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1. Evidence of galaxy assembly bias in SDSS DR7 galaxy samples from count statistics

   https://doi.org/10.1093/mnras/stac2465  

   Wang, Kuan ; Mao, Yao-Yuan ; Zentner, Andrew R. ; Guo, Hong ; Lange, Johannes U. ; van den Bosch, Frank C. ; Mezini, Lorena ( September 2022 , Monthly Notices of the Royal Astronomical Society)

   We present observational constraints on the galaxy–halo connection, focusing particularly on galaxy assembly bias from a novel combination of counts-in-cylinders statistics, P(NCIC), with the standard measurements of the projected two-point correlation function wp(rp), and number density ngal of galaxies. We measure ngal, wp(rp), and P(NCIC) for volume-limited, luminosity-threshold samples of galaxies selected from SDSS DR7, and use them to constrain halo occupation distribution (HOD) models, including a model in which galaxy occupation depends upon a secondary halo property, namely halo concentration. We detect significant positive central assembly bias for the Mr < −20.0 and Mr < −19.5 samples. Central galaxies preferentially reside within haloes of high concentration at fixed mass. Positive central assembly bias is also favoured in the Mr < −20.5 and Mr < −19.0 samples. We find no evidence of central assembly bias in the Mr < −21.0 sample. We observe only a marginal preference for negative satellite assembly bias in the Mr < −20.0 and Mr < −19.0 samples, and non-zero satellite assembly bias is not indicated in other samples. Our findings underscore the necessity of accounting for galaxy assembly bias when interpreting galaxy survey data, and demonstrate the potential of count statistics in extracting information from the spatial distribution of galaxies, which could be applied to both galaxy–halo connection studies and cosmological analyses.

    

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2. Toward Accurate Modeling of Galaxy Clustering on Small Scales: Halo Model Extensions and Lingering Tension

   https://doi.org/10.3847/1538-4357/acc576  

   Beltz-Mohrmann, Gillian D. ; Szewciw, Adam O. ; Berlind, Andreas A. ; Sinha, Manodeep ( May 2023 , The Astrophysical Journal)

   This paper represents an effort to provide robust constraints on the galaxy–halo connection and simultaneously test the Planck ΛCDM cosmology using a fully numerical model of small-scale galaxy clustering. We explore two extensions to the standard Halo Occupation Distribution model: assembly bias, whereby halo occupation depends on both halo mass and the larger environment, and velocity bias, whereby galaxy velocities do not perfectly trace the velocity of the dark matter within the halo. Moreover, we incorporate halo mass corrections to account for the impact of baryonic physics on the halo population. We identify an optimal set of clustering measurements to constrain this “decorated” HOD model for both low- and high-luminosity galaxies in SDSS DR7. We find that, for low-luminosity galaxies, a model with both assembly bias and velocity bias provides the best fit to the clustering measurements, with no tension remaining in the fit. In this model, we find evidence for both central and satellite galaxy assembly bias at the 99% and 95% confidence levels, respectively. In addition, we find evidence for satellite galaxy velocity bias at the 99.9% confidence level. For high-luminosity galaxies, we find no evidence for either assembly bias or velocity bias, but our model exhibits significant tension with SDSS measurements. We find that all of these conclusions still stand when we include the effects of baryonic physics on the halo mass function, suggesting that the tension we find for high-luminosity galaxies may be due to a problem with our assumed cosmological model.

    

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3. Testing the accuracy of halo occupation distribution modelling using hydrodynamic simulations

   https://doi.org/10.1093/mnras/stz3442  

   Beltz-Mohrmann, Gillian D ; Berlind, Andreas A ; Szewciw, Adam O ( February 2020 , Monthly Notices of the Royal Astronomical Society)

   null (Ed.)

   ABSTRACT Halo models provide a simple and computationally inexpensive way to investigate the connection between galaxies and their dark matter haloes. However, these models rely on the assumption that the role of baryons can easily be parametrized in the modelling procedure. We aim to examine the ability of halo occupation distribution (HOD) modelling to reproduce the galaxy clustering found in two different hydrodynamic simulations, Illustris and EAGLE. For each simulation, we measure several galaxy clustering statistics on two different luminosity threshold samples. We then apply a simple five parameter HOD, which was fit to each simulation separately, to the corresponding dark matter-only simulations, and measure the same clustering statistics. We find that the halo mass function is shifted to lower masses in the hydrodynamic simulations, resulting in a galaxy number density that is too high when an HOD is applied to the dark matter-only simulation. However, the exact way in which baryons alter the mass function is remarkably different in the two simulations. After applying a correction to the halo mass function in each simulation, the HOD is able to accurately reproduce all clustering statistics for the high luminosity sample of galaxies. For the low luminosity sample, we find evidence that in addition to correcting the halo mass function, including spatial, velocity, and assembly bias parameters in the HOD is necessary to accurately reproduce clustering statistics. 

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4. Exploiting non-linear scales in galaxy–galaxy lensing and galaxy clustering: A forecast for the dark energy survey

   https://doi.org/10.1093/mnras/stab3793  

   Salcedo, Andrés N. ; Weinberg, David H. ; Wu, Hao-Yi ; Wibking, Benjamin D. ( January 2022 , Monthly Notices of the Royal Astronomical Society)

   The combination of galaxy–galaxy lensing (GGL) and galaxy clustering is a powerful probe of low-redshift matter clustering, especially if it is extended to the non-linear regime. To this end, we use an N-body and halo occupation distribution (HOD) emulator method to model the redMaGiC sample of colour-selected passive galaxies in the Dark Energy Survey (DES), adding parameters that describe central galaxy incompleteness, galaxy assembly bias, and a scale-independent multiplicative lensing bias Alens. We use this emulator to forecast cosmological constraints attainable from the GGL surface density profile ΔΣ(rp) and the projected galaxy correlation function wp, gg(rp) in the final (Year 6) DES data set over scales $r_p=0.3\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$. For a $3{{\ \rm per\ cent}}$ prior on Alens we forecast precisions of $1.9{{\ \rm per\ cent}}$, $2.0{{\ \rm per\ cent}}$, and $1.9{{\ \rm per\ cent}}$ on Ωm, σ8, and $S_8 \equiv \sigma _8\Omega _m^{0.5}$, marginalized over all halo occupation distribution (HOD) parameters as well as Alens. Adding scales $r_p=0.3\!-\!3.0\, h^{-1} \, \mathrm{Mpc}$ improves the S8 precision by a factor of ∼1.6 relative to a large scale ($3.0\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$) analysis, equivalent to increasing the survey area by a factor of ∼2.6. Sharpening the Alens prior to $1{{\ \rm per\ cent}}$ further improves the S8 precision to $1.1{{\ \rm per\ cent}}$, and it amplifies the gain from including non-linear scales. Our emulator achieves per cent-level accuracy similar to the projected DES statistical uncertainties, demonstrating the feasibility of a fully non-linear analysis. Obtaining precise parameter constraints from multiple galaxy types and from measurements that span linear and non-linear clustering offers many opportunities for internal cross-checks, which can diagnose systematics and demonstrate the robustness of cosmological results.

    

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5. Using Maximum Circular Velocity in Halo Occupation Distribution Models to Predict Galaxy Clustering

   https://doi.org/10.3847/2515-5172/ac67f3  

   Mezini, Lorena ; Wang, Kuan ; Mao, Yao-Yuan ; Zentner, Andrew R. ( April 2022 , Research Notes of the AAS)

   Standard halo occupation distribution (HOD) models predict how galaxies occupy halos based on a single property, the virial mass,M_vir. To incorporate galaxy assembly bias, we consider alternative halo mass proxies to use in the HOD. A promising replacement is maximum circular velocity,$V_{\max }$, which measures the halo’s potential well, and successfully predicts galaxy clustering in subhalo abundance matching models. We fit galaxy clustering measurements from SDSS DR7 with two modified HODs besides the standardM_vir-based model: one where$V_{\max }$is used as the halo property that determines galaxy occupation, and the other adopting an adjustable combination ofM_virand$V_{\max }$. Except for the reduced volumeM_r < − 20 threshold sample fit with$V_{\max }$alone, neither change improves the model performance in predicting the projected two-point correlation function,w_p. We conclude that switching the primary variable to$V_{\max }$does not significantly improve the HOD model’s ability to fit galaxy clustering.

    

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