Large-scale galaxy bias

Desjacques, Vincent; Jeong, Donghui; Schmidt, Fabian

doi:10.1016/j.physrep.2017.12.002

Cited by 732 publications

(1,108 citation statements)

References 649 publications

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“…The cross-correlation measurements were not used in the combined probes analysis and so the robustness tests were not performed on these measurements. We present these results to demonstrate that there is a clustering signal in adjacent redshift bins (2,1), (3,2), (4,3), and (5,4) and not as a robustness test; hence, we do not include a goodness-of-fit for this measurement. The amplitude of this signal is determined by the overlap in the nðzÞ between redshift bins (see Fig.…”

Section: Appendix B: Cross-correlationsmentioning

confidence: 99%

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Dark Energy Survey year 1 results: Galaxy clustering for combined probes

Elvin-Poole¹,

Crocce²,

Ross³

et al. 2018

Phys. Rev. D

155

235

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We measure the clustering of DES year 1 galaxies that are intended to be combined with weak lensing samples in order to produce precise cosmological constraints from the joint analysis of large-scale structure and lensing correlations. Two-point correlation functions are measured for a sample of 6.6 × 10 5 luminous red galaxies selected using the REDMAGIC algorithm over an area of 1321 square degrees, in the redshift range 0.15 < z < 0.9, split into five tomographic redshift bins. The sample has a mean redshift uncertainty of σ z =ð1 þ zÞ ¼ 0.017. We quantify and correct spurious correlations induced by spatially variable survey properties, testing their impact on the clustering measurements and covariance. We demonstrate the sample's robustness by testing for stellar contamination, for potential biases that could arise from the systematic correction, and for the consistency between the two-point auto-and cross-correlation functions. We show that the corrections we apply have a significant impact on the resultant measurement of cosmological parameters, but that the results are robust against arbitrary choices in the correction method. We find the linear galaxy bias in each redshift bin in a fiducial cosmology to be bðσ 8 =0.81Þj z¼0.24 ¼ 1.40 AE 0.07, bðσ 8 =0.81Þj z¼0.38 ¼ 1.60 AE 0.05, bðσ 8 =0.81Þj z¼0.53 ¼ 1.60 AE 0.04 for galaxies with luminosities L=L Ã > 0.5, bðσ 8 =0.81Þj z¼0.68 ¼ 1.93 AE 0.04 for L=L Ã > 1 and bðσ 8 =0.81Þj z¼0.83 ¼ 1.98 AE 0.07 for L=L Ã > 1.5, broadly consistent with expectations for the redshift and luminosity dependence of the bias of red galaxies. We show these measurements to be consistent with the linear bias obtained from tangential shear measurements.

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Section: Appendix B: Cross-correlationsmentioning

confidence: 99%

“…Thus, in cosmological studies the galaxy bias is often treated as a nuisance parameter-one that is degenerate with the amplitude of the clustering of matter. See, e.g., [2] and references therein.…”

Section: Introductionmentioning

confidence: 99%

Dark Energy Survey year 1 results: Galaxy clustering for combined probes

Elvin-Poole¹,

Crocce²,

Ross³

et al. 2018

Phys. Rev. D

155

235

View full text Add to dashboard Cite

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“…Through the observational contamination of other galaxy types as well as possible nonlinear systematics, the use of the LA model may result in a biased parameter estimation. Similar to the galaxy bias (Desjacques et al 2018), the improved theoretical description is indispensable (see, e.g., Blazek et al 2019;Vlah et al 2019, for closely related works).…”

Section: Forecasting Cosmologicalmentioning

confidence: 99%

Improving Geometric and Dynamical Constraints on Cosmology with Intrinsic Alignments of Galaxies

Taruya

Okumura

2020

ApJL

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We show that the spatial correlation of the intrinsic alignments (IAs) of galaxies, measured in galaxy redshift surveys, offers a precision route to improve the geometrical and dynamical constraints on cosmology. The IA has been treated as a contaminant against cosmological probes such as weak gravitational lensing experiments. However, the large-scale correlation of IAs is expected to follow the coherent large-scale matter inhomogeneities. Here, making use of its anisotropic nature, we show that the large-scale IA correlations help to improve the measurements of the geometric distances and growth of structure. In combination with the conventional galaxy clustering statistics, we find that constraints on equation-of-state parameter for dark energy and Hubble parameter can be tighter than those from the clustering statistics alone by a factor of more than 1.5.

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“…Galaxies are therefore biased tracers of the density field, sampling only the over-dense regions (e.g. Kaiser 1984; Bardeen et al 1986; see Desjacques et al 2018 for a recent review). The bias, b, of a population of galaxies is defined according to,…”

Section: Introductionmentioning

confidence: 99%

Linear bias forecasts for emission line cosmological surveys

Merson

Smith

Benson

et al. 2019

Monthly Notices of the Royal Astronomical Society

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We forecast the linear bias for Hα-emitting galaxies at high redshift. To simulate a Euclid-like and a WFIRST-like survey, we place galaxies into a large-volume dark matter halo lightcone by sampling a library of luminosity-dependent halo occupation distributions (HODs), which is constructed using a physically motivated galaxy formation model. We calibrate the dust attenuation in the lightcones such that they are able to reproduce the Hα luminosity function or the Hα cumulative number counts. The angle-averaged galaxy correlation function is computed for each survey in redshift slices of width ∆z = 0.2. In each redshift bin the linear bias can be fitted with a single, scale-independent value that increases with increasing redshift. Fitting for the evolution of linear bias with redshift, we find that our Euclid-like and WFIRST-like surveys are both consistent within error with the relation b(z) = 0.7z +0.7. Our bias forecasts are consistent with bias measurements from the HiZELS survey. We find that the Euclid-like and WFIRST-like surveys yield linear biases that are broadly consistent within error, most likely due to the HOD for the WFIRST-like survey having a steeper power-law slope towards larger halo masses.

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Large-scale galaxy bias

Cited by 732 publications

References 649 publications

Dark Energy Survey year 1 results: Galaxy clustering for combined probes

Dark Energy Survey year 1 results: Galaxy clustering for combined probes

Improving Geometric and Dynamical Constraints on Cosmology with Intrinsic Alignments of Galaxies

Linear bias forecasts for emission line cosmological surveys

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