Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published August 2022 | Published + Accepted Version
Journal Article Open

NIHAO – XXVII. Crossing the green valley

Abstract

The transition of high-mass galaxies from being blue and star-forming to being red and dead is a crucial step in galaxy evolution, yet not fully understood. In this work, we use the NIHAO (Numerical Investigation of a Hundred Astrophysical Objects) suite of galaxy simulations to investigate the relation between the transition time through the green valley and other galaxy properties. The typical green valley crossing time of our galaxies is approximately 400 Myr, somewhat shorter than observational estimates. The crossing of the green valley is triggered by the onset of active galactic nucleus (AGN) feedback and the subsequent shutdown of star formation. Interestingly, the time spent in the green valley is not related to any other galaxy properties, such as stellar age or metallicity, or the time at which the star formation quenching takes place. The crossing time is set by two main contributions: the ageing of the current stellar population and the residual star formation in the green valley. These effects are of comparable magnitude, while major and minor mergers have a negligible contribution. Most interestingly, we find the time that a galaxy spends to travel through the green valley is twice the e-folding time of the star formation quenching. This result is stable against galaxy properties and the exact numerical implementation of AGN feedback in the simulation. Assuming a typical crossing time of about 1 Gyr inferred from observations, our results imply that any mechanism or process aiming to quench star formation must do it on a typical time-scale of 500 Myr.

Additional Information

© 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model). Accepted 2022 April 25. Received 2022 April 22; in original form 2022 March 9. The authors gratefully acknowledge the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for funding this project by providing computing time on the GCS Supercomputer SuperMUC at the Leibniz Supercomputing Centre (http://www.lrz.de). A part of this research was carried out on the High Performance Computing resources at New York University Abu Dhabi. We used the software package PYNBODY (Pontzen et al. 2013) for our analyses. DATA AVAILABILITY. The data underlying this paper will be shared on reasonable request to the corresponding author.

Attached Files

Published - stac1155.pdf

Accepted Version - 2204.11579.pdf

Files

stac1155.pdf
Files (11.8 MB)
Name Size Download all
md5:28de1e8ec9c457fd9fd5be8a44fba9de
1.8 MB Preview Download
md5:c60f183926870abaa8b08c0248ce9660
10.0 MB Preview Download

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023