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ABSTRACT The high-redshift galaxy UV luminosity function (UVLF) has become essential for understanding the formation and evolution of the first galaxies. Yet, UVLFs only measure galaxy abundances, giving rise to a degeneracy between the mean galaxy luminosity and its stochasticity. Here, we show that upcoming clustering measurements with the JWST, as well as with Roman, will be able to break this degeneracy, even at redshifts z ≳ 10. First, we demonstrate that current Subaru Hyper Suprime-Cam (HSC) measurements of the galaxy bias at z ∼ 4–6 point to a relatively tight halo-galaxy connection, with low stochasticity. Then, we show that the larger UVLFs observed by JWST at z ≳ 10 can be explained with either a boosted average UV emission or an enhanced stochasticity. These two models, however, predict different galaxy biases, which are potentially distinguishable in JWST and Roman surveys. Galaxy-clustering measurements, therefore, will provide crucial insights into the connection between the first galaxies and their dark-matter haloes, and identify the root cause of the enhanced abundance of z ≳ 10 galaxies revealed with JWST during its first year of operations.
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Galaxy bias in the era of LSST: perturbative bias expansions
Upcoming imaging surveys will allow for high signal-to-noise measurements of galaxy clustering at small scales. In this work, we present the results of the Rubin Observatory Legacy Survey of Space and Time (LSST) bias challenge, the goal of which is to compare the performance of different nonlinear galaxy bias models in the context of LSST Year 10 (Y10) data. Specifically, we compare two perturbative approaches, Lagrangian perturbation theory (LPT) and Eulerian perturbation theory (EPT) to two variants of Hybrid Effective Field Theory (HEFT), with our fiducial implementation of these models including terms up to second order in the bias expansion as well as nonlocal bias and deviations from Poissonian stochasticity. We consider a variety of different simulated galaxy samples and test the performance of the bias models in a tomographic joint analysis of LSST-Y10-like galaxy clustering, galaxy-galaxy-lensing and cosmic shear. We find both HEFT methods as well as LPT and EPT combined with non-perturbative predictions for the matter power spectrum to yield unbiased constraints on cosmological parameters up to at least a maximal scale ofkmax = 0.4 Mpc-1for all samples considered, even in the presence of assembly bias. While we find that we can reduce the complexity of the bias model for HEFT without compromising fit accuracy, this is not generally the case for the perturbative models. We find significant detections of non-Poissonian stochasticity in all cases considered, and our analysis shows evidence that small-scale galaxy clustering predominantly improves constraints on galaxy bias rather than cosmological parameters. These results therefore suggest that the systematic uncertainties associated with current nonlinear bias models are likely to be subdominant compared to other sources of error for tomographic analyses of upcoming photometric surveys, which bodes well for future galaxy clustering analyses using these high signal-to-noise data.
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- Award ID(s):
- 2206563
- PAR ID:
- 10541494
- Publisher / Repository:
- Journal of Cosmology and Astroparticle Physics
- Date Published:
- Journal Name:
- Journal of Cosmology and Astroparticle Physics
- Volume:
- 2024
- Issue:
- 02
- ISSN:
- 1475-7516
- Page Range / eLocation ID:
- 015
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1088/1475-7516/2024/02/015
