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Models of the spatial distribution of dark matter halos must achieve new levels of precision and accuracy in order to satisfy the requirements of upcoming experiments. In this work, we present a halo bias emulator for modeling the clustering of halos on large scales. It incorporates the cosmological dependence of the bias beyond the mapping of halo mass to peak height. The emulator makes substantial improvements in accuracy compared to the widely used Tinker et al. (2010) model. Halos in this work are defined using an overdensity criteria of 200 relative to the mean background density. Halo catalogs are produced for 40 N-body simulations as part of the Aemulus project at snapshots from z=3 to z=0. The emulator is trained over the mass range $6\times10^{12}-7\times10^{15}\ h^{-1}M_{\odot}$. Using an additional suite of 35 simulations, we determine that the precision of the emulator is redshift dependent, achieving sub-percent levels for a majority of the redshift range. Two additional simulation suites are used to test the ability of the emulator to extrapolate to higher and lower masses. Our high-resolution simulation suite is used to develop an extrapolation scheme in which the emulator asymptotes to the Tinker et al. (2010) model at low mass, achieving ~3% accuracy down to $10^{11}\ h^{-1}M_{\odot}$. Finally, we present a method to propagate emulator modeling uncertainty into an error budget. Our emulator is made publicly available at \url{https://github.com/AemulusProject/bias_emulator}., Comment: 14 pages, 7 figures, Submitted to ApJ

Development of the hardware, data analysis, and simulation techniques for large compact radio arrays dedicated to mapping the 21 cm line of neutral hydrogen gas has proven to be more difficult than imagined twenty years ago when such telescopes were first proposed. Despite tremendous technical and methodological advances, there are several outstanding questions on how to optimally calibrate and analyze such data. On the positive side, it has become clear that the outstanding issues are purely technical in nature and can be solved with sufficient development activity. Such activity will enable science across redshifts, from early galaxy evolution in the pre-reionization era to dark energy evolution at low redshift., Comment: 10 pages + references, 2 figures, 1 table; APC white paper submitted to the Astro2020 decadal survey. arXiv admin note: text overlap with arXiv:1810.09572

Modern cosmological analyses constrain physical parameters using Markov Chain Monte Carlo (MCMC) or similar sampling techniques. Oftentimes, these techniques are computationally expensive to run and require up to thousands of CPU hours to complete. Here we present a method for reconstructing the log-probability distributions of completed experiments from an existing MCMC chain (or any set of posterior samples). The reconstruction is performed using Gaussian process regression for interpolating the log-probability. This allows for easy resampling, importance sampling, marginalization, testing different samplers, investigating chain convergence, and other operations. As an example use-case, we reconstruct the posterior distribution of the most recent Planck 2018 analysis. We then resample the posterior, and generate a new MCMC chain with forty times as many points in only thirty minutes. Our likelihood reconstruction tool can be found online at https://github.com/tmcclintock/AReconstructionTool., Comment: 7 pages, 4 figures, repository at https://github.com/tmcclintock/AReconstructionTool

The Core Cosmology Library (CCL) provides routines to compute basic cosmological observables to a high degree of accuracy, which have been verified with an extensive suite of validation tests. Predictions are provided for many cosmological quantities, including distances, angular power spectra, correlation functions, halo bias and the halo mass function through state-of-the-art modeling prescriptions available in the literature. Fiducial specifications for the expected galaxy distributions for the Large Synoptic Survey Telescope (LSST) are also included, together with the capability of computing redshift distributions for a user-defined photometric redshift model. A rigorous validation procedure, based on comparisons between CCL and independent software packages, allows us to establish a well-defined numerical accuracy for each predicted quantity. As a result, predictions for correlation functions of galaxy clustering, galaxy-galaxy lensing and cosmic shear are demonstrated to be within a fraction of the expected statistical uncertainty of the observables for the models and in the range of scales of interest to LSST. CCL is an open source software package written in C, with a python interface and publicly available at https://github.com/LSSTDESC/CCL., Comment: 38 pages, 18 figures, matches ApJS accepted version

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

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/

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/

The recent discovery of the ultraluminous quasar SDSS J010013.02+280225.8 at redshift 6.3 has exacerbated the time compression problem implied by the appearance of supermassive black holes only ~900 Myr after the big bang, and only ~500 Myr beyond the formation of Pop II and III stars. Aside from heralding the onset of cosmic reionization, these first and second generation stars could have reasonably produced the ~5-20 solar-mass seeds that eventually grew into z~6-7 quasars. But this process would have taken ~900 Myr, a timeline that appears to be at odds with the predictions of LCDM without an anomalously high accretion rate, or some exotic creation of ~10^5 solar-mass seeds. There is no evidence of either of these happening in the local universe. In this paper, we show that a much simpler, more elegant solution to the supermassive black hole anomaly is instead to view this process using the age-redshift relation predicted by the R_h=ct Universe, an FRW cosmology with zero active mass. In this context, cosmic reionization lasted from t~883 Myr to ~2 Gyr (z~15 to z~6), so ~5-20 solar-mass black hole seeds formed shortly after reionization had begun, would have evolved into ~10^10 solar-mass quasars by z~6-7 simply via the standard Eddington-limited accretion rate. The consistency of these observations with the age-redshift relationship predicted by R_h=ct supports the existence of dark energy; but not in the form of a cosmological constant., Comment: 10 Pages, 2 Figures, 1 Table. Accepted for publication in Proc. R. Soc. A

The recently constructed Hubble diagram using a combined sample of SNLS and SDSS-II Type Ia SNe, and an application of the Alcock-Paczynski (AP) test using model-independent Baryon Acoustic Oscillation data, have suggested that the principal constraint underlying the cosmic expansion is the total equation-of-state of the cosmic fluid, rather than that of its dark energy. These studies have focused on the critical redshift range (0 < z < 2) within which the transition from decelerated to accelerated expansion is thought to have occurred, and they suggest that the cosmic fluid has zero active mass, consistent with a constant expansion rate. The evident impact of this conclusion on cosmological theory calls for an independent confirmation. In this paper, we carry out this crucial one-on-one comparison between the R_h=ct Universe (an FRW cosmology with zero active mass) and wCDM/LCDM, using the latest high-z measurements of H(z). Whereas the Type Ia SNe yield the integrated luminosity distance, while the AP diagnostic tests the geometry of the Universe, the Hubble parameter directly samples the expansion rate itself. We find that the model-independent cosmic chronometer data prefer R_h}=ct over wCDM/LCDM with a BIC likelihood of ~95% versus only ~5%, in strong support of the earlier SNeIa and AP results. This contrasts with a recent analysis of H(z) data based solely on BAO measurements which, however, strongly depend on the assumed cosmology. We discuss why the latter approach is inappropriate for model comparisons, and emphasize again the need for truly model-independent observations to be used in cosmological tests., Comment: 22 pages, 1 figure, 1 table. Accepted for publication in the Astronomical Journal