[C II] 158 μm emission as an indicator of galaxy star formation rate

Abstract

Copyright and License

Acknowledgement

We thank the anonymous referee for useful comments which have helped improved the quality of this manuscript. LL acknowledges financial support from the Swiss National Science Foundation (hereafter SNSF) (grant no. P2ZHP2_199729) and the University of Toronto Faculty of Arts and Science. RF acknowledges financial support from the SNSF (grant no. PP00P2_194814, 200021_188552). NM was supported by the Natural Sciences and Engineering Research Council of Canada (grant no. RGPIN-2023-04901). DN acknowledges funding from the NSF via AST-1909153. DAA acknowledges support by NSF grants AST-2009687 and AST-2108944, CXO grant TM2-23006X, and Simons Foundation award CCA-1018464. LB acknowledge financial support from the SNSF (grant no .PP00P2_194814). CAFG was supported by NSF through grants AST-1715216, AST-2108230, and CAREER award AST-1652522; by NASA through grants 17-ATP17-0067 and 21-ATP21-0036; by STScI through grants HST-AR-16124.001-A and HST-GO-16730.016-A; by CXO through grant TM2-23005X; and by the Research Corporation for Science Advancement (RCSA) through a Cottrell Scholar Award. DTC is supported by a CITA/Dunlap Institute postdoctoral fellowship. DTC also acknowledges support through the Vincent and Beatrice Tremaine Postdoctoral Fellowship at CITA during the preparation and review of this work. JYHC acknowledges support from a CITA postdoctoral fellowship. DK were supported by NSF grant AST-1715101 and the Cottrell Scholar Award from the RCSA. Support for PFH was provided by NSF research grants 1911233, 20009234, 2108318, NSF CAREER grant 1455342, NASA grants 80NSSC18K0562 andHST-AR-15800. This work was performed in part at the Aspen Center for Physics, which is supported by National Science Foundation grant PHY-2210452. The Dunlap Institute is funded through an endowment established by the David Dunlap family and the University of Toronto. The Flatiron Institute is supported by the Simons Foundation.

We acknowledge PRACE for awarding us access to MareNostrum at the Barcelona Supercomputing Center (BSC), Spain. This research was partly carried out via the Frontera computing project at the Texas Advanced Computing Center. Frontera is made possible by National Science Foundation award OAC-1818253. Computations were performed on the Niagara supercomputer at the SciNet HPC Consortium. SciNet is funded by Innovation, Science and Economic Development Canada; the Digital Research Alliance of Canada; the Ontario Research Fund: Research Excellence; and the University of Toronto. This work was supported in part by a grant from the Swiss National Supercomputing Centre (CSCS) under project IDs s697 and s698. We acknowledge access to Piz Daint at the Swiss National Supercomputing Centre, Switzerland under the University of Zurich’s share with the project ID uzh18. This work made use of infrastructure services provided by S3IT (www.s3it.uzh.ch), the Service and Support for Science IT team at the University of Zurich.

The authors would also like to acknowledge the use of AI language model ChatGPT (GPT-3.5, https://chat.openai.com/) for assistance in refining the writing and language of this manuscript.