The bias of dark matter tracers: assessing the accuracy of mapping techniques

Pellejero-Ibáñez, Marcos; Balaguera-Antolínez, A.; Kitaura, Francisco-Shu; Angulo, Raúl E.; Yepes, Gustavo; Chuang, Chia-Hsun; Reyes-Peraza, Guillermo; Autefage, Mathieu; Vakili, Mohammadjavad; Zhao, Cheng

doi:10.1093/mnras/staa270

Cited by 20 publications

(3 citation statements)

References 60 publications

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“…Strong efforts are currently being done on this direction (see e.g. Balaguera-Antolínez et al 2019a, Balaguera-Antolínez et al 2019b, Pellejero-Ibañez et al 2020a…”

Section: Stellar Mass Selected Galaxies Resultsmentioning

confidence: 99%

Modelling galaxy clustering in redshift space with a Lagrangian bias formalism and $N$-body simulations

Pellejero-Ibanez,

Stuecker,

Angulo

et al. 2021

Preprint

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Improving the theoretical description of galaxy clustering on small scales is an important challenge in cosmology, as it can considerably increase the scientific return of forthcoming galaxy surveys -e.g. tightening the bounds on neutrino masses and deviations from general relativity. In this paper we propose and test a new model for the clustering of galaxies that is able to accurately describe redshift-space distortions even down to small scales. This model corresponds to a second-order perturbative Lagrangian bias expansion which is advected to Eulerian space employing a displacement field extracted from 𝑁-body simulations. Eulerian coordinates are then transformed into redshift space by directly employing simulated velocity fields augmented with nuisance parameters capturing various possible satellite fractions and intra-halo small-scale velocities. We quantify the accuracy of our approach against samples of physically-motivated mock galaxies selected according to either Stellar Mass (SM) or Star Formation Rate (SFR) at multiple abundances and at 𝑧 = 0 and 1. We find our model describes the monopole, quadrupole and hexadecapole of the galaxy-power spectra down to scales of 𝑘 ≈ 0.6[ℎ/Mpc] within the accuracy of our simulations. This approach could pave the way to significantly increase the amount of cosmological information to be extracted from future galaxy surveys.

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“…Strong efforts are currently being done on this direction (see e.g. Balaguera-Antolínez et al 2019a, Balaguera-Antolínez et al 2019b, Pellejero-Ibañez et al 2020a…”

Section: Stellar Mass Selected Galaxies Resultsmentioning

confidence: 99%

Modelling galaxy clustering in redshift space with a Lagrangian bias formalism and $N$-body simulations

Pellejero-Ibanez,

Stuecker,

Angulo

et al. 2021

Preprint

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“…Moreover, the resolutions of the density fields are low (∼ 5h −1 Mpc for eBOSS EZmocks and ∼ 2.5h −1 Mpc for BOSS Patchy mocks), meaning that below these scales the tracers are positioned following a cloud-in-cell distribution. These and other limitations entail catalogues that although good enough for estimating the covariance matrix, do not truthfully reproduce all ingredients present in the data (see [101,107,134]). One consequence is that the BAO signal in these mocks is weaker than in data [66,68].…”

Section: B the Impact Of Non-linear Clusteringmentioning

confidence: 99%

Primordial feature constraints from BOSS + eBOSS

Thiago

Beutler

Peacock

2023

J. Cosmol. Astropart. Phys.

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Understanding the universe in its pristine epoch is crucial in order to obtain a concise comprehension of the late-time universe. Although current data in cosmology are compatible with Gaussian primordial perturbations whose power spectrum follows a nearly scale-invariant power law, this need not be the case when a fundamental theoretical construction is assumed. These extended models lead to sharp features in the primordial power spectrum, breaking its scale invariance. In this work, we obtain combined constraints on four primordial feature models by using the final data release of the BOSS galaxies and eBOSS quasars. By pushing towards the fundamental mode of these surveys and using the larger eBOSS volume, we were able to extend the feature parameter space (i.e. the feature frequency ω) by a factor of four compared to previous analyses using BOSS. While we did not detect any significant features, previous work showed that next-generation galaxy surveys such as DESI will improve the sensitivity to features by a factor of 7, and will also extend the parameter space by a factor of 2.5.

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“…BAM has been shown to be able to generate ensembles of mock catalogs with an accuracy of 1 − 10% in the two-and three-point statistics of dark matter halos (e.g. Pellejero-Ibañez et al 2020) and currently aims at generating the realistic set of galaxy mock catalogs by including intrinsic properties of tracers such as halo masses, concentrations, spins (Balaguera-Antolínez & Kitaura, in preparation).…”

Section: Bammentioning

confidence: 99%

The bias from hydrodynamic simulations: mapping baryon physics onto dark matter fields

Sinigaglia,

Kitaura,

Balaguera-Antolínez

et al. 2020

Preprint

Self Cite

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This paper investigates the hierarchy of baryon physics assembly bias relations obtained from stateof-the-art hydrodynamic simulations with respect to the underlying cosmic web spanned by the dark matter field. Using the Bias Assignment Method (BAM) we find that non-local bias plays a central role. We classify the cosmic web based on the invariants of the curvature tensor defined not only by the gravitational potential, but especially by the overdensity, as small scale clustering becomes important in this context. First, the gas density bias relation can be directly mapped onto the dark matter density field to high precision exploiting the strong correlation between them. In a second step, the neutral hydrogen is mapped based on the dark matter and the gas density fields. Finally, the temperature is mapped based on the previous quantities. This permits us to statistically reconstruct the baryon properties within the same simulated volume finding percent-precision in the two-point statistics and compatible results in the three-point statistics, in general within 1-σ, with respect to the reference simulation (with 5 to 6 orders of magnitude less computing time). This paves the path to establish the best set-up for the construction of mocks probing the intergalactic medium for the generation of such key ingredients in the statistical analysis of large forthcoming missions such as DESI, Euclid, J-PAS and WEAVE.

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The bias of dark matter tracers: assessing the accuracy of mapping techniques

Cited by 20 publications

References 60 publications

Modelling galaxy clustering in redshift space with a Lagrangian bias formalism and $N$-body simulations

Modelling galaxy clustering in redshift space with a Lagrangian bias formalism and $N$-body simulations

Primordial feature constraints from BOSS + eBOSS

The bias from hydrodynamic simulations: mapping baryon physics onto dark matter fields

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