Approximate methods to populate dark-matter haloes with galaxies are of great utility to galaxy surveys. However, the limitations of simple halo occupation models (HODs) preclude a full use of small-scale galaxy clustering data and call for more sophisticated models. We study two galaxy populations, luminous red galaxies (LRGs) and star-forming emission-line galaxies (ELGs), at two epochs, z = 1 and z = 0, in the large-volume, high-resolution hydrodynamical simulation of the MillenniumTNG project. In a partner study we concentrated on the small-scale, one-halo regime down to r ∼ 0.1 h−1 Mpc, while here we focus on modelling galaxy assembly bias in the two-halo regime, r ≳ 1 h−1 Mpc. Interestingly, the ELG signal exhibits scale dependence out to relatively large scales (r ∼ 20 h−1 Mpc), implying that the linear bias approximation for this tracer is invalid on these scales, contrary to common assumptions. The 10–15 per cent discrepancy is only reconciled when we augment our halo occupation model with a dependence on extrinsic halo properties (‘shear’ being the best-performing one) rather than intrinsic ones (e.g. concentration, peak mass). We argue that this fact constitutes evidence for two-halo galaxy conformity. Including tertiary assembly bias (i.e. a property beyond mass and ‘shear’) is not an essential requirement for reconciling the galaxy assembly bias signal of LRGs, but the combination of external and internal properties is beneficial for recovering ELG the clustering. We find that centrals in low-mass haloes dominate the assembly bias signal of both populations. Finally, we explore the predictions of our model for higher order statistics such as nearest neighbour counts. The latter supplies additional information about galaxy assembly bias and can be used to break degeneracies between halo model parameters.
- Award ID(s):
- 1814208
- PAR ID:
- 10163802
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 885
- Issue:
- 2
- ISSN:
- 1538-4357
- Page Range / eLocation ID:
- 153
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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ABSTRACT We build a deep learning framework that connects the local formation process of dark matter haloes to the halo bias. We train a convolutional neural network (CNN) to predict the final mass and concentration of dark matter haloes from the initial conditions. The CNN is then used as a surrogate model to derive the response of the haloes’ mass and concentration to long-wavelength perturbations in the initial conditions, and consequently the halo bias parameters following the ‘response bias’ definition. The CNN correctly predicts how the local properties of dark matter haloes respond to changes in the large-scale environment, despite no explicit knowledge of halo bias being provided during training. We show that the CNN recovers the known trends for the linear and second-order density bias parameters b1 and b2, as well as for the local primordial non-Gaussianity linear bias parameter bϕ. The expected secondary assembly bias dependence on halo concentration is also recovered by the CNN: at fixed mass, halo concentration has only a mild impact on b1, but a strong impact on bϕ. Our framework opens a new window for discovering which physical aspects of the halo’s Lagrangian patch determine assembly bias, which in turn can inform physical models of halo formation and bias.
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Abstract Stellar kinematics and metallicity are key to exploring formation scenarios for galactic disks and halos. In this work, we characterized the relationship between kinematics and photometric metallicity along the line of sight to M31's disk. We combined optical Hubble Space Telescope/Advanced Camera for Surveys photometry, from the Panchromatic Hubble Andromeda Treasury survey, with Keck/DEIMOS spectra, from the Spectroscopic and Photometric Landscape of Andromeda’s Stellar Halo survey. The resulting sample of 3512 individual red giant branch stars spans 4–19 projected kpc, making it a useful probe of both the disk and inner halo. We separated these stars into disk and halo populations, by modeling the line-of-sight velocity distributions as a function of position across the disk region, where ∼73% stars have a high likelihood of belonging to the disk and ∼14% to the halo. Although stellar halos are typically thought to be metal-poor, the kinematically identified halo contains a significant population of stars (∼29%) with disk-like metallicity ([Fe/H]phot∼ −0.10). This metal-rich halo population lags the gaseous disk to a similar extent as the rest of the halo, indicating that it does not correspond to a canonical thick disk. Its properties are inconsistent with those of tidal debris originating from the Giant Stellar Stream merger event. Moreover, the halo is chemically distinct from the phase-mixed component previously identified along the minor axis (i.e., away from the disk), implying contributions from different formation channels. These metal-rich halo stars provide direct chemodynamical evidence in favor of the previously suggested “kicked-up” disk population in M31's inner stellar halo.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3847/1538-4357/ab46ab
