 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 55 𝑀 (cid:12) . Stellar accretion takes ∼ 400kyr on average, but (cid:38) 1Myr for > 10 𝑀 (cid:12) 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 previous versions that neglected different feedback physics entirely. But more detailed comparison with synthetic observations will be needed to constrain the theoretical uncertainties.
31 citations
TL;DR: In this article , the authors analyse the first 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.
Abstract: ABSTRACT We analyse 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 $\sim 9 \rm Myr$, from initial turbulent collapse to dispersal by feedback. Protostellar jets dominate feedback momentum initially, but radiation and winds cause cloud disruption at $\sim 8{{\ \rm per\ cent}}$ star formation efficiency (SFE), and the first supernova at $8.3\, \rm Myr$ comes too late to influence star formation significantly. The per-free-fall SFE is dynamic, accelerating from 0 per cent to $\sim 18{{\ \rm per\ cent}}$ before dropping quickly to <1 per cent, but the estimate from YSO counts compresses it to a narrower range. The primary cluster forms hierarchically and condenses to a brief ($\sim 1\, \mathrm{Myr}$) compact ($\sim 1\, \rm pc$) 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 55 M⊙. Stellar accretion takes $\sim 400\, \rm kyr$ on average, but $\gtrsim 1\,\rm Myr$ for >10 M⊙ stars, so massive stars finish growing latest. The fraction of stars in multiples increase as a function of primary mass, as observed. Overall, the simulation much more closely resembles reality, compared to previous versions that neglected different feedback physics entirely. But more detailed comparison with synthetic observations will be needed to constrain the theoretical uncertainties.
29 citations
University of Bonn1, Heidelberg University2, Princeton University3, INAF4, University of Chile5, Carnegie Institution for Science6, University of Wyoming7, Moscow State University8, European Southern Observatory9, Australian National University10, University of Western Australia11, Ohio State University12, Liverpool John Moores University13, Max Planck Society14, Ghent University15, National Radio Astronomy Observatory16, University of Alberta17
TL;DR: In this paper, the authors assess the feedback mechanisms acting within a sample of 5810 HII regions identified from the PHANGS-MUSE survey of 19 nearby ($ 1), yet there is a small sample of compact H II regions with $P_\mathrm{tot,max}/P_ \mathm{de} < 1$ ($sim$1% of the sample).
Abstract: The feedback from young stars (i.e. pre-supernova) is thought to play a crucial role in molecular cloud destruction. In this paper, we assess the feedback mechanisms acting within a sample of 5810 HII regions identified from the PHANGS-MUSE survey of 19 nearby ($ 1$, and expanding, yet there is a small sample of compact HII regions with $P_\mathrm{tot,max}/P_\mathrm{de} < 1$ ($\sim$1% of the sample). These mostly reside in galaxy centres ($R_\mathrm{gal}<1$kpc), or, specifically, environments of high gas surface density; log($\Sigma_\mathrm{gas}/\mathrm{M_\odot} \mathrm{pc}^{-2}$)$\sim$2.5 (measured on kpc-scales). Lastly, we compare to a sample of literature measurements for $P_\mathrm{therm}$ and $P_\mathrm{rad}$ to investigate how dominant pressure term transitions over around 5dex in spatial dynamic range and 10 dex in pressure.
21 citations
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TL;DR: Matplotlib is a 2D graphics package used for Python for application development, interactive scripting, and publication-quality image generation across user interfaces and operating systems.
Abstract: Matplotlib is a 2D graphics package used for Python for application development, interactive scripting,and publication-quality image generation across user interfaces and operating systems
23,312 citations
Max Planck Society1, Yale University2, Space Telescope Science Institute3, Harvard University4, University of Colorado Boulder5, Columbia University6, University of Toronto7, Argonne National Laboratory8, Ohio State University9, European Southern Observatory10, Aix-Marseille University11, ETH Zurich12, California Institute of Technology13, New York University14, Louisiana State University15, Australian National University16, Cornell University17, University College London18, Goddard Space Flight Center19, Leibniz Institute for Astrophysics Potsdam20
TL;DR: Astropy as discussed by the authors is a Python package for astronomy-related functionality, including support for domain-specific file formats such as flexible image transport system (FITS) files, Virtual Observatory (VO) tables, common ASCII table formats, unit and physical quantity conversions, physical constants specific to astronomy, celestial coordinate and time transformations, world coordinate system (WCS) support, generalized containers for representing gridded as well as tabular data, and a framework for cosmological transformations and conversions.
Abstract: We present the first public version (v02) of the open-source and community-developed Python package, Astropy This package provides core astronomy-related functionality to the community, including support for domain-specific file formats such as flexible image transport system (FITS) files, Virtual Observatory (VO) tables, and common ASCII table formats, unit and physical quantity conversions, physical constants specific to astronomy, celestial coordinate and time transformations, world coordinate system (WCS) support, generalized containers for representing gridded as well as tabular data, and a framework for cosmological transformations and conversions Significant functionality is under activedevelopment, such as a model fitting framework, VO client and server tools, and aperture and point spread function (PSF) photometry tools The core development team is actively making additions and enhancements to the current code base, and we encourage anyone interested to participate in the development of future Astropy versions
9,720 citations
TL;DR: In this paper, the uncertainty inherent in any observational estimate of the IMF is investigated by studying the scatter introduced by Poisson noise and the dynamical evolution of star clusters, and it is found that this apparent scatter reproduces quite well the observed scatter in power-law index determinations, thus defining the fundamental limit within which any true variation becomes undetectable.
Abstract: A universal initial mass function (IMF) is not intuitive, but so far no convincing evidence for a variable IMF exists. The detection of systematic variations of the IMF with star-forming conditions would be the Rosetta Stone for star formation.
In this contribution an average or Galactic-field IMF is defined, stressing that there is evidence for a change in the power-law index at only two masses: near 0.5 M⊙ and near 0.08 M⊙. Using this supposed universal IMF, the uncertainty inherent in any observational estimate of the IMF is investigated by studying the scatter introduced by Poisson noise and the dynamical evolution of star clusters. It is found that this apparent scatter reproduces quite well the observed scatter in power-law index determinations, thus defining the fundamental limit within which any true variation becomes undetectable. The absence of evidence for a variable IMF means that any true variation of the IMF in well-studied populations must be smaller than this scatter.
Determinations of the power-law indices α are subject to systematic errors arising mostly from unresolved binaries. The systematic bias is quantified here, with the result that the single-star IMFs for young star clusters are systematically steeper by Δα≈0.5 between 0.1 and 1 M⊙ than the Galactic-field IMF, which is populated by, on average, about 5-Gyr-old stars. The MFs in globular clusters appear to be, on average, systematically flatter than the Galactic-field IMF (Piotto & Zoccali; Paresce & De Marchi), and the recent detection of ancient white-dwarf candidates in the Galactic halo and the absence of associated low-mass stars (Ibata et al.; Mendez & Minniti) suggest a radically different IMF for this ancient population. Star formation in higher metallicity environments thus appears to produce relatively more low-mass stars. While still tentative, this is an interesting trend, being consistent with a systematic variation of the IMF as expected from theoretical arguments.
6,784 citations
University of Jyväskylä1, California Polytechnic State University2, University of California, Los Angeles3, Los Alamos National Laboratory4, National Research University – Higher School of Economics5, University of California, Berkeley6, University of Birmingham7, Australian Nuclear Science and Technology Organisation8, University of Washington9, University of Massachusetts Amherst10, University of West Bohemia11, Brigham Young University12, University of Texas at Austin13, Universidade Federal de Minas Gerais14, Google15
TL;DR: SciPy as discussed by the authors is an open-source scientific computing library for the Python programming language, which has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year.
Abstract: SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
6,244 citations
TL;DR: Starburst99 as mentioned in this paper is a comprehensive set of model predictions for spectrophotometric and related properties of galaxies with active star formation, which is an improved and extended version of the data set previously published by Leitherer & Heckman.
Abstract: Starburst99 is a comprehensive set of model predictions for spectrophotometric and related properties of galaxies with active star formation. The models are an improved and extended version of the data set previously published by Leitherer & Heckman. We have upgraded our code by implementing the latest set of stellar evolution models of the Geneva group and the model atmosphere grid compiled by Lejeune et al. Several predictions which were not included in the previous publication are shown here for the first time. The models are presented in a homogeneous way for five metallicities between Z = 0.040 and 0.001 and three choices of the initial mass function. The age coverage is 106—109 yr. We also show the spectral energy distributions which are used to compute colors and other quantities. The full data set is available for retrieval at a Web site, which allows users to run specific models with nonstandard parameters as well. We also make the source code available to the community.
4,212 citations