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Journal ArticleDOI

Efficiently Cooled Stellar Wind Bubbles in Turbulent Clouds. I. Fractal Theory and Application to Star-forming Clouds

01 Jun 2021-The Astrophysical Journal (American Astronomical Society)-Vol. 914, Iss: 2, pp 89
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.
Citations
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Journal ArticleDOI
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.

37 citations

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
TL;DR: In this article , a pressure-regulated, feedback-modulated (PRFM) theory of the star-forming ISM was proposed, leading to a prediction that the star formation rate per unit area, ΣSFR, will scale nearly linearly with ISM weight.
Abstract: The star formation rate (SFR) in galactic disks depends on both the quantity of the available interstellar medium (ISM) gas and its physical state. Conversely, the ISM’s physical state depends on the SFR, because the “feedback” energy and momentum injected by recently formed massive stars is crucial to offsetting losses from turbulent dissipation and radiative cooling. The ISM’s physical state also responds to the gravitational field that confines it, with increased weight driving higher pressure. In a quasi-steady state, it is expected that the mean total pressure of different thermal phases will match each other, that the component pressures and total pressure will satisfy thermal and dynamical equilibrium requirements, and that the SFR will adjust as needed to provide the requisite stellar radiation and supernova feedback. The pressure-regulated, feedback-modulated (PRFM) theory of the star-forming ISM formalizes these ideas, leading to a prediction that the SFR per unit area, ΣSFR, will scale nearly linearly with ISM weight  . In terms of the large-scale gas surface density Σgas, stellar plus dark matter density ρ sd, and effective ISM velocity dispersion σ eff, an observable weight estimator is ≈PDE=πGΣgas2/2+Σgas(2Gρsd)1/2σeff , and this is predicted to match the total midplane pressure P tot. Using a suite of multiphase magnetohydrodynamic simulations run with the TIGRESS computational framework, we test the principles of the PRFM model and calibrate the total feedback yield ϒtot = P tot/ΣSFR ∼ 1000 km s−1, as well as its components. We compare the results from TIGRESS to theory, previous numerical simulations, and observations, finding excellent agreement.

16 citations

Journal ArticleDOI
TL;DR: In this article, the authors used ALMA data at 350 GHz with 28 milliarcsecond (0.5 pc) resolution to detect blueshifted absorption and redshifted emission (P-Cygni profiles) towards three super star clusters in multiple lines, including CS 7$-$6 and H$−13$CN 4$-$3, which represents direct evidence for previously unobserved outflows.
Abstract: Young massive clusters play an important role in the evolution of their host galaxies, and feedback from the high-mass stars in these clusters can have profound effects on the surrounding interstellar medium. The nuclear starburst in the nearby galaxy NGC253 at a distance of 3.5 Mpc is a key laboratory in which to study star formation in an extreme environment. Previous high resolution (1.9 pc) dust continuum observations from ALMA discovered 14 compact, massive super star clusters (SSCs) still in formation. We present here ALMA data at 350 GHz with 28 milliarcsecond (0.5 pc) resolution. We detect blueshifted absorption and redshifted emission (P-Cygni profiles) towards three of these SSCs in multiple lines, including CS 7$-$6 and H$^{13}$CN 4$-$3, which represents direct evidence for previously unobserved outflows. The mass contained in these outflows is a significant fraction of the cluster gas masses, which suggests we are witnessing a short but important phase. Further evidence of this is the finding of a molecular shell around the only SSC visible at near-IR wavelengths. We model the P-Cygni line profiles to constrain the outflow geometry, finding that the outflows must be nearly spherical. Through a comparison of the outflow properties with predictions from simulations, we find that none of the available mechanisms completely explains the observations, although dust-reprocessed radiation pressure and O star stellar winds are the most likely candidates. The observed outflows will have a very substantial effect on the clusters' evolution and star formation efficiency.

14 citations

References
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Journal ArticleDOI
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

Journal ArticleDOI
16 Sep 2020-Nature
TL;DR: In this paper, the authors review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data, and their evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.
Abstract: Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis. NumPy is the primary array programming library for Python; here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.

7,624 citations

Journal ArticleDOI
Pavel Kroupa1
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

Journal ArticleDOI
TL;DR: In this article, the authors focus on the broad patterns in the star formation properties of galaxies along the Hubble sequence and their implications for understanding galaxy evolution and the physical processes that drive the evolution.
Abstract: Observations of star formation rates (SFRs) in galaxies provide vital clues to the physical nature of the Hubble sequence and are key probes of the evolutionary histories of galaxies. The focus of this review is on the broad patterns in the star formation properties of galaxies along the Hubble sequence and their implications for understanding galaxy evolution and the physical processes that drive the evolution. Star formation in the disks and nuclear regions of galaxies are reviewed separately, then discussed within a common interpretive framework. The diagnostic methods used to measure SFRs are also reviewed, and a self-consistent set of SFR calibrations is presented as an aid to workers in the field. One of the most recognizable features of galaxies along the Hubble sequence is the wide range in young stellar content and star formation activity. This variation in stellar content is part of the basis of the Hubble classification itself (Hubble 1926), and understanding its physical nature and origins is fundamental to understanding galaxy evolution in its broader context. This review deals with the global star formation properties of galaxies, the systematics of those properties along the Hubble sequence, and their implications for galactic evolution. I interpret “Hubble sequence” in this context very loosely, to encompass not only morphological type but other properties such as gas content, mass, bar structure, and dynamical environment, which can strongly influence the largescale star formation rate (SFR).

6,640 citations

Journal ArticleDOI
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