Galaxy Redshift Survey Research Articles

Deep ugrizY imaging and DEEP2/3 spectroscopy: a photometric redshift testbed for LSST and public release of data from the DEEP3 Galaxy Redshift Survey

ABSTRACT We present catalogues of calibrated photometry and spectroscopic redshifts in the Extended Groth Strip, intended for studies of photometric redshifts (photo-z’s). The data includes ugriz photometry from Canada–France–Hawaii Telescope Legacy Survey (CFHTLS) and Y-band photometry from the Subaru Suprime camera, as well as spectroscopic redshifts from the DEEP2, DEEP3, and 3D-HST surveys. These catalogues incorporate corrections to produce effectively matched-aperture photometry across all bands, based upon object size information available in the catalogue and Moffat profile point spread function fits. We test this catalogue with a simple machine learning-based photometric redshift algorithm based upon Random Forest regression, and find that the corrected aperture photometry leads to significant improvement in photo-z accuracy compared to the original SExtractor catalogues from CFHTLS and Subaru. The deep ugrizY photometry and spectroscopic redshifts are well suited for empirical tests of photometric redshift algorithms for LSST. The resulting catalogues are publicly available at http://d-scholarship.pitt.edu/36064/. We include a basic summary of the strategy of the DEEP3 Galaxy Redshift Survey to accompany the recent public release of DEEP3 data.

Testing general relativity with the Doppler magnification effect

ABSTRACT The apparent sizes and brightnesses of galaxies are correlated in a dipolar pattern around matter overdensities in redshift space, appearing larger on their near side and smaller on their far side. The opposite effect occurs for galaxies around an underdense region. These patterns of apparent magnification induce dipole and higher multipole terms in the cross-correlation of galaxy number density fluctuations with galaxy size/brightness (which is sensitive to the convergence field). This provides a means of directly measuring peculiar velocity statistics at low and intermediate redshift, with several advantages for performing cosmological tests of general relativity (GR). In particular, it does not depend on empirically calibrated scaling relations like the Tully–Fisher and Fundamental Plane methods. We show that the next generation of spectroscopic galaxy redshift surveys will be able to measure the Doppler magnification effect with sufficient signal-to-noise ratio to test GR on large scales. We illustrate this with forecasts for the constraints that can be achieved on parametrized deviations from GR for forthcoming low-redshift galaxy surveys with DESI and SKA2. Although the cross-correlation statistic considered has a lower signal-to-noise ratio than RSD, it will be a useful probe of GR since it is sensitive to different systematics.

The Truncated Lindley Distribution with Applications in Astrophysics

This paper reviews the Lindley distribution and then introduces the scale and the double truncation. The unknown parameters of the truncated Lindley distribution are evaluated with the maximum likelihood estimators. An application of the Lindley distribution with scale is done to the initial mass function for stars. The magnitude version of the Lindley distribution with scale is applied to the luminosity function for the Sloan Digital Sky Survey (SDSS) galaxies and to the photometric maximum of the 2MASS Redshift Survey (2MRS) galaxies. The truncated Lindley luminosity function allows to model the Malquist bias of the 2MRS galaxies.

Optimally Mapping Large-scale Structures with Luminous Sources

Abstract Intensity mapping has emerged as a promising tool to probe the three-dimensional structure of the universe. The traditional approach of galaxy redshift surveys is based on individual galaxy detection, typically performed by thresholding and digitizing large-scale intensity maps. By contrast, intensity mapping uses the integrated emission from all sources in a 3D pixel (or voxel) as an analog tracer of large-scale structure. In this work, we develop a formalism to quantify the performance of both approaches when measuring large-scale structures. We compute the Fisher information of an arbitrary observable, derive the optimal estimator, and study its performance as a function of source luminosity function, survey resolution, instrument sensitivity, and other survey parameters. We identify regimes where each approach is advantageous and discuss optimal strategies for different scenarios. To determine the best strategy for any given survey, we develop a metric that is easy to compute from the source luminosity function and the survey sensitivity, and we demonstrate the application with several planned intensity mapping surveys.

On structure formation from a small-scales-interacting dark sector

We consider a cosmological model with an interaction between dark matter and dark energy which leaves the background cosmology unaffected and only affects the evolution of the perturbations. This is achieved by introducing a coupling given in terms of the relative velocities of dark matter and dark energy. This interaction has the distinctive feature of appearing predominantly on small scales, where peculiar velocities can become important. We confront the predictions of the model to cosmological observations and find a potential alleviation of the known tension in the amplitude of density perturbations as measured by low redshift galaxy surveys and the Planck data. The model also predicts a shift in the turnover of the matter power spectrum which does not depend on the horizon at equality (fixed by the background cosmology and, thus, unaffected by the perturbations) and is entirely due to the interaction between dark matter and dark energy. A bias in the peculiar velocity between baryons and dark matter is also shown to be a unique feature of this type of interactions in the dark sector.

Simulated multitracer analyses with H i intensity mapping

We use full sky simulations, including the effects of foreground contamination and removal, to explore multi-tracer synergies between a SKA-like 21cm intensity mapping survey and a LSST-like photometric galaxy redshift survey. In particular we study ratios of auto and cross-correlations between the two tracers as estimators of the ratio of their biases, a quantity that should benefit considerably from the cosmic variance cancellation of the multi-tracer approach. We show how well we should be able to measure the bias ratio on very large scales (down to $\ell \sim 3$), which is crucial to measure primordial non-Gaussianity and general relativistic effects on large scale structure. We find that, in the absence of foregrounds but with realistic noise levels of such surveys, the multi-tracer estimators are able to improve on the sensitivity of a cosmic-variance contaminated measurement by a factor of $2-4$. When foregrounds are included, estimators using the 21cm auto-correlation become biased. However, we show that cross-correlation estimators are immune to this and do not incur in any significant penalty in terms of sensitivity from discarding the auto-correlation data. However, the loss of long-wavelength radial modes caused by foreground removal in combination with the low redshift resolution of photometric surveys, reduces the sensitivity of the multi-tracer estimator, albeit still better than the cosmic variance contaminated scenario even in the noise free case. Finally we explore different alternative avenues to avoid this problem.

Renormalization group computation of likelihood functions for cosmological data sets

I show how a renormalization group (RG) method can be used to incrementally integrate the information in cosmological large-scale structure data sets (including CMB, galaxy redshift surveys, etc.). I show numerical tests for Gaussian fields, where the method allows arbitrarily close to exact computation of the likelihood function in order $\sim N$ time, even for problems with no symmetry, compared to $N^3$ for brute force linear algebra (where $N$ is the number of data points -- to be fair, methods already exist to solve the Gaussian problem in at worst $N \log N$ time, and this method will not necessarily be faster in practice). The method requires no sampling or other Monte Carlo (random) element. Non-linearity/non-Gaussianity can be accounted for to the extent that terms generated by integrating out small scale modes can be projected onto a sufficient basis, e.g., at least in the sufficiently perturbative regime. The formulas to evaluate are straightforward and require no understanding of quantum field theory, but this paper may also serve as a pedagogical introduction to Wilsonian RG for astronomers.

Measuring the ISW effect with next-generation radio surveys

The late-time integrated Sachs-Wolfe (ISW) signal in the CMB temperature anisotropies is an important probe of dark energy when it can be detected by cross-correlation with large-scale structure surveys. Because of their huge sky area, surveys in the radio are well-suited to ISW detection. We show that 21cm intensity mapping and radio continuum surveys with the SKA in Phase~1 promise a $\sim5\sigma$ detection if we use tomography, with a similar forecast for the precursor EMU survey. In SKA Phase~2, the 21cm galaxy redshift survey and the continuum survey could deliver a $\sim6\sigma$ detection. Our analysis of the radio surveys aims for theoretical accuracy on large scales. Firstly, we include all the effects on the radio surveys from observing on the past lightcone: redshift-space distortions and lensing magnification can have a significant impact on the ISW signal to noise ratio, while Doppler and other relativistic distortions are not significant. Secondly, we use the full information in the observable galaxy angular power spectra $C_\ell(z,z')$, by avoiding the Limber approximation and by including all cross-correlations between redshift bins in the covariance. Without these cross-bin correlations, the ISW signal to noise ratio is biased.

Effects of [N ii] and H α line blending on theWFIRSTGalaxy redshift survey

The Wide Field Infrared Survey Telescope (WFIRST) will conduct a galaxy redshift survey using the H$\alpha$ emission line primarily for spectroscopic redshift determination. Due to the modest spectroscopic resolution of the grism, the H$\alpha$ and the neighboring [NII] lines are blended, leading to a redshift bias that depends on the [NII]/H$\alpha$ ratio, which is correlated with a galaxy's metallicity, hence mass and ultimately environment. We investigate how this bias propagates into the galaxy clustering and cosmological parameters obtained from the WFIRST. Using simulation, we explore the effect of line blending on redshift-space distortion and baryon acoustic oscillation (BAO) measurements. We measure the BAO parameters $\alpha_{\parallel}$, $\alpha_{\perp}$, the logarithmic growth factor $f_{v}$, and calculate their errors based on the correlations between the line ratio and large-scale structure. We find $\Delta\alpha_{\parallel} = 0.31 \pm 0.23 \%$ ($0.26\pm0.17\%$), $\Delta\alpha_{\perp} = -0.10\pm0.10\%$ ($-0.12 \pm 0.11 \%$), and $\Delta f_{v} = 0.17\pm0.33\%$ ($-0.20 \pm 0.30\%$) for redshift 1.355--1.994 (0.700--1.345), which use approximately 18$\%$, 9$\%$, and 7$\%$ of the systematic error budget in a root-sum-square sense. These errors may already be tolerable but further mitigations are discussed. Biases due to the environment-independent redshift error can be mitigated by measuring the redshift error probability distribution function. High-spectral-resolution re-observation of a few thousand galaxies would be required (if by direct approach) to reduce them to below 25$\%$ of the error budget. Finally, we outline the next steps to improve the modeling of [NII]-induced blending biases and their interaction with other redshift error sources.

Cosmological inference from Bayesian forward modelling of deep galaxy redshift surveys

We present a large-scale Bayesian inference framework to constrain cosmological parameters using galaxy redshift surveys, via an application of the Alcock-Paczyński (AP) test. Our physical model of the non-linearly evolved density field, as probed by galaxy surveys, employs Lagrangian perturbation theory (LPT) to connect Gaussian initial conditions to the final density field, followed by a coordinate transformation to obtain the redshift space representation for comparison with data. We have implemented a Hamiltonian Monte Carlo sampler to generate realisations of three-dimensional (3D) primordial and present-day matter fluctuations from a non-Gaussian LPT-Poissonian density posterior given a set of observations. This hierarchical approach encodes a novel AP test, extracting several orders of magnitude more information from the cosmic expansion compared to classical approaches, to infer cosmological parameters and jointly reconstruct the underlying 3D dark matter density field. The novelty of this AP test lies in constraining the comoving-redshift transformation to infer the appropriate cosmology which yields isotropic correlations of the galaxy density field, with the underlying assumption relying purely on the geometrical symmetries of the cosmological principle. Such an AP test does not rely explicitly on modelling the full statistics of the field. We verified in depth via simulations that this renders our test robust to model misspecification. This leads to another crucial advantage, namely that the cosmological parameters exhibit extremely weak dependence on the currently unresolved phenomenon of galaxy bias, thereby circumventing a potentially key limitation. This is consequently among the first methods to extract a large fraction of information from statistics other than that of direct density contrast correlations, without being sensitive to the amplitude of density fluctuations. We perform several statistical efficiency and consistency tests on a mock galaxy catalogue, using the SDSS-III survey as template, taking into account the survey geometry and selection effects, to validate the Bayesian inference machinery implemented.

A rigorous EFT-based forward model for large-scale structure

Conventional approaches to cosmology inference from galaxy redshift surveys are based on n-point functions, which are under rigorous perturbative control on sufficiently large scales. Here, we present an alternative approach, which employs a likelihood at the level of the galaxy density field. By integrating out small-scale modes based on effective-field theory arguments, we prove that this likelihood is under perturbative control if certain specific conditions are met. We further show that the information captured by this likelihood is equivalent to the combination of the next-to-leading order galaxy power spectrum, leading-order bispectrum, and BAO reconstruction. Combined with MCMC sampling and MAP optimization techniques, our results allow for fully Bayesian cosmology inference from large-scale structure that is under perturbative control. We illustrate this via a first demonstration of unbiased cosmology inference from nonlinear large-scale structure using this likelihood. In particular, we show unbiased estimates of the power spectrum normalization σ8 from a catalog of simulated dark matter halos, where nonlinear information is crucial in breaking the b1−σ8 degeneracy.

The promising future of a robust cosmological neutrino mass measurement

We forecast the sensitivity of thirty-five different combinations of future Cosmic Microwave Background and Large Scale Structure data sets to cosmological parameters and to the total neutrino mass. We work under conservative assumptions accounting for uncertainties in the modelling of systematics. In particular, for galaxy redshift surveys, we remove the information coming from non-linear scales. We use Bayesian parameter extraction from mock likelihoods to avoid Fisher matrix uncertainties. Our grid of results allows for a direct comparison between the sensitivity of different data sets. We find that future surveys will measure the neutrino mass with high significance and will not be substantially affected by potential parameter degeneracies between neutrino masses, the density of relativistic relics, and a possible time-varying equation of state of Dark Energy.

The extended Baryon Oscillation Spectroscopic Survey: testing a new approach to measure the evolution of the structure growth

The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is one of the first of a new generation of galaxy redshift surveys that will cover a large range in redshift with sufficient resolution to measure the baryon acoustic oscillations (BAO) signal. For surveys covering a large redshift range we can no longer ignore cosmological evolution, meaning that either the redshift shells analysed have to be significantly narrower than the survey, or we have to allow for the averaging over evolving quantities. Both of these have the potential to remove signal: analysing small volumes increases the size of the Fourier window function, reducing the large-scale information, while averaging over evolving quantities can, if not performed carefully, remove differential information. It will be important to measure cosmological evolution from these surveys to explore and discriminate between models. We apply a method to optimally extract this differential information to mock catalogues designed to mimic the eBOSS quasar sample. By applying a set of weights to extract redshift space distortion measurements as a function of redshift, we demonstrate an analysis that does not invoke the problems discussed above. We show that our estimator gives unbiased constraints.

A 3D Voronoi+Gapper Galaxy Cluster Finder in Redshift Space to z ∼ 0.2. II. An Abundant Cluster Population Dominated by Late-type Galaxies Unveiled

Abstract We identify 1901 galaxy clusters (N g ≥ 2) with the VoML+G algorithm (Paper I) on the Two-Degree Field Galaxy Redshift Survey. We present the 341 clusters with at least 10 galaxies that are within 0.009 < z < 0.14 (the Catalog), of which 254 (∼75%) have counterparts in the literature (NED), with the remainder (87) plausibly “new” because of incompleteness of previous searches or unusual galaxy contents. The 207 clusters within z = 0.04–0.09 are used to study the properties of the galaxy systems in the nearby universe, including their galaxy contents parameterized by the late-type galaxy fractions (f L ). For this nearly complete cluster subsample, we find the following: (i) 63% are dominated by early-type galaxies (i.e., the late-type-poor clusters, f L < 0.5) with corresponding mean multiplicity and logarithmic virial mass (in units of M ⊙) of 22 ± 1 and 12.91 ± 0.04, respectively; and (ii) 37% are dominated by late-type galaxies (i.e., the late-type-rich clusters, f L ≥ 0.5) with corresponding mean multiplicity and logarithmic virial mass (in units of M ⊙) of 15.7 ± 0.9 and 12.66 ± 0.07, respectively. The statistical analysis of the late-type fraction distribution supports, with a 3σ confidence level, the presence of two population components. It is suggested that the late-type-poor galaxy systems reflect and extend the class of Abell-APM-EDCC clusters and that the late-type-rich systems (∼one-third of the total) belong to a new, previously unappreciated class. The late-type-rich clusters, on average high mass-to-light ratio systems, appear to be more clustered on large scales than the late-type-poor clusters. A class of late-type-rich clusters is not predicted by current theory.

TightH0 constraint from galaxy redshift surveys: combining baryon acoustic oscillation measurements and Alcock–Paczynski test with a CMB prior

We report a tight Hubble constant constraint $67.78^{+1.21}_{-1.86}$ km s$^{-1}$ Mpc$^{-1}$ (2.26\% precision) derived from galaxy redshift surveys. We combine the BAO measurements from 6dFGS, the SDSS DR7 main galaxies, the BOSS DR12 galaxies, and eBOSS DR14 quasars, and also apply the tomographic Alcock-Paczynski (AP) method to the BOSS DR12 galaxies, to place constraints on $H_0$ in the spatially flat $\Lambda$CDM framework. Our result is fully consistent with the CMB constraints from Planck, but in $2.58\sigma$ tension with local measurements of Riess et al. 2016. Compared with the BAO alone constraint, the BAO+AP combined result reduces the error bar by 32%. This shows the strong power of the tomographic AP method in extracting cosmological information from galaxy redshift surveys.

Dark matter halo properties versus local density and cosmic web location

We study the effects of the local environmental density and the cosmic web environment (filaments, walls, and voids) on key properties of dark matter halos using the Bolshoi-Planck LCDM cosmological simulation. The z = 0 simulation is analysed into filaments, walls, and voids using the SpineWeb method and also the VIDE package of tools, both of which use the watershed transform. The key halo properties that we study are the specific mass accretion rate, spin parameter, concentration, prolateness, scale factor of the last major merger, and scale factor when the halo had half of its z = 0 mass. For all these properties, we find that there is no discernible difference between the halo properties in filaments, walls, or voids when compared at the same environmental density. As a result, we conclude that environmental density is the core attribute that affects these properties. This conclusion is in line with recent findings that properties of galaxies in redshift surveys are independent of their cosmic web environment at the same environmental density at z ~ 0. We also find that the local web environment of the Milky Way and the Andromeda galaxies near the centre of a cosmic wall does not appear to have any effect on the properties of these galaxies' dark matter halos except for their orientation, although we find that it is rather rare to have such massive halos near the centre of a relatively small cosmic wall.

Forward modeling of spectroscopic galaxy surveys: application to SDSS

Galaxy spectra are essential to probe the spatial distribution of galaxies in our Universe. To better interpret current and future spectroscopic galaxy redshift surveys, it is important to be able to simulate these data sets. We describe USPEC, a forward modeling tool to generate galaxy spectra taking into account some intrinsic galaxy properties as well as instrumental responses of a given telescope. The model for the intrinsic properties of the galaxy population, i.e., the luminosity functions, and size and spectral coefficients distributions, was developed in an earlier work for broad-band imaging surveys [1], and we now aim to test the model further using spectroscopic data. We apply USPEC to the SDSS/CMASS sample of Luminous Red Galaxies (LRGs). We construct selection cuts that match those used to build this LRG sample, which we then apply to data and simulations in the same way. The resulting real and simulated average spectra show a good statistical agreement overall, with residual differences likely coming from a bluer galaxy population of the simulated sample. We also do not explore the impact of non-solar element ratios in our simulations. For a quantitative comparison, we perform Principal Component Analysis (PCA) of the sets of spectra. By comparing the PCs constructed from simulations and data, we find good agreement for all components. The distributions of the eigencoefficients also show an appreciable overlap. We are therefore able to properly simulate the LRG sample taking into account the SDSS/BOSS instrumental responses. The differences between the two samples can be ascribed to the intrinsic properties of the simulated galaxy population, which can be reduced by further improvements of our modeling method in the future. We discuss how these results can be useful for the forward modeling of upcoming large spectroscopic surveys.

Wide-field Optical Spectroscopy of Abell 133: A Search for Filaments Reported in X-Ray Observations

Abstract Filaments of the cosmic web have long been associated with the threadlike structures seen in galaxy redshift surveys. However, despite their baryon content being dominated by hot gas, these filaments have been an elusive target for X-ray observations. Recently, detections of filaments in very deep (2.4 Ms) observations with Chandra were reported around Abell 133 (z = 0.0559). To verify these claims, we conducted a multiobject spectrographic campaign on the Baade 6.5 m telescope around Abell 133; this resulted in a catalog of ∼3000 new redshift measurements, of which 254 are of galaxies near the cluster. We investigate the kinematic state of Abell 133 and identify the physical locations of filamentary structure in the galaxy distribution. Contrary to previous studies, we see no evidence that Abell 133 is dynamically disturbed; we reject the hypothesis that there is a kinematically distinct subgroup (p = 0.28) and find no velocity offset between the central galaxy and the cluster ( ). The spatial distribution of galaxies traces the X-ray filaments, as confirmed by angular cross-correlation with a significance of ∼5σ. A similar agreement is found in the angular density distribution, where two X-ray structures have corresponding galaxy enhancements. We also identify filaments in the large-scale structure of galaxies; these filaments approach the cluster from the direction the X-ray structures are seen. While more members between R 200 and 2 × R 200 are required to clarify which large-scale filaments connect to the X-ray gas, we argue that this is compelling evidence that the X-ray emission is indeed associated with cosmic filaments.

Redshift-space distortion from dynamical dark energy with time-dependent Lagrangian perturbation theory

We apply the Lagrangian perturbation theory with time-dependent growth functions at second and third order of perturbation with the aim to model the effect of dynamical dark energy on redshift-space distortions. Our fiducial galaxy redshift surveys are modeled after the upcoming SKA and DESI redshift surveys. We include PLANCK CMB priors and the 20\% uncertainty on the linear bias parameter, incorporating the unknown instrumentation noise. After the marginalizing, our results show that the constraints on the density parameter could potentially get better than $\sim$1\%, while the constraints on $w_0$ and $w_{\rm a}$ could be better than $\sim 5\%$ and $\sim 60\%$ respectively, consistent with works done before. However, the inclusion of time-dependent growth functions would alter the nonlinear power spectrum by as much as $\sim$10\%. The inclusion of the time-dependent growth functions become crucial as the precision gets better.

Measuring linear and non-linear galaxy bias using counts-in-cells in the Dark Energy Survey Science Verification data

Non-linear bias measurements require a great level of control of potential systematic effects in galaxy redshift surveys. Our goal is to demonstrate the viability of using Counts-in-Cells (CiC), a statistical measure of the galaxy distribution, as a competitive method to determine linear and higher-order galaxy bias and assess clustering systematics. We measure the galaxy bias by comparing the first four moments of the galaxy density distribution with those of the dark matter distribution. We use data from the MICE simulation to evaluate the performance of this method, and subsequently perform measurements on the public Science Verification (SV) data from the Dark Energy Survey (DES). We find that the linear bias obtained with CiC is consistent with measurements of the bias performed using galaxy-galaxy clustering, galaxy-galaxy lensing, CMB lensing, and shear+clustering measurements. Furthermore, we compute the projected (2D) non-linear bias using the expansion $\delta_{g} = \sum_{k=0}^{3} (b_{k}/k!) \delta^{k}$, finding a non-zero value for $b_2$ at the $3\sigma$ level. We also check a non-local bias model and show that the linear bias measurements are robust to the addition of new parameters. We compare our 2D results to the 3D prediction and find compatibility in the large scale regime ($>30$ Mpc $h^{-1}$)