Galaxy Formation in the Santa Cruz semi-analytic model compared with IllustrisTNG -- I. Galaxy scaling relations, dispersions, and residuals at z=0

Gabrielpillai, Austen; Somerville, Rachel S.; Genel, Shy; Rodríguez-Gómez, Vicente; Pandya, Viraj; Yung, L. Y. Aaron; Hernquist, Lars

doi:10.48550/arxiv.2111.03077

Cited by 3 publications

(4 citation statements)

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“…For example, for stellar masses and star formation rates, it is known that the residual of these quantities from the mean at a given halo mass is correlated with other halo properties, such as formation history (e.g., Matthee et al 2017), that are known to be correlated with the halo clustering strength via a process called assembly bias (Croton et al 2007). We can think of these as limitations of the standard halo model approach, which could be relatively easily overcome by using SAMs run within merger trees extracted from dissipationless simulations, which we have done in other work (e.g., Gabrielpillai et al 2021;Hadzhiyska et al 2021).…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, it is challenging to connect line emission mechanisms happening on the atomic scale to the sub-parsec-scale molecular clouds, kiloparsec-scale galaxies, and megaparsec-scale dark matter halos. There are many analytic models in the literature describing the major submillimeter LIM targets, including CO, [C II], [O III], and [N II] lines (e.g., Lidz et al 2011;Gong et al 2012;Pullen et al 2013;Kamenetzky et al 2014;Silva et al 2015;Mashian et al 2015;Li et al 2016;Pullen et al 2018;Padmanabhan 2019;Sun et al 2019;Yang & Lidz 2020;Padmanabhan et al 2021). All those models include empirical treatments to some degree and fail to simultaneously cover all the lines of interest.…”

Section: Introductionmentioning

confidence: 99%

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An Empirical Representation of a Physical Model for the ISM [C ii], CO, and [C i] Emission at Redshift 1 ≤ z ≤ 9

Yang

Popping

Somerville

et al. 2022

ApJ

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Submillimeter emission lines produced by the interstellar medium (ISM) are strong tracers of star formation and are some of the main targets of line intensity mapping (LIM) surveys. In this work we present an empirical multiline emission model that simultaneously covers the mean, scatter, and correlations of [C ii], CO J = 1–0 to J = 5–4, and [C i] lines in the redshift range 1 ≤ z ≤ 9. We assume that the galaxy ISM line emission luminosity versus halo mass relations can be described by double power laws with redshift-dependent lognormal scatter. The model parameters are then derived by fitting to the state-of-the-art semianalytic simulation results that have successfully reproduced multiple submillimeter line observations at 0 ≤ z ≲ 6. We cross-check the line emission statistics predicted by the semianalytic simulation and our empirical model, finding that at z ≥ 1 our model reproduces the simulated line intensities with fractional error less than about 10%. The fractional difference is less than 25% for the power spectra. Grounded on physically motivated and self-consistent galaxy simulations, this computationally efficient model will be helpful in forecasting ISM emission-line statistics for upcoming LIM surveys.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Empirical Representation of a Physical Model for the ISM [C ii], CO, and [C i] Emission at Redshift 1 ≤ z ≤ 9

Yang

Popping

Somerville

et al. 2022

ApJ

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“…We also perform additional cross-checks using the concentration obtained by fitting an NFW profile to the halos. In particular, we use c NFW ≡ R vir /R scale (R vir is the virial radius and R scale is the Klypin scale radius (Klypin et al 2011) corresponding to the largest subhalo in the halo) measurements by Gabrielpillai et al (2021), which were obtained by running the Rockstar code (Behroozi et al 2013) on the TNG300 halos.…”

Section: Cluster Data and Propertiesmentioning

confidence: 99%

Augmenting astrophysical scaling relations with machine learning: application to reducing the Sunyaev-Zeldovich flux-mass scatter

Wadekar¹,

Thiele²,

Villaescusa-Navarro³

et al. 2022

Preprint

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Complex systems (stars, supernovae, galaxies, and clusters) often exhibit low scatter relations between observable properties (e.g., luminosity, velocity dispersion, oscillation period, temperature). These scaling relations can illuminate the underlying physics and can provide observational tools for estimating masses and distances. Machine learning can provide a fast and systematic way to search for new scaling relations (or for simple extensions to existing relations) in abstract high-dimensional parameter spaces. We use a machine learning tool called symbolic regression (SR), which models the patterns in a given dataset in the form of analytic equations. We focus on the Sunyaev-Zeldovich flux−cluster mass relation (Y SZ − M ), the scatter in which affects inference of cosmological parameters from cluster abundance data. Using SR on the data from the IllustrisTNG hydrodynamical simulation, we find a new proxy for cluster mass which combines Y SZ and concentration of ionized gas (c gas ):SZ (1 − A c gas ). Y conc reduces the scatter in the predicted M by ∼ 20 − 30% for large clusters (M 10 14 h −1 M ) at both high and low redshifts, as compared to using just Y SZ . We show that the dependence on c gas is linked to cores of clusters exhibiting larger scatter than their outskirts. Finally, we test Y conc on clusters from simulations of the CAMELS project and show that Y conc is robust against variations in cosmology, astrophysics, subgrid physics, and cosmic variance. Our results and methodology can be useful for accurate multiwavelength cluster mass estimation from current and upcoming CMB and X-ray surveys like ACT, SO, SPT, eROSITA and CMB-S4.1. INTRODUCTION Astrophysical scaling relations are simple low-scatter relationships (generally power laws) between properties of astrophysical systems which hold over a wide range of parameter values. Some notable examples of such relations are the Phillips relation for supernovae (Phillips 1993), the Color-Magnitude Relation, the Leavitt period luminosity relation for Cepheids (Leavitt & Pickering 1912;Riess et al. 2016Riess et al. , 2019, the Tully Fisher relation (Tully & Fisher 1977) and its baryonic analogue (McGaugh et al. 2000) for spiral galaxies, the

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“…Using the Rockstar catalog of (gravity-only) IllustrisTNG parent halos (Behroozi et al 2013) produced in Gabrielpillai et al (2021), we measure properties of the individual halos, such as the radius R 200 and mass M 200 , where R 200 is the radius at which the mean interior density is 200 times the critical density ρ cr (z) (Battaglia et al 2012), defined as…”

Section: Data Extraction and Modellingmentioning

confidence: 99%

An exploration of the properties of cluster profiles for the thermal and kinetic Sunyaev-Zel'dovich effects

Lee,

Coulton,

Thiele

et al. 2022

Preprint

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With the advent of high-resolution, low-noise CMB measurements, the ability to extract cosmological information from thermal Sunyaev-Zel'dovich effect and kinetic Sunyaev-Zel'dovich effect will be limited not by statistical uncertainties but rather by systematic and theoretical uncertainties. The theoretical uncertainty is driven by the lack of knowledge about the electron pressure and density. Thus we explore the electron pressure and density distributions in the IllustrisTNG hydrodynamical simulations, and we demonstrate that the cluster properties exhibit a strong dependence on the halo concentration -providing some of the first evidence of cluster assembly bias in the electron pressure and density. Further, our work shows evidence for a broken power-law mass dependence, with lower pressure in lower mass halos than previous work and a strong evolution with mass of the radial correlations in the electron density and pressure. Both of these effects highlight the differing impact of active galactic nuclei and supernova feedback on the gas in galaxy groups compared to massive clusters. We verified that we see qualitatively similar features in the SIMBA hydro-dynamical simulations, suggesting these effects could be generic features. Finally, we provide a parametric formula for the electron pressure and density profile as a function of dark matter halo mass, halo concentration, and redshift. These fitting formulae can reproduce the distribution of density and pressure of clusters and will be useful in extracting cosmological information from upcoming CMB surveys.

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Galaxy Formation in the Santa Cruz semi-analytic model compared with IllustrisTNG -- I. Galaxy scaling relations, dispersions, and residuals at z=0

Cited by 3 publications

References 61 publications

An Empirical Representation of a Physical Model for the ISM [C ii], CO, and [C i] Emission at Redshift 1 ≤ z ≤ 9

An Empirical Representation of a Physical Model for the ISM [C ii], CO, and [C i] Emission at Redshift 1 ≤ z ≤ 9

Augmenting astrophysical scaling relations with machine learning: application to reducing the Sunyaev-Zeldovich flux-mass scatter

An exploration of the properties of cluster profiles for the thermal and kinetic Sunyaev-Zel'dovich effects

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