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ChangHoon Hahn

Publications and source records attributed to ChangHoon Hahn.

83 records · Page 5Linked to original sources

IQ-Collaboratory 1.1: the Star-Forming Sequence of Simulated Central Galaxies

A tightly correlated star formation rate-stellar mass relation of star forming galaxies, or star-forming sequence (SFS), is a key feature in galaxy property-space that is predicted by modern galaxy formation models. We present a flexible data-driven approach for identifying this SFS over a wide range of star formation rates and stellar masses using Gaussian mixture modeling (GMM). Using this method, we present a consistent comparison of the $z=0$ SFSs of central galaxies in the Illustris, EAGLE, and Mufasa hydrodynamic simulations and the Santa Cruz semi-analytic model (SC-SAM), alongside data from the Sloan Digital Sky Survey. We find, surprisingly, that the amplitude of the SFS varies by up to ${\sim} 0.7\,\mathrm{dex}$ (factor of ${\sim} 5$) among the simulations with power-law slopes range from $0.7$ to $1.2$. In addition to the SFS, our GMM method also identifies sub-components in the star formation rate-stellar mass relation corresponding to star-burst, transitioning, and quiescent sub-populations. The hydrodynamic simulations are similarly dominated by SFS and quiescent sub-populations unlike the SC-SAM, which predicts substantial fractions of transitioning and star-burst galaxies at stellar masses above and below $10^{10} M_\odot$, respectively. All of the simulations also produce an abundance of low-mass quiescent central galaxies in apparent tension with observations. These results illustrate that, even among models that well reproduce many observables of the galaxy population, the $z=0$ SFS and other sub-populations still show marked differences that can provide strong constraints on galaxy formation models.

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Likelihood Non-Gaussianity in Large-Scale Structure Analyses

Standard present day large-scale structure (LSS) analyses make a major assumption in their Bayesian parameter inference --- that the likelihood has a Gaussian form. For summary statistics currently used in LSS, this assumption, even if the underlying density field is Gaussian, cannot be correct in detail. We investigate the impact of this assumption on two recent LSS analyses: the Beutler et al. (2017) power spectrum multipole ($P_\ell$) analysis and the Sinha et al. (2017) group multiplicity function ($ζ$) analysis. Using non-parametric divergence estimators on mock catalogs originally constructed for covariance matrix estimation, we identify significant non-Gaussianity in both the $P_\ell$ and $ζ$ likelihoods. We then use Gaussian mixture density estimation and Independent Component Analysis on the same mocks to construct likelihood estimates that approximate the true likelihood better than the Gaussian $pseudo$-likelihood. Using these likelihood estimates, we accurately estimate the true posterior probability distribution of the Beutler et al. (2017) and Sinha et al. (2017) parameters. Likelihood non-Gaussianity shifts the $fσ_8$ constraint by $-0.44σ$, but otherwise, does not significantly impact the overall parameter constraints of Beutler et al. (2017). For the $ζ$ analysis, using the pseudo-likelihood significantly underestimates the uncertainties and biases the constraints of Sinha et al. (2017) halo occupation parameters. For $\log M_1$ and $α$, the posteriors are shifted by $+0.43σ$ and $-0.51σ$ and broadened by $42\%$ and $66\%$, respectively. The divergence and likelihood estimation methods we present provide a straightforward framework for quantifying the impact of likelihood non-Gaussianity and deriving more accurate parameter constraints.

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The clustering of luminous red galaxies at z $\sim$ 0.7 from eBOSS and BOSS data

We present the first scientific results from the luminous red galaxy sample (LRG) of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). We measure the small and intermediate scale clustering from a sample of more than 61,000 galaxies in the redshift range $0.6 < z < 0.9$. We interpret these measurements in the framework of the Halo Occupation Distribution. The bias of eBOSS LRGs is $2.30 \pm 0.03$, with a satellite fraction of $13\pm3$\% and a mean halo mass of $2.5\times10^{13}h^{-1}M_{\odot}$. These results are consistent with expectations, demonstrating that eBOSS galaxies will be reliable tracers of large scale structure at $z\sim 0.7$. The eBOSS galaxy bias implies a scatter of luminosity at fixed halo mass, $σ_{\log L}$, of 0.19 dex. Using the clustering of massive galaxies from BOSS-CMASS, BOSS-LOWZ, and SDSS, we find that $σ_{\log L}=0.19$ is consistent with observations over the full redshift range that these samples cover. The addition of eBOSS to previous surveys allows investigation of the evolution of massive galaxies over the past $\sim 7$ Gyr.

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Accurate halo-galaxy mocks from automatic bias estimation and particle mesh gravity solvers

Reliable extraction of cosmological information from clustering measurements of galaxy surveys requires estimation of the error covariance matrices of observables. The accuracy of covariance matrices is limited by our ability to generate sufficiently large number of independent mock catalogs that can describe the physics of galaxy clustering across a wide range of scales. Furthermore, galaxy mock catalogs are required to study systematics in galaxy surveys and to test analysis tools. In this investigation, we present a fast and accurate approach for generation of mock catalogs for the upcoming galaxy surveys. Our method relies on low-resolution approximate gravity solvers to simulate the large scale dark matter field, which we then populate with halos according to a flexible nonlinear and stochastic bias model. In particular, we extend the \textsc{patchy} code with an efficient particle mesh algorithm to simulate the dark matter field (the \textsc{FastPM} code), and with a robust MCMC method relying on the \textsc{emcee} code for constraining the parameters of the bias model. Using the halos in the BigMultiDark high-resolution $N$-body simulation as a reference catalog, we demonstrate that our technique can model the bivariate probability distribution function (counts-in-cells), power spectrum, and bispectrum of halos in the reference catalog. Specifically, we show that the new ingredients permit us to reach percentage accuracy in the power spectrum up to $k\sim 0.4\; \,h\,{\rm Mpc}^{-1}$ (within 5\% up to $k\sim 0.6\; \,h\,{\rm Mpc}^{-1}$) with accurate bispectra improving previous results based on Lagrangian perturbation theory.

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Halo Histories vs. Galaxy Properties at z=0, III: The Properties of Star-Forming Galaxies

We measure how the properties of star-forming central galaxies correlate with large-scale environment, $δ$, measured on $10$Mpc/h scales. We use group catalogs to isolate a robust sample of central galaxies with high purity and completeness. The properties we investigate are star formation rate (SFR), exponential disk scale length $R_{\rm exp}$, and Sersic index of the light profile, $n$. We find that, at all stellar masses, there is an inverse correlation between SFR and $δ$, meaning that above-average star forming centrals live in underdense regions. For $n$ and $R_{\rm exp}$, there is no correlation with $δ$ at $M_{\rm star}\lesssim 10^{10.5}$ $M_\odot$, but at higher masses there are positive correlations; a weak correlation with $R_{\rm exp}$ and a strong correlation with $n$. These data are evidence of assembly bias within the star-forming population. The results for SFR are consistent with a model in which SFR correlates with present-day halo accretion rate, $\dot{M}_h$. In this model, galaxies are assigned to halos using the abundance matching ansatz, which maps galaxy stellar mass onto halo mass. At fixed halo mass, SFR is assigned to galaxies using the same approach,but $\dot{M}_h$ is used to map onto SFR. The best-fit model requires some scatter in the $\dot{M}_h$-SFR relation. The $R_{\rm exp}$ and $n$ measurements are consistent with a model in which these quantities are correlated with the spin parameter of the halo, $λ$. Halo spin does not correlate with $δ$ at low halo masses, but for higher mass halos, high-spin halos live in higher density environments at fixed $M_h$. Put together with the earlier installments of this series, these data demonstrate that quenching processes have limited correlation with halo formation history, but the growth of active galaxies, as well as other detailed properties, are influenced by the details of halo assembly.

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Approximate Bayesian Computation in Large Scale Structure: constraining the galaxy-halo connection

Standard approaches to Bayesian parameter inference in large scale structure assume a Gaussian functional form (chi-squared form) for the likelihood. This assumption, in detail, cannot be correct. Likelihood free inferences such as Approximate Bayesian Computation (ABC) relax these restrictions and make inference possible without making any assumptions on the likelihood. Instead ABC relies on a forward generative model of the data and a metric for measuring the distance between the model and data. In this work, we demonstrate that ABC is feasible for LSS parameter inference by using it to constrain parameters of the halo occupation distribution (HOD) model for populating dark matter halos with galaxies. Using specific implementation of ABC supplemented with Population Monte Carlo importance sampling, a generative forward model using HOD, and a distance metric based on galaxy number density, two-point correlation function, and galaxy group multiplicity function, we constrain the HOD parameters of mock observation generated from selected "true" HOD parameters. The parameter constraints we obtain from ABC are consistent with the "true" HOD parameters, demonstrating that ABC can be reliably used for parameter inference in LSS. Furthermore, we compare our ABC constraints to constraints we obtain using a pseudo-likelihood function of Gaussian form with MCMC and find consistent HOD parameter constraints. Ultimately our results suggest that ABC can and should be applied in parameter inference for LSS analyses.

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Clustering of quasars in the First Year of the SDSS-IV eBOSS survey: Interpretation and halo occupation distribution

In current and future surveys, quasars play a key role. The new data will extend our knowledge of the Universe as it will be used to better constrain the cosmological model at redshift $z>1$ via baryon acoustic oscillation and redshift space distortion measurements. Here, we present the first clustering study of quasars observed by the extended Baryon Oscillation Spectroscopic Survey. We measure the clustering of $\sim 70,000$ quasars located in the redshift range $0.9<z<2.2$ that cover 1,168 deg$^2$. We model the clustering and produce high-fidelity quasar mock catalogues based on the BigMultiDark Planck simulation. Thus, we use a modified (Sub)Halo Abundance Matching model to account for the specificities of the halo population hosting quasars. We find that quasars are hosted by halos with masses $\sim10^{12.7}M_\odot$ and their bias evolves from 1.54 ($z=1.06$) to 3.15 ($z=1.98$). Using the current eBOSS data, we cannot distinguish between models with different fractions of satellites. The high-fidelity mock light-cones, including properties of halos hosting quasars, are made publicly available.

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Halo Histories vs. Galaxy Properties at z=0 II: Large-Scale Galactic Conformity

Using group catalogs from the SDSS DR7, we attempt to measure galactic conformity in the local universe. We measure the quenched fraction of neighbor galaxies around isolated primary galaxies, dividing the isolated sample into star-forming and quiescent objects. We restrict our measurements to scales $>1$ Mpc to probe the correlations between the formation histories of distinct halos. Over the stellar mass range $10^{9.7} \le M_\ast/M_\odot \le 10^{10.9}$, we find minimal statistical evidence for conformity. We further compare these data to predictions of the halo age-matching model, in which the oldest galaxies are associated with the oldest halos at fixed $M_\ast$. For models with strong correlations between halo and stellar age, the conformity signal is too large to be consistent with the data. For weaker implementations of age-matching, galactic conformity is not a sensitive diagnostic of halo assembly bias, and would not produce a detectable signal in SDSS data. We reproduce the results of Kauffmann et al 2013, in which the star formation rates of neighbor galaxies are significantly reduced around primary galaxies when the primaries are themselves low star formers. However, we find this result is mainly driven by contamination in the isolation criterion, when using our group catalog to remove the small fraction of satellite galaxies in the sample, the conformity signal largely goes away. Lastly, we show that small conformity signals, i.e., 2-5% differences in the quenched fractions of neighbor galaxies, can be produced by mechanisms other than halo assembly bias. For example, if passive galaxies occupy more massive halos than star forming galaxies of the same stellar mass, a conformity signal that is consistent with recent measurements from PRIMUS (Berti et al 2016) can be produced.

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Star Formation Quenching Timescale of Central Galaxies in a Hierarchical Universe

Central galaxies make up the majority of the galaxy population, including the majority of the quiescent population at $\mathcal{M}_* > 10^{10}\mathrm{M}_\odot$. Thus, the mechanism(s) responsible for quenching central galaxies plays a crucial role in galaxy evolution as whole. We combine a high resolution cosmological $N$-body simulation with observed evolutionary trends of the "star formation main sequence," quiescent fraction, and stellar mass function at $z < 1$ to construct a model that statistically tracks the star formation histories and quenching of central galaxies. Comparing this model to the distribution of central galaxy star formation rates in a group catalog of the SDSS Data Release 7, we constrain the timescales over which physical processes cease star formation in central galaxies. Over the stellar mass range $10^{9.5}$ to $10^{11} \mathrm{M}_\odot$ we infer quenching e-folding times that span $1.5$ to $0.5\; \mathrm{Gyr}$ with more massive central galaxies quenching faster. For $\mathcal{M}_* = 10^{10.5}\mathrm{M}_\odot$, this implies a total migration time of $\sim 4~\mathrm{Gyrs}$ from the star formation main sequence to quiescence. Compared to satellites, central galaxies take $\sim 2~\mathrm{Gyrs}$ longer to quench their star formation, suggesting that different mechanisms are responsible for quenching centrals versus satellites. Finally, the central galaxy quenching timescale we infer provides key constraints for proposed star formation quenching mechanisms. Our timescale is generally consistent with gas depletion timescales predicted by quenching through strangulation. However, the exact physical mechanism(s) responsible for this still remain unclear.

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The Effect of Fiber Collisions on the Galaxy Power Spectrum Multipole

Fiber-fed multi-object spectroscopic surveys, with their ability to collect an unprecedented number of redshifts, currently dominate large-scale structure studies. However, physical constraints limit these surveys from successfully collecting redshifts from galaxies too close to each other on the focal plane. This ultimately leads to significant systematic effects on galaxy clustering measurements. Using simulated mock catalogs, we demonstrate that fiber collisions have a significant impact on the power spectrum, $P(k)$, monopole and quadrupole that exceeds sample variance at scales smaller than $k\sim0.1~h/Mpc$. We present two methods to account for fiber collisions in the power spectrum. The first, statistically reconstructs the clustering of fiber collided galaxy pairs by modeling the distribution of the line-of-sight displacements between them. It also properly accounts for fiber collisions in the shot-noise correction term of the $P(k)$ estimator. Using this method, we recover the true $P(k)$ monopole of the mock catalogs with residuals of $<0.5\%$ at $k=0.3~h/Mpc$ and $<4\%$ at $k=0.83~h/Mpc$ -- a significant improvement over existing correction methods. The quadrupole, however, does not improve significantly. The second method models the effect of fiber collisions on the power spectrum as a convolution with a configuration space top-hat function that depends on the physical scale of fiber collisions. It directly computes theoretical predictions of the fiber-collided $P(k)$ multipoles and reduces the influence of smaller scales to a set of nuisance parameters. Using this method, we reliably model the effect of fiber collisions on the monopole and quadrupole down to the scale limits of theoretical predictions. The methods we present in this paper will allow us to robustly analyze galaxy power spectrum multipole measurements to much smaller scales than previously possible.

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PRIMUS: Effect of Galaxy Environment on the Quiescent Fraction Evolution at z < 0.8

We investigate the effects of galaxy environment on the evolution of the quiescent fraction ($f_\mathrm{Q}$) from z =0.8 to 0.0 using spectroscopic redshifts and multi-wavelength imaging data from the PRIsm MUlti-object Survey (PRIMUS) and the Sloan Digitial Sky Survey (SDSS). Our stellar mass limited galaxy sample consists of ~14,000 PRIMUS galaxies within z = 0.2-0.8 and ~64,000 SDSS galaxies within z = 0.05-0.12. We classify the galaxies as quiescent or star-forming based on an evolving specific star formation cut, and as low or high density environments based on fixed cylindrical aperture environment measurements on a volume-limited environment defining population. For quiescent and star-forming galaxies in low or high density environments, we examine the evolution of their stellar mass function (SMF). Then using the SMFs we compute $f_\mathrm{Q}(M_{*})$ and quantify its evolution within our redshift range. We find that the quiescent fraction is higher at higher masses and in denser environments. The quiescent fraction rises with cosmic time for all masses and environments. At a fiducial mass of $10^{10.5}M_\odot$, from z~0.7 to 0.1, the quiescent fraction rises by 15% at the lowest environments and by 25% at the highest environments we measure. These results suggest that for a minority of galaxies their cessation of star formation is due to external influences on them. However, in the recent Universe a substantial fraction of the galaxies that cease forming stars do so due to internal processes.

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