A New Measure of Assembly Bias Using the Environment Dependence of the Luminosity Function
Assembly bias is the variation in the clustering of dark matter halos and galaxies that arises from correlations between the halo assembly history and the large-scale environment at fixed halo mass. In this work, we use the cosmological magnetohydrodynamical simulation TNG300 to investigate how asse...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | The Astrophysical Journal |
| Subjects: | |
| Online Access: | https://doi.org/10.3847/1538-4357/ade98b |
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| Summary: | Assembly bias is the variation in the clustering of dark matter halos and galaxies that arises from correlations between the halo assembly history and the large-scale environment at fixed halo mass. In this work, we use the cosmological magnetohydrodynamical simulation TNG300 to investigate how assembly bias affects the environment-dependent galaxy luminosity function (LF). We measure the LFs in bins of large-scale environment for the original simulated galaxy sample and for a shuffled sample, where the galaxies are randomly reassigned among halos of similar mass to remove assembly bias. By comparing them, we find distinct signatures, showing variations in the number of galaxies at the ∼10% level across all luminosities. Assembly bias increases the tendency of galaxies to reside in denser environments and further dilutes underdense regions, beyond the trends governed by halo mass. When separating by color, we see that assembly bias has a much bigger effect on red galaxies fainter than ${M}_{r}-5\,{\mathrm{log}}\,h=-18.5$ , which accounts for a ∼20% increase in the number of galaxies in the densest environment and a remarkable 50% decrease in the least dense regions. The ratio of these measurements for the densest and least dense regions provides a significant assembly bias signal for the faint red galaxies, larger than a factor of 2. Overall, our results provide a novel sensitive measure of assembly bias, offering valuable insight for modeling the effect and a potential new route to detect it in observations. |
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| ISSN: | 1538-4357 |