137 research outputs found
Cosmological Analysis of Three-Dimensional BOSS Galaxy Clustering and Planck CMB Lensing Cross Correlations via Lagrangian Perturbation Theory
We present a formalism for jointly fitting pre- and post-reconstruction
redshift-space clustering (RSD) and baryon acoustic oscillations (BAO) plus
gravitational lensing (of the CMB) that works directly with the observed
2-point statistics. The formalism is based upon (effective) Lagrangian
perturbation theory and a Lagrangian bias expansion, which models RSD, BAO and
galaxy-lensing cross correlations within a consistent dynamical framework. As
an example we present an analysis of clustering measured by the Baryon
Oscillation Spectroscopic Survey in combination with CMB lensing measured by
Planck. The post-reconstruction BAO strongly constrains the distance-redshift
relation, the full-shape redshift-space clustering constrains the matter
density and growth rate, and CMB lensing constrains the clustering amplitude.
Using only the redshift space data we obtain , and . The addition of
lensing information, even when restricted to the Northern Galactic Cap,
improves constraints to ,
and , in tension with CMB and cosmic shear
constraints. The combination of and are consistent with
Planck, though their constraints derive mostly from redshift-space clustering.
The low value are driven by cross correlations with CMB lensing in
the low redshift bin () and at large angular scales, which show a
deficit compared to expectations from galaxy clustering alone. We
conduct several systematics tests on the data and find none that could fully
explain these tensions.Comment: 46 pages, 15 figures, updated to match version accepted by JCA
Precision Redshift-Space Galaxy Power Spectra using Zel'dovich Control Variates
Numerical simulations in cosmology require trade-offs between volume,
resolution and run-time that limit the volume of the Universe that can be
simulated, leading to sample variance in predictions of ensemble-average
quantities such as the power spectrum or correlation function(s). Sample
variance is particularly acute at large scales, which is also where analytic
techniques can be highly reliable. This provides an opportunity to combine
analytic and numerical techniques in a principled way to improve the dynamic
range and reliability of predictions for clustering statistics. In this paper
we extend the technique of Zel'dovich control variates, previously demonstrated
for 2-point functions in real space, to reduce the sample variance in
measurements of 2-point statistics of biased tracers in redshift space. We
demonstrate that with this technique, we can reduce the sample variance of
these statistics down to their shot-noise limit out to . This allows a better matching with perturbative models and improved
predictions for the clustering of e.g.~quasars, galaxies and neutral Hydrogen
measured in spectroscopic redshift surveys at very modest computational
expense. We discuss the implementation of ZCV, give some examples and provide
forecasts for the efficacy of the method under various conditions.Comment: 17 pages main text, 5 pages of appendices, 9 figure
The Aemulus Project III: Emulation of the Galaxy Correlation Function
Using the N-body simulations of the AEMULUS Project, we construct an emulator
for the non-linear clustering of galaxies in real and redshift space. We
construct our model of galaxy bias using the halo occupation framework,
accounting for possible velocity bias. The model includes 15 parameters,
including both cosmological and galaxy bias parameters. We demonstrate that our
emulator achieves ~ 1% precision at the scales of interest, 0.1<r<10 h^{-1}
Mpc, and recovers the true cosmology when tested against independent
simulations. Our primary parameters of interest are related to the growth rate
of structure, f, and its degenerate combination fsigma_8. Using this emulator,
we show that the constraining power on these parameters monotonically increases
as smaller scales are included in the analysis, all the way down to 0.1 h^{-1}
Mpc. For a BOSS-like survey, the constraints on fsigma_8 from r<30 h^{-1} Mpc
scales alone are more than a factor of two tighter than those from the fiducial
BOSS analysis of redshift-space clustering using perturbation theory at larger
scales. The combination of real- and redshift-space clustering allows us to
break the degeneracy between f and sigma_8, yielding a 9% constraint on f alone
for a BOSS-like analysis. The current AEMULUS simulations limit this model to
surveys of massive galaxies. Future simulations will allow this framework to be
extended to all galaxy target types, including emission-line galaxies.Comment: 14 pages, 8 figures, 1 table; submitted to ApJ; the project webpage
is available at https://aemulusproject.github.io ; typo in Figure 7 and
caption updated, results unchange
The Aemulus Project I: Numerical Simulations for Precision Cosmology
The rapidly growing statistical precision of galaxy surveys has lead to a
need for ever-more precise predictions of the observables used to constrain
cosmological and galaxy formation models. The primary avenue through which such
predictions will be obtained is suites of numerical simulations. These
simulations must span the relevant model parameter spaces, be large enough to
obtain the precision demanded by upcoming data, and be thoroughly validated in
order to ensure accuracy. In this paper we present one such suite of
simulations, forming the basis for the AEMULUS Project, a collaboration devoted
to precision emulation of galaxy survey observables. We have run a set of 75
(1.05 h^-1 Gpc)^3 simulations with mass resolution and force softening of
3.51\times 10^10 (Omega_m / 0.3) ~ h^-1 M_sun and 20 ~ h^-1 kpc respectively in
47 different wCDM cosmologies spanning the range of parameter space allowed by
the combination of recent Cosmic Microwave Background, Baryon Acoustic
Oscillation and Type Ia Supernovae results. We present convergence tests of
several observables including spherical overdensity halo mass functions, galaxy
projected correlation functions, galaxy clustering in redshift space, and
matter and halo correlation functions and power spectra. We show that these
statistics are converged to 1% (2%) for halos with more than 500 (200)
particles respectively and scales of r>200 ~ h^-1 kpc in real space or k ~ 3 h
Mpc^-1 in harmonic space for z\le 1. We find that the dominant source of
uncertainty comes from varying the particle loading of the simulations. This
leads to large systematic errors for statistics using halos with fewer than 200
particles and scales smaller than k ~ 4 h^-1 Mpc. We provide the halo catalogs
and snapshots detailed in this work to the community at
https://AemulusProject.github.io.Comment: 16 pages, 12 figures, 3 Tables Project website:
https://aemulusproject.github.io
The Aemulus Project II: Emulating the Halo Mass Function
Existing models for the dependence of the halo mass function on cosmological
parameters will become a limiting source of systematic uncertainty for cluster
cosmology in the near future. We present a halo mass function emulator and
demonstrate improved accuracy relative to state-of-the-art analytic models. In
this work, mass is defined using an overdensity criteria of 200 relative to the
mean background density. Our emulator is constructed from the AEMULUS
simulations, a suite of 40 N-body simulations with snapshots from z=3 to z=0.
These simulations cover the flat wCDM parameter space allowed by recent Cosmic
Microwave Background, Baryon Acoustic Oscillation and Type Ia Supernovae
results, varying the parameters w, Omega_m, Omega_b, sigma_8, N_{eff}, n_s, and
H_0. We validate our emulator using five realizations of seven different
cosmologies, for a total of 35 test simulations. These test simulations were
not used in constructing the emulator, and were run with fully independent
initial conditions. We use our test simulations to characterize the modeling
uncertainty of the emulator, and introduce a novel way of marginalizing over
the associated systematic uncertainty. We confirm non-universality in our halo
mass function emulator as a function of both cosmological parameters and
redshift. Our emulator achieves better than 1% precision over much of the
relevant parameter space, and we demonstrate that the systematic uncertainty in
our emulator will remain a negligible source of error for cluster abundance
studies through at least the LSST Year 1 data set.Comment: https://aemulusproject.github.io
Priors on red galaxy stochasticity from hybrid effective field theory
We investigate the stochastic properties of typical red galaxy samples in a
controlled numerical environment. We use Halo Occupation Distribution (HOD)
modelling to create mock realizations of three separate bright red galaxy
samples consistent with datasets used for clustering and lensing analyses in
modern galaxy surveys. Second-order Hybrid Effective Field Theory (HEFT) is
used as a field-level forward model to describe the full statistical
distribution of these tracer samples, and their stochastic power spectra are
directly measured and compared to the Poisson shot-noise prediction. While all
of the galaxy samples we consider are hosted within haloes with sub-Poisson
stochasticity, we observe that the galaxy samples themselves possess
stochasticities that range from sub-Poisson to super-Poisson, in agreement with
predictions from the halo model. As an application of our methodology, we place
priors on the expected degree of non-Poisson stochasticity in cosmological
analyses using such samples. We expect these priors will be useful in reducing
the complexity of the full parameter space for future analyses using
second-order Lagrangian bias models. More generally, the techniques outlined
here present the first application of hybrid EFT methods to characterize models
of the galaxy--halo connection at the field level, revealing new connections
between once-disparate modelling frameworks.Comment: 16 pages, 10 figures. Revised version accepted to MNRAS. Revisions
include a new appendix on the covariance of the field-level bias estimato
The cosmology dependence of galaxy clustering and lensing from a hybrid -body-perturbation theory model
We implement a model for the two-point statistics of biased tracers that
combines dark matter dynamics from -body simulations with an analytic
Lagrangian bias expansion. Using Aemulus, a suite of -body simulations built
for emulation of cosmological observables, we emulate the cosmology dependence
of these nonlinear spectra from redshifts to . We quantify the
accuracy of our emulation procedure, which is sub-per cent at for the redshifts probed by upcoming surveys and improves at higher
redshifts. We demonstrate its ability to describe the statistics of complex
tracer samples, including those with assembly bias and baryonic effects,
reliably fitting the clustering and lensing statistics of such samples at
redshift to scales of . We show that the emulator can be used for unbiased
cosmological parameter inference in simulated joint clustering and
galaxy--galaxy lensing analyses with data drawn from an independent -body
simulation. These results indicate that our emulator is a promising tool that
can be readily applied to the analysis of current and upcoming datasets from
galaxy surveys.Comment: 19 pages, 17 figures. Updated to reflect the journal version. Code
available at https://github.com/kokron/anz
The Aemulus Project VI: Emulation of beyond-standard galaxy clustering statistics to improve cosmological constraints
There is untapped cosmological information in galaxy redshift surveys in the
non-linear regime. In this work, we use the AEMULUS suite of cosmological
-body simulations to construct Gaussian process emulators of galaxy
clustering statistics at small scales () in
order to constrain cosmological and galaxy bias parameters. In addition to
standard statistics -- the projected correlation function
, the redshift-space monopole of the correlation
function , and the quadrupole -- we emulate statistics
that include information about the local environment, namely the underdensity
probability function and the density-marked correlation
function . This extends the model of AEMULUS III for redshift-space
distortions by including new statistics sensitive to galaxy assembly bias. In
recovery tests, we find that the beyond-standard statistics significantly
increase the constraining power on cosmological parameters of interest:
including and improves the precision of our
constraints on by 33%, by 28%, and the growth of
structure parameter, , by 18% compared to standard statistics. We
additionally find that scales below contain as much
information as larger scales. The density-sensitive statistics also contribute
to constraining halo occupation distribution parameters and a flexible
environment-dependent assembly bias model, which is important for extracting
the small-scale cosmological information as well as understanding the
galaxy-halo connection. This analysis demonstrates the potential of emulating
beyond-standard clustering statistics at small scales to constrain the growth
of structure as a test of cosmic acceleration. Our emulator is publicly
available at https://github.com/kstoreyf/aemulator.Comment: Submitted to the Astrophysical Journal; comments welcom
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