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Fast and inefficient star formation due to short-lived molecular clouds and rapid feedback

Nature volume 569, pages 519–522 (2019)Cite this article

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Abstract

The physics of star formation and the deposition of mass, momentum and energy into the interstellar medium by massive stars (‘feedback’) are the main uncertainties in modern cosmological simulations of galaxy formation and evolution1,2. These processes determine the properties of galaxies3,4 but are poorly understood on the scale of individual giant molecular clouds (less than 100 parsecs)5,6, which are resolved in modern galaxy formation simulations7,8. The key question is why the timescale for depleting molecular gas through star formation in galaxies (about 2 billion years)9,10 exceeds the cloud dynamical timescale by two orders of magnitude11. Either most of a cloud’s mass is converted into stars over many dynamical times12 or only a small fraction turns into stars before the cloud is dispersed on a dynamical timescale13,14. Here we report high-angular-resolution observations of the nearby flocculent spiral galaxy NGC 300. We find that the molecular gas and high-mass star formation on the scale of giant molecular clouds are spatially decorrelated, in contrast to their tight correlation on galactic scales5. We demonstrate that this decorrelation implies rapid evolutionary cycling between clouds, star formation and feedback. We apply a statistical method15,16 to quantify the evolutionary timeline and find that star formation is regulated by efficient stellar feedback, which drives cloud dispersal on short timescales (around 1.5 million years). The rapid feedback arises from radiation and stellar winds, before supernova explosions can occur. This feedback limits cloud lifetimes to about one dynamical timescale (about 10 million years), with integrated star formation efficiencies of only 2 to 3 per cent. Our findings reveal that galaxies consist of building blocks undergoing vigorous, feedback-driven life cycles that vary with the galactic environment and collectively define how galaxies form stars.

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Fig. 1: Decorrelation of molecular gas and young stellar emission on sub-kiloparsec scales.
Fig. 2: Radial profiles of constrained quantities in comparison to theoretical predictions.
Fig. 3: Dependence of measured quantities on spatial resolution.

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Data availability

The ALMA CO(1–0) data used in this work are from projects 2013.1.00351.S and 2015.1.00258.S (PI A. Schruba) and are publicly available through the ALMA archive (https://almascience.eso.org/alma-data/archive). The MPG/ESO 2.2-m Hα data are publicly available as raw data from the ESO archive (http://archive.eso.org/) under programme ID 065.N-0076 (PI F. Bresolin). All other (for example, derived) data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

A dedicated publication of the analysis software used in the current study is in preparation. The code is available from the corresponding author upon reasonable request.

References

  1. Somerville, R. S. & Davé, R. Physical models of galaxy formation in a cosmological framework. Annu. Rev. Astron. Astrophys. 53, 51–113 (2015).

    ADS  CAS  Google Scholar 

  2. Naab, T. & Ostriker, J. P. Theoretical challenges in galaxy formation. Annu. Rev. Astron. Astrophys. 55, 59–109 (2017).

    ADS  CAS  Google Scholar 

  3. Scannapieco, C. et al. The Aquila comparison project: the effects of feedback and numerical methods on simulations of galaxy formation. Mon. Not. R. Astron. Soc. 423, 1726–1749 (2012).

    ADS  Google Scholar 

  4. Hopkins, P. F., Narayanan, D. & Murray, N. The meaning and consequences of star formation criteria in galaxy models with resolved stellar feedback. Mon. Not. R. Astron. Soc. 432, 2647–2653 (2013).

    ADS  Google Scholar 

  5. Kennicutt, R. C. & Evans, N. J. Star formation in the Milky Way and nearby galaxies. Annu. Rev. Astron. Astrophys. 50, 531–608 (2012).

    ADS  CAS  Google Scholar 

  6. Krumholz, M. R. The big problems in star formation: the star formation rate, stellar clustering, and the initial mass function. Phys. Rep. 539, 49–134 (2014).

    ADS  MathSciNet  Google Scholar 

  7. Grand, R. J. J. et al. The Auriga Project: the properties and formation mechanisms of disc galaxies across cosmic time. Mon. Not. R. Astron. Soc. 467, 179–207 (2017).

    ADS  CAS  Google Scholar 

  8. Hopkins, P. F. et al. FIRE-2 simulations: physics versus numerics in galaxy formation. Mon. Not. R. Astron. Soc. 480, 800–863 (2018).

    ADS  Google Scholar 

  9. Bigiel, F. et al. The star formation law in nearby galaxies on sub-kpc scales. Astron. J. 136, 2846–2871 (2008).

    ADS  CAS  Google Scholar 

  10. Calzetti, D., Liu, G. & Koda, J. Star formation laws: the effects of gas cloud sampling. Astrophys. J. 752, 98 (2012).

    ADS  Google Scholar 

  11. Zuckerman, B. & Palmer, P. Radio radiation from interstellar molecules. Annu. Rev. Astron. Astrophys. 12, 279–313 (1974).

    ADS  Google Scholar 

  12. Koda, J. et al. Dynamically driven evolution of the interstellar medium in M51. Astrophys. J. Lett. 700, L132–L136 (2009).

    ADS  CAS  Google Scholar 

  13. Leisawitz, D., Bash, F. N. & Thaddeus, P. A CO survey of regions around 34 open clusters. Astrophys. J. 70 (Suppl.), 731–812 (1989).

    ADS  CAS  Google Scholar 

  14. Elmegreen, B. G. Star formation in a crossing time. Astrophys. J. 530, 277–281 (2000).

    ADS  CAS  Google Scholar 

  15. Kruijssen, J. M. D. & Longmore, S. N. An uncertainty principle for star formation—I. Why galactic star formation relations break down below a certain spatial scale. Mon. Not. R. Astron. Soc. 439, 3239–3252 (2014).

    ADS  Google Scholar 

  16. Kruijssen, J. M. D. et al. An uncertainty principle for star formation—II. A new method for characterizing the cloud-scale physics of star formation and feedback across cosmic history. Mon. Not. R. Astron. Soc. 479, 1866–1952 (2018).

    ADS  Google Scholar 

  17. Schruba, A., Leroy, A. K., Walter, F., Sandstrom, K. & Rosolowsky, E. The scale dependence of the molecular gas depletion time in M33. Astrophys. J. 722, 1699–1706 (2010).

    ADS  CAS  Google Scholar 

  18. Dobbs, C. L. & Pringle, J. E. The exciting lives of giant molecular clouds. Mon. Not. R. Astron. Soc. 432, 653–667 (2013).

    ADS  CAS  Google Scholar 

  19. Jeffreson, S. M. R. & Kruijssen, J. M. D. A general theory for the lifetimes of giant molecular clouds under the influence of galactic dynamics. Mon. Not. R. Astron. Soc. 476, 3688–3715 (2018).

    ADS  CAS  Google Scholar 

  20. Tan, J. C. Star formation rates in disk galaxies and circumnuclear starbursts from cloud collisions. Astrophys. J. 536, 173–184 (2000).

    ADS  Google Scholar 

  21. Schaye, J. et al. The EAGLE project: simulating the evolution and assembly of galaxies and their environments. Mon. Not. R. Astron. Soc. 446, 521–554 (2015).

    ADS  CAS  Google Scholar 

  22. Pillepich, A. et al. Simulating galaxy formation with the IllustrisTNG model. Mon. Not. R. Astron. Soc. 473, 4077–4106 (2018).

    ADS  Google Scholar 

  23. McKee, C. F. & Ostriker, J. P. A theory of the interstellar medium—three components regulated by supernova explosions in an inhomogeneous substrate. Astrophys. J. 218, 148–169 (1977).

    ADS  CAS  Google Scholar 

  24. Hopkins, P. F., Quataert, E. & Murray, N. The structure of the interstellar medium of star-forming galaxies. Mon. Not. R. Astron. Soc. 421, 3488–3521 (2012).

    ADS  CAS  Google Scholar 

  25. Vutisalchavakul, N., Evans, N. J. II & Battersby, C. The star-formation relation for regions in the galactic plane: the effect of spatial resolution. Astrophys. J. 797, 77 (2014).

    ADS  Google Scholar 

  26. Bolatto, A. D. et al. Suppression of star formation in the galaxy NGC 253 by a starburst-driven molecular wind. Nature 499, 450–453 (2013).

    ADS  CAS  PubMed  Google Scholar 

  27. Muratov, A. L. et al. Gusty, gaseous flows of FIRE: galactic winds in cosmological simulations with explicit stellar feedback. Mon. Not. R. Astron. Soc. 454, 2691–2713 (2015).

    ADS  CAS  Google Scholar 

  28. Westmeier, T., Braun, R. & Koribalski, B. S. Gas and dark matter in the Sculptor group: NGC 300. Mon. Not. R. Astron. Soc. 410, 2217–2236 (2011).

    ADS  CAS  Google Scholar 

  29. Agertz, O., Kravtsov, A. V., Leitner, S. N. & Gnedin, N. Y. Toward a complete accounting of energy and momentum from stellar feedback in galaxy formation simulations. Astrophys. J. 770, 25 (2013).

    ADS  Google Scholar 

  30. Genzel, R. et al. The SINS survey of z ~ 2 galaxy kinematics: properties of the giant star-forming clumps. Astrophys. J. 733, 101 (2011).

    ADS  Google Scholar 

  31. Bolatto, A. D., Wolfire, M. & Leroy, A. K. The CO-to-H2 conversion factor. Annu. Rev. Astron. Astrophys. 51, 207–268 (2013).

    ADS  CAS  Google Scholar 

  32. Wong, T. et al. The Magellanic Mopra Assessment (MAGMA). I. The molecular cloud population of the Large Magellanic Cloud. Astrophys. J. 197 (Suppl.), 16 (2011).

    Google Scholar 

  33. Druard, C. et al. The IRAM M 33 CO(2−1) survey. A complete census of molecular gas out to 7 kpc. Astron. Astrophys. 567, A118 (2014).

    Google Scholar 

  34. Faesi, C. M., Lada, C. J., Forbrich, J., Menten, K. M. & Bouy, H. Molecular cloud-scale star formation in NGC 300. Astrophys. J. 789, 81 (2014).

    ADS  Google Scholar 

  35. Roussel, H. et al. Extinction law variations and dust excitation in the spiral galaxy NGC 300. Astrophys. J. 632, 227–252 (2005).

    ADS  CAS  Google Scholar 

  36. Luridiana, V., Morisset, C. & Shaw, R. A. PyNeb: a new tool for analyzing emission lines. I. Code description and validation of results. Astron. Astrophys. 573, A42 (2015).

    ADS  Google Scholar 

  37. Leitherer, C. et al. Starburst99: synthesis models for galaxies with active star formation. Astrophys. J. 123 (Suppl.), 3–40 (1999).

    CAS  Google Scholar 

  38. Haydon, D. T. et al. An uncertainty principle for star formation — III. The characteristic time-scales of star formation rate tracers. Preprint at https://arxiv.org/abs/1810.10897 (2018).

  39. Murphy, E. J. et al. Calibrating extinction-free star formation rate diagnostics with 33 GHz free–free emission in NGC 6946. Astrophys. J. 737, 67 (2011).

    ADS  Google Scholar 

  40. Kroupa, P. On the variation of the initial mass function. Mon. Not. R. Astron. Soc. 322, 231–246 (2001).

    ADS  Google Scholar 

  41. Kang, X., Zhang, F., Chang, R., Wang, L. & Cheng, L. The star formation history of low-mass disk galaxies: a case study of NGC 300. Astron. Astrophys. 585, A20 (2016).

    ADS  Google Scholar 

  42. Dalcanton, J. J. et al. The ACS Nearby Galaxy Survey Treasury. Astrophys. J. 183 (Suppl.), 67–108 (2009).

    Google Scholar 

  43. Koch, E. W. et al. Kinematics of the atomic ISM in M33 on 80 pc scales. Mon. Not. R. Astron. Soc. 479, 2505–2533 (2018).

    ADS  Google Scholar 

  44. Dale, D. A. et al. The Spitzer Local Volume Legacy: Survey Description and Infrared Photometry. Astrophys. J. 703, 517–556 (2009).

    ADS  CAS  Google Scholar 

  45. Querejeta, M. et al. The Spitzer Survey of Stellar Structure in Galaxies (S4G): precise stellar mass distributions from automated dust correction at 3.6 μm. Astrophys. J. 219 (Suppl.), 5 (2015).

    Google Scholar 

  46. Meidt, S. E. et al. Reconstructing the Stellar Mass Distributions of Galaxies Using S4G IRAC 3.6 and 4.5 μm images. I. Correcting for contamination by polycyclic aromatic hydrocarbons, hot dust, and intermediate-age stars. Astrophys. J. 744, 17 (2012).

    ADS  Google Scholar 

  47. Leroy, A. K. et al. The star formation efficiency in nearby galaxies: measuring where gas forms stars effectively. Astron. J. 136, 2782–2845 (2008).

    ADS  CAS  Google Scholar 

  48. Meidt, S. E. et al. Reconstructing the stellar mass distributions of galaxies using S4G IRAC 3.6 and 4.5 μm images. II. The conversion from light to mass. Astrophys. J. 788, 144 (2014).

    ADS  Google Scholar 

  49. Faesi, C. M., Lada, C. J. & Forbrich, J. The ALMA view of GMCs in NGC 300: physical properties and scaling relations at 10 pc resolution. Astrophys. J. 857, 19 (2018).

    ADS  Google Scholar 

  50. van der Kruit, P. C. & Freeman, K. C. Galaxy disks. Annu. Rev. Astron. Astrophys. 49, 301–371 (2011).

    ADS  Google Scholar 

  51. Gogarten, S. M. et al. The Advanced Camera for Surveys Nearby Galaxy Survey Treasury. V. Radial star formation history of NGC 300. Astrophys. J. 712, 858–874 (2010).

    ADS  Google Scholar 

  52. Bresolin, F. et al. Extragalactic chemical abundances: do H ii regions and young stars tell the same story? The case of the spiral galaxy NGC 300. Astrophys. J. 700, 309–330 (2009).

    ADS  CAS  Google Scholar 

  53. Saintonge, A. et al. xCOLD GASS: The complete IRAM 30 m legacy survey of molecular gas for galaxy evolution studies. Astrophys. J. 233 (Suppl.), 22 (2017).

    Google Scholar 

  54. Catinella, B. et al. xGASS: total cold gas scaling relations and molecular-to-atomic gas ratios of galaxies in the local Universe. Mon. Not. R. Astron. Soc. 476, 875–895 (2018).

    ADS  CAS  Google Scholar 

  55. Moster, B. P., Naab, T. & White, S. D. M. Galactic star formation and accretion histories from matching galaxies to dark matter haloes. Mon. Not. R. Astron. Soc. 428, 3121–3138 (2013).

    ADS  Google Scholar 

  56. Bland-Hawthorn, J. & Gerhard, O. The Galaxy in context: structural, kinematic, and integrated properties. Annu. Rev. Astron. Astrophys. 54, 529–596 (2016).

    ADS  CAS  Google Scholar 

  57. Rosolowsky, E. & Leroy, A. Bias-free measurement of giant molecular cloud properties. Publ. Astron. Soc. Pacif. 118, 590–610 (2006).

    ADS  Google Scholar 

  58. Leroy, A. K. et al. ALMA reveals the molecular medium fueling the nearest nuclear starburst. Astrophys. J. 801, 25 (2015).

    ADS  Google Scholar 

  59. Solomon, P. M., Rivolo, A. R., Barrett, J. & Yahil, A. Mass, luminosity, and line width relations of galactic molecular clouds. Astrophys. J. 319, 730–741 (1987).

    ADS  CAS  Google Scholar 

  60. Williams, J. P., de Geus, E. J. & Blitz, L. Determining structure in molecular clouds. Astrophys. J. 428, 693–712 (1994).

    ADS  CAS  Google Scholar 

  61. da Silva, R. L., Fumagalli, M. & Krumholz, M. SLUG—stochastically lighting up galaxies. I. Methods and validating tests. Astrophys. J. 745, 145 (2012).

    ADS  Google Scholar 

  62. Krumholz, M. R., Fumagalli, M., da Silva, R. L., Rendahl, T. & Parra, J. SLUG—stochastically lighting up galaxies. III. A suite of tools for simulated photometry, spectroscopy, and Bayesian inference with stochastic stellar populations. Mon. Not. R. Astron. Soc. 452, 1447–1467 (2015).

    ADS  CAS  Google Scholar 

  63. Hygate, A. P. S. et al. An uncertainty principle for star formation — IV. On the nature and filtering of diffuse emission. Preprint available at https://arxiv.org/abs/1810.11405 (2018).

  64. Schruba, A. et al. A molecular star formation law in the atomic-gas-dominated regime in nearby galaxies. Astron. J. 142, 37 (2011).

    ADS  Google Scholar 

  65. Leroy, A. K. et al. Molecular gas and star formation in nearby disk galaxies. Astron. J. 146, 19 (2013).

    ADS  Google Scholar 

  66. Pety, J. et al. The Plateau de Bure + 30 m Arcsecond Whirlpool Survey reveals a thick disk of diffuse molecular gas in the M51 galaxy. Astrophys. J. 779, 43 (2013).

    ADS  Google Scholar 

  67. Schruba, A. et al. Physical properties of molecular clouds at 2 pc resolution in the low-metallicity dwarf galaxy NGC 6822 and the Milky Way. Astrophys. J. 835, 278 (2017).

    ADS  Google Scholar 

  68. Krumholz, M. R., Dekel, A. & McKee, C. F. A. Universal, local star formation law in galactic clouds, nearby galaxies, high-redshift disks, and starbursts. Astrophys. J. 745, 69 (2012).

    ADS  Google Scholar 

  69. Elmegreen, B. G. Supercloud formation by nonaxisymmetric gravitational instabilities in sheared magnetic galaxy disks. Astrophys. J. 312, 626–639 (1987).

    ADS  Google Scholar 

  70. Leitherer, C. et al. The effects of stellar rotation. II. A comprehensive set of Starburst99 models. Astrophys. J. 212 (Suppl.), 14 (2014).

    Google Scholar 

  71. Spitzer, L. Physical Processes in the Interstellar Medium (Wiley-Interscience, 1978).

  72. Hosokawa, T. & Inutsuka, S.-i. Dynamical expansion of ionization and dissociation front around a massive star. II. On the generality of triggered star formation. Astrophys. J. 646, 240–257 (2006).

    CAS  Google Scholar 

  73. Tielens, A. G. G. M. The Physics and Chemistry of the Interstellar Medium (Cambridge Univ. Press, 2005).

  74. Weaver, R., McCray, R., Castor, J., Shapiro, P. & Moore, R. Interstellar bubbles. II Structure and evolution. Astrophys. J. 218, 377–395 (1977).

    ADS  CAS  Google Scholar 

  75. Mac Low, M.-M. & McCray, R. Superbubbles in disk galaxies. Astrophys. J. 324, 776–785 (1988).

    ADS  Google Scholar 

  76. Thompson, T. A., Quataert, E. & Murray, N. Radiation pressure-supported starburst disks and active galactic nucleus fueling. Astrophys. J. 630, 167–185 (2005).

    ADS  Google Scholar 

  77. Krumholz, M. R. & Thompson, T. A. Direct numerical simulation of radiation pressure-driven turbulence and winds in star clusters and galactic disks. Astrophys. J. 760, 155 (2012).

    ADS  Google Scholar 

  78. Rosen, A. L., Lopez, L. A., Krumholz, M. R. & Ramirez-Ruiz, E. Gone with the wind: where is the missing stellar wind energy from massive star clusters? Mon. Not. R. Astron. Soc. 442, 2701–2716 (2014).

    ADS  CAS  Google Scholar 

  79. Chevance, M. et al. A milestone toward understanding PDR properties in the extreme environment of LMC-30 Doradus. Astron. Astrophys. 590, A36 (2016).

    Google Scholar 

  80. Toomre, A. On the gravitational stability of a disk of stars. Astrophys. J. 139, 1217–1238 (1964).

    ADS  Google Scholar 

  81. Hughes, A. et al. A comparative study of giant molecular clouds in M51, M33, and the Large Magellanic Cloud. Astrophys. J. 779, 46 (2013).

    ADS  Google Scholar 

  82. Clark, P. C., Bonnell, I. A., Zinnecker, H. & Bate, M. R. Star formation in unbound giant molecular clouds: the origin of OB associations? Mon. Not. R. Astron. Soc. 359, 809–818 (2005).

    ADS  CAS  Google Scholar 

  83. Padoan, P., Haugbølle, T. & Nordlund, Å. A simple law of star formation. Astrophys. J. Lett. 759, L27 (2012).

    ADS  Google Scholar 

  84. Dale, J. E., Ercolano, B. & Bonnell, I. A. Ionizing feedback from massive stars in massive clusters—III. Disruption of partially unbound clouds. Mon. Not. R. Astron. Soc. 430, 234–246 (2013).

    ADS  CAS  Google Scholar 

  85. Rathborne, J. M. et al. A cluster in the making: ALMA reveals the initial conditions for high-mass cluster formation. Astrophys. J. 802, 125 (2015).

    ADS  Google Scholar 

  86. Scoville, N. Z., Solomon, P. M. & Sanders, D. B. in The Large-Scale Characteristics of the Galaxy (ed. Burton, W. B.) 277–283 (IAU, 1979).

  87. Sanders, D. B., Scoville, N. Z. & Solomon, P. M. Giant molecular clouds in the Galaxy. II—Characteristics of discrete features. Astrophys. J. 289, 373–387 (1985).

    ADS  CAS  Google Scholar 

  88. Hartmann, L., Ballesteros-Paredes, J. & Bergin, E. A. Rapid formation of molecular clouds and stars in the solar neighborhood. Astrophys. J. 562, 852–868 (2001).

    ADS  CAS  Google Scholar 

  89. Engargiola, G., Plambeck, R. L., Rosolowsky, E. & Blitz, L. Giant molecular clouds in M33. I. BIMA All-Disk Survey. Astrophys. J. 149 (Suppl.), 343–363 (2003).

    ADS  CAS  Google Scholar 

  90. Blitz, L. et al. in Protostars and Planets V (eds. Reipurth, B., Jewitt, D. & Keil, K.) 81–96 (Univ. Arizona Press, 2007).

  91. Kawamura, A. et al. The second survey of the molecular clouds in the Large Magellanic Cloud by NANTEN. II. Star formation. Astrophys. J. 184 (Suppl.), 1–17 (2009).

    CAS  Google Scholar 

  92. Murray, N. Star formation efficiencies and lifetimes of giant molecular clouds in the Milky Way. Astrophys. J. 729, 133 (2011).

    ADS  Google Scholar 

  93. Dobbs, C. L. et al. in Protostars and Planets VI (eds. Beuther, H. et al.) 3–26 (Univ. Arizona Press, 2014).

  94. Meidt, S. E. et al. Short GMC lifetimes: an observational estimate with the PdBI Arcsecond Whirlpool Survey (PAWS). Astrophys. J. 806, 72 (2015).

    ADS  Google Scholar 

  95. Kruijssen, J. M. D., Dale, J. E. & Longmore, S. N. The dynamical evolution of molecular clouds near the Galactic Centre—I. Orbital structure and evolutionary timeline. Mon. Not. R. Astron. Soc. 447, 1059–1079 (2015).

    ADS  Google Scholar 

  96. Corbelli, E. et al. From molecules to young stellar clusters: the star formation cycle across the disk of M 33. Astron. Astrophys. 601, A146 (2017).

    Google Scholar 

  97. Barnes, A. T. et al. Star formation rates and efficiencies in the Galactic Centre. Mon. Not. R. Astron. Soc. 469, 2263–2285 (2017).

    ADS  CAS  Google Scholar 

  98. Kreckel, K. et al. A 50 pc scale view of star formation efficiency across NGC 628. Astrophys. J. Lett. 863, L21 (2018).

    ADS  Google Scholar 

  99. Grasha, K. et al. Connecting young star clusters to CO molecular gas in NGC 7793 with ALMA-LEGUS. Mon. Not. R. Astron. Soc. 481, 1016–1027 (2018).

    ADS  Google Scholar 

  100. Efremov, Y. N. & Elmegreen, B. G. Hierarchical star formation from the time-space distribution of star clusters in the Large Magellanic Cloud. Mon. Not. R. Astron. Soc. 299, 588–594 (1998).

    ADS  Google Scholar 

  101. Elmegreen, B. G. & Falgarone, E. A fractal origin for the mass spectrum of interstellar clouds. Astrophys. J. 471, 816 (1996).

    ADS  CAS  Google Scholar 

  102. Hopkins, P. F. An excursion-set model for the structure of giant molecular clouds and the interstellar medium. Mon. Not. R. Astron. Soc. 423, 2016–2036 (2012).

    ADS  CAS  Google Scholar 

  103. Hopkins, P. F. A general theory of turbulent fragmentation. Mon. Not. R. Astron. Soc. 430, 1653–1693 (2013).

    ADS  Google Scholar 

  104. Mac Low, M.-M. & Klessen, R. S. Control of star formation by supersonic turbulence. Rev. Mod. Phys. 76, 125–194 (2004).

    ADS  Google Scholar 

  105. Henshaw, J. D., Longmore, S. N. & Kruijssen, J. M. D. Seeding the Galactic Centre gas stream: gravitational instabilities set the initial conditions for the formation of protocluster clouds. Mon. Not. R. Astron. Soc. 463, L122–L126 (2016).

    ADS  Google Scholar 

  106. Zamora-Avilés, M., Vázquez-Semadeni, E. & Colín, P. An evolutionary model for collapsing molecular clouds and their star formation activity. Astrophys. J. 751, 77 (2012).

    ADS  Google Scholar 

  107. Elmegreen, B. G. On the appearance of thresholds in the dynamical model of star formation. Astrophys. J. 854, 16 (2018).

    ADS  Google Scholar 

  108. Burkhart, B. The star formation rate in the gravoturbulent interstellar medium. Astrophys. J. 863, 118 (2018).

    ADS  Google Scholar 

  109. Vázquez-Semadeni, E., Zamora-Avilés, M., Galván-Madrid, R. & Forbrich, J. Molecular cloud evolution—VI. Measuring cloud ages. Mon. Not. R. Astron. Soc. 479, 3254–3263 (2018).

    ADS  Google Scholar 

  110. Feldmann, R., Gnedin, N. Y. & Kravtsov, A. V. How universal is the relation? Astrophys. J. 732, 115 (2011).

    ADS  Google Scholar 

  111. Semenov, V. A., Kravtsov, A. V. & Gnedin, N. Y. Nonuniversal star formation efficiency in turbulent ISM. Astrophys. J. 826, 200 (2016).

    ADS  Google Scholar 

  112. Semenov, V. A., Kravtsov, A. V. & Gnedin, N. Y. The physical origin of long gas depletion times in galaxies. Astrophys. J. 845, 133 (2017).

    ADS  Google Scholar 

  113. Semenov, V. A., Kravtsov, A. V. & Gnedin, N. Y. How galaxies form stars: the connection between local and global star formation in galaxy simulations. Astrophys. J. 861, 4 (2018).

    ADS  Google Scholar 

  114. Ochsendorf, B. B., Meixner, M., Roman-Duval, J., Rahman, M. & Evans, N. J. II. What sets the massive star formation rates and efficiencies of giant molecular clouds? Astrophys. J. 841, 109 (2017).

    ADS  Google Scholar 

  115. Silk, J. Feedback, disk self-regulation, and galaxy formation. Astrophys. J. 481, 703 (1997).

    ADS  Google Scholar 

  116. Elmegreen, B. G. & Efremov, Y. N. A universal formation mechanism for open and globular clusters in turbulent gas. Astrophys. J. 480, 235–245 (1997).

    ADS  Google Scholar 

  117. Kennicutt, R. C. Jr. Star formation in galaxies along the Hubble sequence. Annu. Rev. Astron. Astrophys. 36, 189–231 (1998).

    ADS  CAS  Google Scholar 

  118. Fujimoto, Y., Tasker, E. J., Wakayama, M. & Habe, A. Do giant molecular clouds care about the galactic structure? Mon. Not. R. Astron. Soc. 439, 936–953 (2014).

    ADS  Google Scholar 

  119. Dobbs, C. L., Pringle, J. E. & Duarte-Cabral, A. The frequency and nature of ‘cloud–cloud collisions’ in galaxies. Mon. Not. R. Astron. Soc. 446, 3608–3620 (2015).

    ADS  CAS  Google Scholar 

  120. Tasker, E. J., Wadsley, J. & Pudritz, R. Star formation in disk galaxies. III. Does stellar feedback result in cloud death? Astrophys. J. 801, 33 (2015).

    Google Scholar 

  121. Meidt, S. E. et al. Gas kinematics on giant molecular cloud scales in M51 with PAWS: cloud stabilization through dynamical pressure. Astrophys. J. 779, 45 (2013).

    ADS  Google Scholar 

  122. Meidt, S. E. et al. A model for the onset of self-gravitation and star formation in molecular gas governed by galactic forces. I. Cloud-scale gas motions. Astrophys. J. 854, 100 (2018).

    ADS  Google Scholar 

  123. Ostriker, E. C., McKee, C. F. & Leroy, A. K. Regulation of star formation rates in multiphase galactic disks: a thermal/dynamical equilibrium model. Astrophys. J. 721, 975–994 (2010).

    ADS  CAS  Google Scholar 

  124. Ostriker, E. C. & Shetty, R. Maximally star-forming galactic disks. I. Starburst regulation via feedback-driven turbulence. Astrophys. J. 731, 41 (2011).

    ADS  Google Scholar 

  125. Kim, C.-G., Kim, W.-T. & Ostriker, E. C. Regulation of star formation rates in multiphase galactic disks: numerical tests of the thermal/dynamical equilibrium model. Astrophys. J. 743, 25 (2011).

    ADS  Google Scholar 

  126. Hopkins, P. F. et al. Galaxies on FIRE (Feedback In Realistic Environments): stellar feedback explains cosmologically inefficient star formation. Mon. Not. R. Astron. Soc. 445, 581–603 (2014).

    ADS  CAS  Google Scholar 

  127. Stinson, G. S. et al. Making galaxies in a cosmological context: the need for early stellar feedback. Mon. Not. R. Astron. Soc. 428, 129–140 (2013).

    ADS  Google Scholar 

  128. Dale, J. E. The modelling of feedback in star formation simulations. New Astron. Rev. 68, 1–33 (2015).

    ADS  Google Scholar 

  129. Gatto, A. et al. Modelling the supernova-driven ISM in different environments. Mon. Not. R. Astron. Soc. 449, 1057–1075 (2015).

    ADS  CAS  Google Scholar 

  130. Gatto, A. et al. The SILCC project—III. Regulation of star formation and outflows by stellar winds and supernovae. Mon. Not. R. Astron. Soc. 466, 1903–1924 (2017).

    ADS  CAS  Google Scholar 

  131. Hu, C.-Y., Naab, T., Glover, S. C. O., Walch, S. & Clark, P. C. Variable interstellar radiation fields in simulated dwarf galaxies: supernovae versus photoelectric heating. Mon. Not. R. Astron. Soc. 471, 2151–2173 (2017).

    ADS  CAS  Google Scholar 

  132. Matzner, C. D. On the role of massive stars in the support and destruction of giant molecular clouds. Astrophys. J. 566, 302–314 (2002).

    ADS  CAS  Google Scholar 

  133. Krumholz, M. R. & Matzner, C. D. The dynamics of radiation-pressure-dominated H ii regions. Astrophys. J. 703, 1352–1362 (2009).

    ADS  CAS  Google Scholar 

  134. Dale, J. E., Ngoumou, J., Ercolano, B. & Bonnell, I. A. Before the first supernova: combined effects of H ii regions and winds on molecular clouds. Mon. Not. R. Astron. Soc. 442, 694–712 (2014).

    ADS  CAS  Google Scholar 

  135. Matzner, C. D. & Jumper, P. H. Star cluster formation with stellar feedback and large-scale inflow. Astrophys. J. 815, 68 (2015).

    ADS  Google Scholar 

  136. Rahner, D., Pellegrini, E. W., Glover, S. C. O. & Klessen, R. S. Winds and radiation in unison: a new semi-analytic feedback model for cloud dissolution. Mon. Not. R. Astron. Soc. 470, 4453–4472 (2017).

    ADS  CAS  Google Scholar 

  137. Kim, J.-G., Kim, W.-T., Ostriker, E. C. & Modeling, U. V. Radiation feedback from massive stars. II. Dispersal of star-forming giant molecular clouds by photoionization and radiation pressure. Astrophys. J. 859, 68 (2018).

    ADS  Google Scholar 

  138. Lopez, L. A. et al. The role of stellar feedback in the dynamics of H ii regions. Astrophys. J. 795, 121 (2014).

    ADS  Google Scholar 

  139. Kennicutt, R. C. Jr et al. Star formation in NGC 5194 (M51a). II. The spatially resolved star formation law. Astrophys. J. 671, 333–348 (2007).

    ADS  CAS  Google Scholar 

  140. Tacconi, L. J. et al. PHIBSS: molecular gas content and scaling relations in z ~ 1–3 massive, main-sequence star-forming galaxies. Astrophys. J. 768, 74 (2013).

    ADS  Google Scholar 

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Acknowledgements

J.M.D.K. and M.C. acknowledge funding from the German Research Foundation (DFG) in the form of an Emmy Noether Research Group grant no. KR4801/1-1. J.M.D.K. acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme via the ERC Starting Grant MUSTANG (grant agreement no. 714907). A.P.S.H. and D.T.H. are fellows of the International Max Planck Research School for Astronomy and Cosmic Physics at the University of Heidelberg (IMPRS-HD). We thank C. Faesi for providing his version of the MPG/ESO 2.2-m Hα map of NGC 300. We thank B. W. Keller and M. R. Krumholz for discussions.

Reviewer information

Nature thanks N. Evans and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Authors and Affiliations

  1. Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Heidelberg, Germany

    J. M. Diederik Kruijssen, Mélanie Chevance, Alexander P. S. Hygate & Daniel T. Haydon

  2. Max-Planck Institut für Astronomie, Heidelberg, Germany

    J. M. Diederik Kruijssen & Alexander P. S. Hygate

  3. Max-Planck Institut für Extraterrestrische Physik, Garching, Germany

    Andreas Schruba, Linda J. Tacconi & Ewine F. van Dishoeck

  4. Astrophysics Research Institute, Liverpool John Moores University, Liverpool, UK

    Steven N. Longmore

  5. Department of Astronomy, University of California Berkeley, Berkeley, CA, USA

    Anna F. McLeod

  6. Department of Physics and Astronomy, Texas Tech University, Lubbock, TX, USA

    Anna F. McLeod

  7. Department of Astronomy, University of Washington, Seattle, WA, USA

    Julianne J. Dalcanton

  8. Leiden Observatory, Leiden University, Leiden, The Netherlands

    Ewine F. van Dishoeck

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  1. J. M. Diederik Kruijssen
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Contributions

J.M.D.K. led the project, carried out the experiment design, developed the analysis method and wrote the text, to which A.S., M.C. and S.N.L. contributed. A.S. performed and reduced the ALMA observations and prepared all observational data for their physical analysis. J.M.D.K. and M.C. carried out the physical analysis of the data, to which A.S., S.N.L., A.P.S.H. and D.T.H. contributed. All authors contributed to aspects of the analysis, the interpretation of the results and the writing of the manuscript.

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Correspondence to J. M. Diederik Kruijssen.

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Extended data figures and tables

Extended Data Fig. 1 Radial profiles of quantities describing the galactic structure of NGC 300.

a–f, The surface densities of molecular gas, atomic gas, total gas and stars (a), the SFR surface density (b), the depletion times of molecular, atomic and total gas (c), the rotation curve (d), the Toomre Q stability parameter (e, where Q = 1 corresponds to equilibrium), and the metallicity (f).

Extended Data Fig. 2 Integrated properties of NGC 300 relative to other star-forming galaxies in the nearby Universe.

a–c, The SFR as a function of stellar mass (a), molecular gas mass (b) and atomic gas mass (c), both for NGC 300 and nearby galaxies from the xCOLDGASS53 and xGASS54 surveys. In b and c, the arrows indicate 3σ and 5σ upper limits of non-detections in xCOLDGASS and xGASS, respectively. The solid lines represent the star-forming galaxy main sequence54 (a), the mean molecular gas depletion time of the xCOLDGASS detections (b), and the mean atomic gas depletion time of the xGASS detections (c), with the 1σ scatter shown in grey.

Extended Data Fig. 3 Radial profiles of the average properties of the GMC population in NGC 300.

a–f, The GMC radius (a), velocity dispersion (b), luminous and virial masses (c), surface density (d), molecular hydrogen number density (e) and virial parameter (f, where αvir = 1 corresponds to virial equilibrium).

Extended Data Fig. 4 NGC 300 seen at different aperture sizes.

This figure illustrates the image processing of this work. The panels show the Hα emission (left) and CO(1–0) emission (right) from NGC 300 convolved with top-hat apertures of diameters increasing from top to bottom from 20 pc to 2,560 pc (see the annotated circles). Each panel also shows the locations of the emission peaks identified in the images at 20-pc resolution (crosses), at which the flux density measurements are made when deriving the CO-to-Hα flux ratio as a function of size scale as in Fig. 1.

Extended Data Fig. 5 PDFs of constrained quantities.

a–f, Normalized probability distributions of the six constrained quantities (solid lines), with best-fitting values (dashed lines) and 1σ uncertainties (dotted lines) indicated in the top-right corner of each panel.

Extended Data Fig. 6 Influence of the GMC life cycle on the decorrelation of molecular gas and young stellar emission.

Shown is the change of the CO-to-Hα flux ratio relative to the galactic average as a function of spatial scale, for apertures placed on CO emission peaks (top branch) and Hα emission peaks (bottom branch). The symbols and 1σ error bars show the CO-to-Hα flux ratios observed across the entire field of view of NGC 300 as in Fig. 1. The evolutionary timeline of the GMC life cycle is constrained by fitting the model indicated by the solid lines. Alternative models with long GMC lifetimes are shown by the dashed and dotted lines (see key). These alternatives are ruled out by the observations.

Extended Data Fig. 7 Distribution of nearest-neighbour distances of identified emission peaks.

The black solid line shows the cumulative distribution of the distances to the nearest neighbours across the combined sample of emission peaks identified in the Hα and CO maps. The median and mean distance are indicated by the vertical dashed and dotted lines, respectively. The vertical grey lines indicate lower and upper limits derived in the Methods section, the first of which is implied by the measured region separation length. The location of the median and mean nearest-neighbour distances between these limits is consistent with the measured separation lengths.

Extended Data Fig. 8 Schematic illustration of cloud-scale evolutionary cycling in the Σ − ΣSFR plane.

The symbols show the observed relation between the total gas surface density (Σ, where the high-redshift sample is assumed to be fully molecular) and the SFR surface density (ΣSFR) for galaxies in the local Universe and at high redshift (see key)68,139,140. For NGC 300, the error bars show the 1σ uncertainties. Dotted lines represent constant gas depletion times as indicated by the labels. The results of this work show that GMCs and star-forming regions move through this diagram. As a function of time, they increase their gas density, increase their SFR, expel gas through feedback and eventually fade by stellar evolution, as schematically illustrated by the red arrows.

Supplementary information

Video 1

Spatial de-correlation between molecular gas and ionised emission from young stars towards small spatial scales in the nearby galaxy NGC300. The top panels show the ionised emission (Hα, left) and molecular gas (CO, right) maps of NGC300, with crosses indicating the emission peaks in each of the maps. The bottom-left panel shows the gas depletion time (the ratio between the top maps). The colour of this map changes from white on large spatial scales (strong CO-Hα correlation) to bright red and blue on small spatial scales (strong CO-Hα anti-correlation). The bottom-right panel quantifies this behaviour by showing how the change of the CO-to-Hα flux ratio relative to the galactic average increases towards small (<150 pc) aperture sizes. The circle and vertical line indicate the spatial scale (‘aperture size’) at which the galaxy is observed.

Video 2

Relation between the change of the CO-to-Hα flux ratio relative to the galactic average and the physical quantities defining the cloud life cycle. The young stellar lifetime (tHα), the cloud lifetime (tCO), the feedback timescale (tfb), and the region separation length (λ) are initially set equal to values measured for NGC300, but are systematically varied to demonstrate their effect on the CO-to-Hα ratio. The top panels show mock ‘CO’ and ‘Hα’ maps from a numerical simulation of a disc galaxy, with an inclination and position angle mimicking NGC300. The images are generated using stellar particles in specific age intervals, yielding emission peak lifetimes as indicated in the timeline and annotation at the top of the video. The bottom-left panel shows the ‘gas depletion time’, i.e. the ratio between the top two maps. The bottom-right panel shows the change of this ratio relative to the galactic average, with λ indicated along the bottom axis. This diagram provides a non-degenerate measurement of the three measured quantities (tCO, tfb, and λ), because tHα is known (see Methods).

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Kruijssen, J.M.D., Schruba, A., Chevance, M. et al. Fast and inefficient star formation due to short-lived molecular clouds and rapid feedback. Nature 569, 519–522 (2019). https://doi.org/10.1038/s41586-019-1194-3

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