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What Drives Galaxies from the Main Sequence to the Green Valley?

Published online by Cambridge University Press:  09 June 2023

Lihwai Lin*
Affiliation:
Institute of Astronomy & Astrophysics, Academia Sinica, Taipei 10617, Taiwan
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Abstract

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Green valley galaxies (by selection) exhibit lower specific star formation rates and are thought to be in the transition from the active star-forming phase to the quiescent state. Physical mechanisms responsible for the depleted star formation in green valley galaxies, however, are still under debate. Using the ALMA-MaNGA Quenching and STar formation (ALMaQUEST) CO observations, we study the so-called ‘resolved star formation scaling relations’, which describe relationships among surface densities of star formation rate, stellar mass, and molecular gas mass. By comparing the kpc-scale scaling relations between the main sequence and green valley galaxies, we are able to quantify if the deficit of star formation in green valley galaxies is driven by depleted molecular gas or inefficient star formation. And finally, we present our recent ALMA dense gas (HCN and HCO+) observations for a set of selected ALMaQUEST galaxies to discuss whether the green valley galaxies lack dense molecular gas or not.

Type
Contributed Paper
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of International Astronomical Union

References

Bolatto, A. D., Wong, T., Utomo, D., et al. 2017, ApJ, 846, 159 10.3847/1538-4357/aa86aaCrossRefGoogle Scholar
Brownson, S., Belfiore, F., Maiolino, R., et al. 2020, MNRAS, 498, L66 10.1093/mnrasl/slaa128CrossRefGoogle Scholar
Daddi, E., Dickinson, M., Morrison, G., et al. 2007, ApJ, 670, 156 10.1086/521818CrossRefGoogle Scholar
Ellison, S. L., Lin, L., Thorp, M. D., et al. 2021, MNRAS, 501, 4777 10.1093/mnras/staa3822CrossRefGoogle Scholar
Kennicutt, R. C., Jr. 1998, ApJ, 498, 54110.1086/305588CrossRefGoogle Scholar
Leroy, A. K., Schinnerer, E., Hughes, A., et al. 2021, ApJS, 257, 43 Google Scholar
Lin, L., Dickinson, M., Jian, H.-Y., et al. 2012, ApJ, 756, 71 10.1088/0004-637X/756/1/71CrossRefGoogle Scholar
Lin, L., Belfiore, F., Pan, H.-A., et al. 2017, ApJ, 851, 18 10.3847/1538-4357/aa96aeCrossRefGoogle Scholar
Lin, L., Pan, H.-A., Ellison, S. L., et al. 2019, ApJL, 884, L33 10.3847/2041-8213/ab4815CrossRefGoogle Scholar
Lin, L., Ellison, S. L., Pan, H.-A., et al. 2020, ApJ, 903, 145 10.3847/1538-4357/abba3aCrossRefGoogle Scholar
Lin, L., Ellison, S. L., Pan, H.-A., et al. 2022, ApJ, 926, 175 10.3847/1538-4357/ac4cccCrossRefGoogle Scholar
Morselli, L., Rodighiero, G., Enia, A., et al. 2020, MNRAS, 496, 4606 10.1093/mnras/staa1811CrossRefGoogle Scholar
Noeske, K. G., Faber, S. M., Weiner, B. J., et al. 2007, ApJ, 660, L47 10.1086/517927CrossRefGoogle Scholar
Pessa, I., Schinnerer, E., Belfiore, F., et al. 2021, A&A, 650, A134 10.1051/0004-6361/202140733CrossRefGoogle Scholar
Sánchez, S. F., Barrera-Ballesteros, J. K., Colombo, D., et al. 2021, MNRAS, 503, 1615 10.1093/mnras/stab442CrossRefGoogle Scholar
Schmidt, M. 1959, ApJ, 129, 243 10.1086/146614CrossRefGoogle Scholar
Sorai, K., Kuno, N., Muraoka, K., et al. 2019, PASJ, 71, S14.Google Scholar
Speagle, J. S., Steinhardt, C. L., Capak, P. L., & Silverman, J. D. 2014, ApJS, 214, 15 10.1088/0067-0049/214/2/15CrossRefGoogle Scholar
Whitaker, K. E., van Dokkum, P. G., Brammer, G., et al. 2012, ApJ, 754, L29 10.1088/2041-8205/754/2/L29CrossRefGoogle Scholar