Linear bias and halo occupation distribution of emission-line galaxies from <i>Nancy Grace Roman Space Telescope</i>

Zhai, Zhongxu; Wang, Yun; Benson, Andrew; Chuang, Chia-Hsun; Yepes, Gustavo

doi:10.1093/mnras/stab1539

Cited by 16 publications

(13 citation statements)

References 71 publications

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“…Another noticeable feature is that Galacticus model shows slightly bi-modal distribution of EW at higher redshift, originating from the two branches of the galaxy population which is also shown in Figure 4. This is likely related to the two sequences on the galaxy star formation rate and halo mass due to periods of mass loss, see discussion in Zhai et al (2021). The bottom panels of Figure 6 display the distribution for 𝐻-band magnitude.…”

Section: Comparison With Wispmentioning

confidence: 88%

“…Based on our previous forecast work using Galacticus (Zhai et al 2019), for a flux limit of 1.0 × 10 −16 erg s −1 cm −2 at 6.5𝜎, Roman HLSS can observe more than 10M H𝛼 ELGs with 1 < 𝑧 < 2, and another 2M [OIII] ELGs with 2 < 𝑧 < 3. The Roman science requirement of detecting both lines ensures a high purity sample for BAO/RSD measurements (Zhai et al 2021). Compared with the Euclid survey which has the line flux limit of 2.0×10 −16 erg s −1 cm −2 at 3.5𝜎, Roman HLSS is designed to enable robust modeling of systematic effects.…”

Section: Roman Hlssmentioning

confidence: 99%

“…The analysis of this paper is based on a synthetic galaxy catalog produced by Galacticus (Benson 2012)-a semi-analytical model (SAM) for galaxy formation and evolution. Compared with our previous works using the same methodology in Zhai et al (2019Zhai et al ( , 2020Zhai et al ( , 2021, the Galacticus software has been updated with better efficiency of ODE solver, and better control of numerical performance. These changes can affect some particular galaxy properties, however the galaxy statistics are only mildly influenced as we show below.…”

Section: Galacticus Modelmentioning

confidence: 99%

“…Using the same SAM, we produce a larger galaxy mock covering 2000 deg 2 sky area and investigate the clustering properties of H𝛼 galaxies (Zhai et al 2020); we analyze this mock by applying methods used in analyzing real data, and evaluate the significance of BAO and RSD measurements. This cosmology mock is further applied in Zhai et al (2021), we measure the linear bias of H𝛼 and [OIII] galaxies for Roman HLSS with different sample selections. This can provide critical information for a following Fisher matrix analysis to forecast the ability of the survey to constrain cosmology and dark energy (Wang 2008).…”

Section: Introductionmentioning

confidence: 99%

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Simulating properties of emission line galaxies from Nancy Grace Roman Space Telescope

Zhai¹,

Wang²,

Benson³

et al. 2021

Preprint

Self Cite

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We simulate the emission line galaxy properties for the Nancy Grace Roman Space Telescope by creating a 4 deg 2 galaxy mock catalog using Galacticus, a semi-analytic model (SAM) for galaxy formation and evolution. The simulated galaxy properties include emission line luminosity, equivalent width (EW), broad band photometry, and spectral energy distribution (SED). We compare this mock catalog with the latest observational data from WISP and MOSDEF. We find that our Galacticus model makes predictions consistent with observational data, over a wide redshift range for multiple emission lines. We use this validated galaxy mock catalog to forecast the photometric completeness of H𝛼 and [OIII] emission lines as a function of line flux cut and H band magnitdue cut, for both Roman and Euclid-like surveys. Our prediction for the photometric completeness of a Euclid-like survey is in good agreement with previous work based on WISP data. Our predictions for the photometric completeness of possible implementations of the Roman High Latitude Wide Area Spectroscopic Survey (HLWASS) provides key input for the planning of such a survey. We find that at H = 24, a Euclid-like survey to the line flux limit of 2×10 −16 erg/s/cm 2 is 97% complete, while a Roman HLWASS to the line flux limit of 10 −16 erg/s/cm 2 is only 94.6% complete (it becomes 98% complete at H = 25).

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Section: Comparison With Wispmentioning

confidence: 88%

Section: Roman Hlssmentioning

confidence: 99%

Section: Galacticus Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Simulating properties of emission line galaxies from Nancy Grace Roman Space Telescope

Zhai¹,

Wang²,

Benson³

et al. 2021

Preprint

Self Cite

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show abstract

“…An additional advantage of using Fix, Pair and Match together is that one can use a high mass resolution in order to resolve well the halos of interests for future surveys (log𝑀 ℎ ∼ 11 for Euclid and DESI) in a 𝑉 ∼ 1(Gpc/ℎ) 3 box with reasonable computing resources (𝑁 = 4096 3 in UNITsim), while keeping a reduced uncertainty on 𝑓 NL (or 𝑝 or 𝑏 𝜙 ). This way, one could also use semi-analytical models of galaxy formation (as recently done in Zhai et al 2021;Knebe et al 2022, to populate 14 https://www.desi.lbl.gov/ 15 https://sci.esa.int/web/euclid UNITsim with H-𝛼 galaxies for Roman/Euclid) to understand the effect of galaxy formation on 𝑝 or 𝑏 𝜙 for different tracers (as done in Barreira et al 2020;Barreira 2021).…”

Section: Discussionmentioning

confidence: 99%

Validating galaxy clustering models with Fixed & Paired and Matched-ICs simulations: application to Primordial Non-Gaussianities

Ávila¹,

Adame²

2022

Preprint

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The Fix and Pair techniques were designed to generate simulations with reduced variance in the 2-point statistics by modifying the Initial Conditions (ICs). In this paper we show that this technique is also valid when the initial conditions have local non-Gaussianities (PNG), parametrised by 𝑓 NL , without biasing the 2-point statistics but reducing significantly their variance. We show how to quantitatively use these techniques to test the accuracy of galaxy/halo clustering models down to a much reduced uncertainty and we apply them to test the standard model for halo clustering in the presence of PNG. Additionally, we show that by Matching the stochastic part of the ICs for two different cosmologies (Gaussian and non-Gaussian) we obtain a large correlation between the (2-point) statistics that can explicitly be used to further reduce the uncertainty of the model testing. For our reference analysis (we obtain an uncertainty of 𝜎( 𝑓 NL ) = 60 with a standard simulation, whereas using Fixed [Fixed-Paired] initial conditions it reduces to 𝜎( 𝑓 NL ) = 12 [𝜎( 𝑓 NL ) = 12]. When also Matching the ICs we obtain 𝜎( 𝑓 NL ) = 18 for the standard case, and 𝜎( 𝑓 NL ) = 8 [𝜎( 𝑓 NL ) = 7] for Fixed [Fixed-Paired]. The combination of the Fix, Pair and Match techniques can be used in the context of PNG to create simulations with an effective volume incremented by a factor ∼ 70 at given computational resources.

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Predicting interloper fraction with graph neural networks

Massara,

Villaescusa-Navarro,

Percival

2023

J. Cosmol. Astropart. Phys.

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Upcoming emission-line spectroscopic surveys, such as Euclid and the Roman Space Telescope, will be affected by systematic effects due to the presence of interlopers: galaxies whose redshift and distance from us are miscalculated due to line confusion in their emission spectra. Particularly pernicious are interlopers involving the confusion between two lines with close emitted wavelengths, like Hβ emitters confused as [O iii], since those are strongly spatially correlated with the target galaxies. They introduce a particular pattern in the 3D distribution of the observed galaxy catalog that can shift the position of the BAO peak in the galaxy correlation function and bias any cosmological analysis performed with that sample. Here we present a novel method to predict the fraction of interlopers in a galaxy catalog, using Graph Neural Networks (GNNs) to learn the posterior distribution of the interloper fraction while marginalizing over cosmology and galaxy bias. The method is developed using simulations with halos acting as a proxy for galaxies. The GNN can infer the mean and standard deviation of the posterior distribution of interloper fraction using small-scale information that is usually not considered in cosmological analyses. The injection of large-scale information into the graph as a global attribute improves the performance of the GNN when marginalizing over cosmology.

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Linear bias and halo occupation distribution of emission-line galaxies from Nancy Grace Roman Space Telescope

Cited by 16 publications

References 71 publications

Simulating properties of emission line galaxies from Nancy Grace Roman Space Telescope

Simulating properties of emission line galaxies from Nancy Grace Roman Space Telescope

Validating galaxy clustering models with Fixed & Paired and Matched-ICs simulations: application to Primordial Non-Gaussianities

Predicting interloper fraction with graph neural networks

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