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Published January 10, 2020 | Submitted + Published
Journal Article Open

Star-forming Clumps in Local Luminous Infrared Galaxies

Abstract

We present HST narrowband near-infrared imaging of Paα and Paβ emission of 48 local luminous infrared galaxies (LIRGs) from the Great Observatories All-Sky LIRG Survey. These data allow us to measure the properties of 810 spatially resolved star-forming regions (59 nuclei and 751 extranuclear clumps) and directly compare their properties to those found in both local and high-redshift star-forming galaxies. We find that in LIRGs the star-forming clumps have radii ranging from ~90 to 900 pc and star formation rates (SFRs) of ~1 × 10⁻³ to 10 M⊙ yr⁻¹, with median values for extranuclear clumps of 170 pc and 0.03 M⊙ yr⁻¹. The detected star-forming clumps are young, with a median stellar age of 8.7 Myr, and have a median stellar mass of 5 × 10⁵ M ⊙. The SFRs span the range of those found in normal local star-forming galaxies to those found in high-redshift star-forming galaxies at z = 1–3. The luminosity function of the LIRG clumps has a flatter slope than found in lower-luminosity, star-forming galaxies, indicating a relative excess of luminous star-forming clumps. In order to predict the possible range of star-forming histories and gas fractions, we compare the star-forming clumps to those measured in the MassiveFIRE high-resolution cosmological simulation. The star-forming clumps in MassiveFIRE cover the same range of SFRs and sizes found in the local LIRGs and have total gas fractions that extend from 10% to 90%. If local LIRGs are similar to these simulated galaxies, we expect that future observations with ALMA will find a large range of gas fractions, and corresponding star formation efficiencies, among the star-forming clumps in LIRGs.

Additional Information

© 2020 The American Astronomical Society. Received 2019 March 12; revised 2019 October 25; accepted 2019 November 18; published 2020 January 13. K.L.L. would like to thank the anonymous referee for their useful comments, as well as P. Hopkins, J. Lee, and Y. Guo for insightful discussions that all greatly improved this paper. K.L.L. was supported by NASA through grants HST-GO-13690.002-A and HST-GO-15241.002-A from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. T.D-S. acknowledges support from ALMA-CONICYT project 31130005 and FONDECYT regular project 1151239. G.C.P. acknowledges support from the University of Florida. S.T.L. was supported by the NRAO Grote Reber Dissertation Fellowship. A.S.E. was supported by NSF grant AST 1109475 and by NASA through grants HST-GO1-0592.01-A, HST-GO1-1196.01-A, and HST-GO1-3364 from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. V.U. acknowledges funding support from the University of California Chancellors Postdoctoral Fellowship and NSF grant AST-1412693. Support for AMM is provided by NASA through Hubble Fellowship grant HST-HF2-51377 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555. This research has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. This research also used astrodendro, a Python package to compute dendrograms of Astronomical data (http://www.dendrograms.org/).

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Published - Larson_2020_ApJ_888_92.pdf

Submitted - 1911.09367.pdf

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Additional details

Created:
August 22, 2023
Modified:
October 18, 2023