Clustering properties of<i>g</i>-selected galaxies at<i>z</i>∼ 0.8

Favole, Ginevra; Comparat, Johan; Prada, Francisco; Yepes, Gustavo; Jullo, Eric; Niemiec, Anna; Kneib, Jean-Paul; Rodríguez-Torres, Sergio; Klypin, Anatoly; Skibba, Ramin; McBride, Cameron K.; Eisenstein, Daniel J.; Schlegel, David J.; Nuza, S. E.; Chuang, Chia-Hsun; Delubac, Timothée; Yèche, Ch; Schneider, Donald P.

doi:10.1093/mnras/stw1483

Cited by 75 publications

(84 citation statements)

References 81 publications

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“…Model galaxies with a brighter [OII] flux are less clustered in both real and redshift space. This contradicts what is found observationally at z = 0 (Favole et al 2016) and is related to the number of star-forming galaxies satellites in the model (see Fig. 2).…”

Section: The Correlation Function In Redshift-spacecontrasting

confidence: 92%

“…15. In this figure we compare model galaxies selected with the same g-band cut to the results from Favole et al (2016). Note that the clustering of model galaxies with F [OII] > 10 −18 erg s −1 cm −2 and 20 < g < 22.8 overlap for separations above 10h −1 Mpc and below this separation they are comparable.…”

Section: The Correlation Function In Redshift-spacementioning

confidence: 93%

“…The linear bias is also calculated in real space and we compare it with the expectations for eBOSS and DESI ( § 5.1). Favole et al (2016) measured the redshift space monopole for a sample at z ∼ 0.8 of g-selected galaxies that they claim is comparable to a selection of [O ii] emitters. We also make cuts similar to those in Favole et al in order to compare the results for g-band selected galaxies and [O ii] emitters with their observed clustering ( § 5.2).…”

Section: The Clustering Of [O Ii] Emittersmentioning

confidence: 99%

“…Model galaxies appear to be less clustered than the current observations of g-selected samples. Favole et al (2016) used weak lensing to estimate the typical mass of haloes hosting g-band selected galaxies, finding (1.25 ± 0.45) × 10 12 h −1 M . Within the same redshift range, the model g-band sample is hosted by haloes with an average mass of ∼ 10 11.8 h −1 M , consistent with the val- ues reported observationally, although somewhat on the low side.…”

Section: The Correlation Function In Redshift-spacementioning

confidence: 99%

“…We adopt a physical approach rather than the empirical one used in Favole et al (2016). The use of a semi-analytical model of galaxy formation and evolution (see White & Frenk 1991;Lacey & Silk 1991;Kauffmann et al 1993;Cole et al 1994;Somerville & Primack 1999, for some of the early developments in this field) gives us the tools to understand the physical processes that are the most relevant for the evolution of (Comparat et al 2015).…”

Section: Introductionmentioning

confidence: 99%

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The host dark matter haloes of [O II] emitters at 0.5 < z < 1.5

González-Pérez¹,

Comparat²,

Norberg³

et al. 2017

Monthly Notices of the Royal Astronomical Society

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Emission line galaxies (ELGs) are used in several ongoing and upcoming surveys (SDSS-IV/eBOSS, DESI) as tracers of the dark matter distribution. Using a new galaxy formation model, we explore the characteristics of [O ii] emitters, which dominate optical ELG selections at z 1. Model [O ii] emitters at 0.5 < z < 1.5 are selected to mimic the DEEP2, VVDS, eBOSS and DESI surveys. The luminosity functions of model [O ii] emitters are in reasonable agreement with observations. The selected [O ii] emitters are hosted by haloes with M halo 10 10.3 h −1 M , with ∼ 90% of them being central star-forming galaxies. The predicted mean halo occupation distributions of [O ii] emitters has a shape typical of that inferred for star-forming galaxies, with the contribution from central galaxies, N [O ii] cen , being far from the canonical step function. The N [O ii] cen can be described as the sum of an asymmetric Gaussian for disks and a step function for spheroids, which plateaus below unity. The model [O ii] emitters have a clustering bias close to unity, which is below the expectations for eBOSS and DESI ELGs. At z ∼ 1, a comparison with observed g-band selected galaxy, which are expected to be dominated by [O ii] emitters, indicates that our model produces too few [O ii] emitters that are satellite galaxies. This suggests the need to revise our modelling of hot gas stripping in satellite galaxies.

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Section: The Correlation Function In Redshift-spacecontrasting

confidence: 92%

Section: The Correlation Function In Redshift-spacementioning

confidence: 93%

Section: The Clustering Of [O Ii] Emittersmentioning

confidence: 99%

Section: The Correlation Function In Redshift-spacementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The host dark matter haloes of [O II] emitters at 0.5 < z < 1.5

González-Pérez¹,

Comparat²,

Norberg³

et al. 2017

Monthly Notices of the Royal Astronomical Society

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Large-scale dark matter simulations

Angulo

Hahn

2022

Living Rev Comput Astrophys

111

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We review the field of collisionless numerical simulations for the large-scale structure of the Universe. We start by providing the main set of equations solved by these simulations and their connection with General Relativity. We then recap the relevant numerical approaches: discretization of the phase-space distribution (focusing on N-body but including alternatives, e.g., Lagrangian submanifold and Schrödinger–Poisson) and the respective techniques for their time evolution and force calculation (direct summation, mesh techniques, and hierarchical tree methods). We pay attention to the creation of initial conditions and the connection with Lagrangian Perturbation Theory. We then discuss the possible alternatives in terms of the micro-physical properties of dark matter (e.g., neutralinos, warm dark matter, QCD axions, Bose–Einstein condensates, and primordial black holes), and extensions to account for multiple fluids (baryons and neutrinos), primordial non-Gaussianity and modified gravity. We continue by discussing challenges involved in achieving highly accurate predictions. A key aspect of cosmological simulations is the connection to cosmological observables, we discuss various techniques in this regard: structure finding, galaxy formation and baryonic modelling, the creation of emulators and light-cones, and the role of machine learning. We finalise with a recount of state-of-the-art large-scale simulations and conclude with an outlook for the next decade.

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SDSS-IV eBOSS emission-line galaxy pilot survey

Comparat

Delubac

Jouvel

et al. 2016

A&A

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The Sloan Digital Sky Survey IV extended Baryonic Oscillation Spectroscopic Survey (SDSS-IV/eBOSS) will observe 195 000 emission-line galaxies (ELGs) to measure the baryonic acoustic oscillation (BAO) standard ruler at redshift 0.9. To test different ELG selection algorithms, 9000 spectra were observed with the SDSS spectrograph as a pilot survey based on data from several imaging surveys. First, using visual inspection and redshift quality flags, we show that the automated spectroscopic redshifts assigned by the pipeline meet the quality requirements for a reliable BAO measurement. We also show the correlations between sky emission, signal-to-noise ratio in the emission lines, and redshift error. Then we provide a detailed description of each target selection algorithm we tested and compare them with the requirements of the eBOSS experiment. As a result, we provide reliable redshift distributions for the different target selection schemes we tested. Finally, we determine an target selection algorithms that is best suited to be applied on DECam photometry because they fulfill the eBOSS survey efficiency requirements.

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Clustering properties ofg-selected galaxies atz∼ 0.8

Cited by 75 publications

References 81 publications

The host dark matter haloes of [O II] emitters at 0.5 < z < 1.5

The host dark matter haloes of [O II] emitters at 0.5 < z < 1.5

Large-scale dark matter simulations

SDSS-IV eBOSS emission-line galaxy pilot survey

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