Redshift Catalog Research Articles

The redshift-space two-point correlation function of ELAIS-S1 galaxies

We investigate the clustering properties of galaxies in the recently completed ELAIS-S1 redshift survey through their spatial two-point autocorrelation function. We used a subsample of the ELAIS-S1 catalogue covering approximately 4 deg2 and consisting of 148 objects selected at 15 μm with a flux >0.5 mJy and a redshift z < 0.5. We detected a positive signal in the correlation function that in the range of separations 1–10 h−1 Mpc is well approximated by a power law with a slope γ= 1.4 ± 0.25 and a correlation length s0= 5.4 ± 1.2 h−1 Mpc, at the 90 per cent significance level. This result is in good agreement with the redshift-space correlation function measured in more local samples of mid-infrared-selected galaxies such as the IRAS Point Source Catalog (PSCz) redshift survey. This suggests a lack of significant clustering evolution of infrared-selected objects out to z= 0.5 that is further confirmed by the consistency found between the correlation functions measured in a local (z < 0.2) and a distant (0.2 < z < 0.5) subsample of ELAIS-S1 galaxies. We also confirm that optically selected galaxies in the local redshift surveys, especially those of the SDSS sample, are significantly more clustered than infrared objects.

Calibrating photometric redshifts of luminous red galaxies

We discuss the construction of a photometric redshift catalogue of luminous red galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS), emphasizing the principal steps necessary for constructing such a catalogue: (i) photometrically selecting the sample, (ii) measuring photometric redshifts and their error distributions, and (iii) estimating the true redshift distribution. We compare two photometric redshift algorithms for these data and find that they give comparable results. Calibrating against the SDSS and SDSS–2dF (Two Degree Field) spectroscopic surveys, we find that the photometric redshift accuracy is σ∼ 0.03 for redshifts less than 0.55 and worsens at higher redshift (∼ 0.06 for z < 0.7). These errors are caused by photometric scatter, as well as systematic errors in the templates, filter curves and photometric zero-points. We also parametrize the photometric redshift error distribution with a sum of Gaussians and use this model to deconvolve the errors from the measured photometric redshift distribution to estimate the true redshift distribution. We pay special attention to the stability of this deconvolution, regularizing the method with a prior on the smoothness of the true redshift distribution. The methods that we develop are applicable to general photometric redshift surveys.

Detection of cosmic filaments using the Candy model

We propose to apply a marked point process to automatically delineate filaments of the large-scale structure in redshift catalogues. We illustrate the feasibility of the idea on an example of simulated catalogues, describe the procedure, and characterize the results. We find the distribution of the length of the filaments, and suggest how to use this approach to obtain other statistical characteristics of filamentary networks.

A Photometric Redshift Galaxy Catalog from the Red‐Sequence Cluster Survey

The Red-Sequence Cluster Survey (RCS) provides a large and deep photometric catalog of galaxies in the z' and Rc bands for 90 deg2 of sky, and supplemental V and B data have been obtained for 33.6 deg2. We compile a photometric redshift catalog from these four-band data by utilizing the empirical quadratic polynomial photometric redshift fitting technique in combination with CNOC2 and GOODS/HDF-N redshift data. The training set includes 4924 spectral redshifts. The resulting catalog contains more than one million galaxies with photometric redshifts <1.5 and Rc < 24, giving an rms scatter σ(Δz) < 0.06 within the redshift range 0.2 < z < 0.5 and σ(Δz) < 0.11 for galaxies at 0.0 < z < 1.5. We describe the empirical quadratic polynomial photometric redshift fitting technique that we use to determine the relation between redshift and photometry. A kd-tree algorithm is used to divide up our sample to improve the accuracy of our catalog. We also present a method for estimating the photometric redshift error for individual galaxies. We show that the redshift distribution of our sample is in excellent agreement with smaller and much deeper photometric and spectroscopic redshift surveys.

The DEEP Groth Strip Galaxy Redshift Survey. III. Redshift Catalog and Properties of Galaxies

The Deep Extragalactic Evolutionary Probe (DEEP) is a series of spectroscopic surveys of faint galaxies, targeted at the properties and clustering of galaxies at redshifts z ~ 1. We present the redshift catalog of the DEEP 1 GSS pilot phase of this project, a Keck/LRIS survey in the HST/WFPC2 Groth Survey Strip. The redshift catalog and data, including reduced spectra, are publicly available through a Web-accessible database. The catalog contains 658 secure galaxy redshifts with a median z=0.65, and shows large-scale structure walls to z = 1. We find a bimodal distribution in the galaxy color-magnitude diagram which persists to z = 1. A similar color division has been seen locally by the SDSS and to z ~ 1 by COMBO-17. For red galaxies, we find a reddening of only 0.11 mag from z ~ 0.8 to now, about half the color evolution measured by COMBO-17. We measure structural properties of the galaxies from the HST imaging, and find that the color division corresponds generally to a structural division. Most red galaxies, ~ 75%, are centrally concentrated, with a red bulge or spheroid, while blue galaxies usually have exponential profiles. However, there are two subclasses of red galaxies that are not bulge-dominated: edge-on disks and a second category which we term diffuse red galaxies (DIFRGs). The distant edge-on disks are similar in appearance and frequency to those at low redshift, but analogs of DIFRGs are rare among local red galaxies. DIFRGs have significant emission lines, indicating that they are reddened mainly by dust rather than age. The DIFRGs in our sample are all at z>0.64, suggesting that DIFRGs are more prevalent at high redshifts; they may be related to the dusty or irregular extremely red objects (EROs) beyond z>1.2 that have been found in deep K-selected surveys. (abridged)

New York University Value-Added Galaxy Catalog: A Galaxy Catalog Based on New Public Surveys

Here we present the New York University Value-Added Galaxy Catalog (NYU-VAGC), a catalog of local galaxies (mostly below z ≈ 0.3) based on a set of publicly released surveys matched to the Sloan Digital Sky Survey (SDSS) Data Release 2. The photometric catalog consists of 693,319 galaxies, QSOs, and stars; 343,568 of these have redshift determinations, mostly from the SDSS. Excluding areas masked by bright stars, the photometric sample covers 3514 deg2, and the spectroscopic sample covers 2627 deg2 (with about 85% completeness). Earlier, proprietary versions of this catalog have formed the basis of many SDSS investigations of the power spectrum, correlation function, and luminosity function of galaxies. Future releases will follow future public releases of the SDSS. The catalog includes matches to the Two Micron All Sky Survey Point Source Catalog and Extended Source Catalog, the IRAS Point Source Catalog Redshift Survey, the Two-Degree Field Galaxy Redshift Survey, the Third Reference Catalogue of Bright Galaxies, and the Faint Images of the Radio Sky at Twenty cm survey. We calculate and compile derived quantities from the images and spectra of the galaxies in the catalogs (for example, K-corrections and structural parameters for the galaxies). The SDSS catalog presented here is photometrically calibrated in a more consistent way than that distributed by the SDSS Data Release 2 Archive Servers and is thus more appropriate for large-scale structure statistics, reducing systematic calibration errors across the sky from ~2% to ~1%. We include an explicit description of the geometry of the catalog, including all imaging and targeting information as a function of sky position. Finally, we have performed eyeball quality checks on a large number of objects in the catalog in order to flag errors (such as errors in deblending). This catalog is complementary to the SDSS Archive Servers in that NYU-VAGC's calibration, geometric description, and conveniently small size are specifically designed for studying galaxy properties and large-scale structure statistics using the SDSS spectroscopic catalog.

Photometric redshifts with the Multilayer Perceptron Neural Network: Application to the HDF-S and SDSS

We present a technique for the estimation of photometric redshifts based on feed-forward neural networks. The Multilayer Perceptron (MLP) Artificial Neural Network is used to predict photometric redshifts in the HDF-S from an ultra deep multicolor catalog. Various possible approaches for the training of the neural network are explored, including the deepest and most complete spectroscopic redshift catalog currently available (the Hubble Deep Field North dataset) and models of the spectral energy distribution of galaxies available in the literature. The MLP can be trained on observed data, theoretical data and mixed samples. The prediction of the method is tested on the spectroscopic sample in the HDF-S (44 galaxies). Over the entire redshift range, $0.1

ImpZ: a new photometric redshift code for galaxies and quasars

We present a combined galaxy-quasar approach to template-fitting photometric redshift techniques and show the method to be a powerful one. The code (ImpZ) is presented, developed and applied to two spectroscopic redshift catalogues, namely the Isaac Newton Telescope Wide Angle Survey ELAIS N1 and N2 fields and the Chandra Deep Field North. In particular, optical size information is used to improve the redshift determination. The success of the code is shown to be very good with Delta z/(1+z) constrained to within 0.1 for 92 per cent of the galaxies in our sample. The extension of template-fitting to quasars is found to be reasonable with Delta z/(1+z) constrained to within 0.25 for 68 per cent of the quasars in our sample. Various template extensions into the far-UV are also tested.

Photometric redshifts with the Multilayer Perceptron Neural Network: Application to the HDF-S and SDSS

We present a technique for the estimation of photometric redshifts based on feed-forward neural networks. The Multilayer Perceptron (MLP) Artificial Neural Network is used to predict photometric redshifts in the HDF-S from an ultra deep multicolor catalog. Various possible approaches for the training of the neural network are explored, including the deepest and most complete spectroscopic redshift catalog currently available (the Hubble Deep Field North dataset) and models of the spectral energy distribution of galaxies available in the literature. The MLP can be trained on observed data, theoretical data and mixed samples. The prediction of the method is tested on the spectroscopic sample in the HDF-S (44 galaxies). Over the entire redshift range, $0.1<z<3.5$, the agreement between the photometric and spectroscopic redshifts in the HDF-S is good: the training on mixed data produces sigma_z(test) ~ 0.11, showing that model libraries together with observed data provide a sufficiently complete description of the galaxy population. The neural system capability is also tested in a low redshift regime, 0<z<0.4, using the Sloan Digital Sky Survey Data Release One (DR1) spectroscopic sample. The resulting accuracy on 88108 galaxies is sigma_z(test) ~ 0.022. Inputs other than galaxy colors - such as morphology, angular size and surface brightness - may be easily incorporated in the neural network technique. An important feature, in view of the application of the technique to large databases, is the computational speed: in the evaluation phase, redshifts of 10^5 galaxies are estimated in few seconds.

Streaming motions of galaxy clusters within 12 000 km s−1- V. The peculiar velocity field

We analyse in detail the peculiar velocity field traced by 56 clusters within 120 h−1 Mpc in the ‘Streaming Motions of Abell Clusters’ (SMAC) sample. The bulk flow of the SMAC sample is 687 ± 203 km s−1, toward l= 260°± 13°, b= 0°± 11°. We discuss possible systematic errors and show that no systematic effect is larger than half of the random error. The flow does not drop off significantly with depth, which suggests that it is generated by structures on large scales. In particular, a Great Attractor as originally proposed by Lynden-Bell et al. cannot be responsible for the SMAC bulk flow. The SMAC data suggest infall into an attractor at the location of the Shapley Concentration, but the detection is marginal (at the 90 per cent confidence level). We find that distant attractors in addition to the Shapley Concentration are required to explain the SMAC bulk flow. A comparison with peculiar velocities predicted from the IRAS Point Source Catalogue redshift (PSCz) survey shows good agreement with a best-fitting value of βI=Ω0.6m/bI= 0.39 ± 0.17. However, the PSCz density field is not sufficient to account for all of the SMAC bulk motion. We also detect, at the 98 per cent confidence level, a residual bulk flow of 372 ± 127 km s−1 toward l= 273°, b= 6° which must be generated by sources not included in the PSCz catalogue, that is, either beyond 200 h−1 Mpc, in the zone of avoidance or in superclusters undersampled by IRAS. Finally, we compare the SMAC bulk flow with other recent measurements. We argue that, at depths ranging from 60 to 120 h−1 Mpc, flows of order 600 km s−1 are excluded by multiple data sets. However, convergence to the cosmic microwave background frame by a depth of 60 h−1 Mpc is also excluded by multiple data sets. We suggest that a bulk flow of 225 km s−1 toward l= 300°, b= 10° at depths greater than 60 h−1 Mpc is consistent with all peculiar velocity surveys, when allowance is made for sparse sampling effects.

The Team Keck Treasury Redshift Survey of the GOODS-North Field

We report the results of an extensive imaging and spectroscopic survey in the Great Observatories Origins Deep Survey (GOODS)-North field completed using DEIMOS on the Keck II telescope. Observations of 2018 targets in a magnitude-limited sample of 2911 objects to RAB = 24.4 yield secure redshifts for a sample of 1440 galaxies and active galactic nuclei (AGNs) plus 96 stars. In addition to redshifts and associated quality assessments, our catalog also includes photometric and astrometric measurements for all targets detected in our R-band imaging survey of the GOODS-North region. We investigate various sources of incompleteness and find the redshift catalog to be 53% complete at its limiting magnitude. The median redshift of z = 0.65 is lower than in similar deep surveys because we did not select against low-redshift targets. Comparison with other redshift surveys in the same field, including a complementary Hawaii-led DEIMOS survey, establishes that our velocity uncertainties are as low as σ ≈ 40 km s-1 for red galaxies and that our redshift confidence assessments are accurate. The distributions of rest-frame magnitudes and colors among the sample agree well with model predictions out to and beyond z = 1. We will release all survey data, including extracted one-dimensional and sky-subtracted two-dimensional spectra, thus providing a sizable and homogeneous database for the GOODS-North field, which will enable studies of large-scale structure, spectral indices, internal galaxy kinematics, and the predictive capabilities of photometric redshifts.

Mock Catalogs for the DEEP2 redshift survey

We present a set of mock redshift catalogs, constructed from N-body simulations, designed to mimic the DEEP2 survey. Galaxies with a range of luminosities are placed within virialized halos in the simulation using a variant of the halo model. The halo model parameters are chosen to reproduce local clustering and abundance data and assumed to be independent of redshift. This allows us to predict the luminosity function, two-point correlation function, luminosity- and scale-dependent bias, redshift space distortions etc. of our galaxies at higher redshifts. We show that the low order clustering properties are consistent with preliminary DEEP2 data. The catalogs can be used to evaluate the selection effects of the survey and to test new algorithms and statistics that are to be used in the analysis of DEEP2 data.

The three-dimensional power spectrum of dark and luminous matter from the VIRMOS-DESCART cosmic shear survey

We present the first optimal power spectrum estimation and three dimensional deprojections for the dark and luminous matter and their cross correlations. The results are obtained using a new optimal fast estimator (Pen 2003) deprojected using minimum variance and SVD techniques. We show the resulting 3-D power spectra for dark matter and galaxies, and their covariance for the VIRMOS-DESCART weak lensing shear and galaxy data. The survey is most sensitive to nonlinear scales k_NL ~ 1 h Mpc^-1. On these scales, our 3-D power spectrum of dark matter is in good agreement with the RCS 3-D power spectrum found by (Hoekstra et al 2002). Our galaxy power is similar to that found by the 2MASS survey, and larger than that of SDSS, APM and RCS, consistent with the expected difference in galaxy population. We find an average bias b=1.24+/-0.18 for the I selected galaxies, and a cross correlation coefficient r=0.75+/-0.23. Together with the power spectra, these results optimally encode the entire two point information about dark matter and galaxies, including galaxy-galaxy lensing. We address some of the implications regarding galaxy halos and mass-to-light ratios. The best fit ``halo'' parameter h=r/b=0.57+/-0.16, suggesting that dynamical masses estimated using galaxies systematically underestimate total mass. Ongoing surveys, such as the Canada-France-Hawaii-Telescope-Legacy survey will significantly improve on the dynamic range, and future photometric redshift catalogs will allow tomography along the same principles.

On the angular correlation function of SZ clusters: Extracting cosmological information from a 2D catalog

We discuss the angular correlation function of Sunyaev-Zel'dovich (SZ)-detected galaxy clusters as a cosmological probe. As a projection of the real-space cluster correlation function, the angular function samples the underlying SZ catalog redshift distribution. It offers a way to study cosmology and cluster evolution directly with the two-dimensional catalog, even before extensive follow-up observations, thereby facilitating the immediate scientific return from SZ surveys. As a simple illustration of the information content of the angular function, we examine its dependence on the parameter pair Om_m, sigma_8 in flat cosmologies. We discuss sources of modeling uncertainty and consider application to the future Planck SZ catalog, showing how these two parameters and the normalization of the SZ flux-mass relation can be simultaneously found when the local X-ray cluster abundance constraint is included.

Spatial and Dynamical Biases in Velocity Statistics of Galaxies

We present velocity statistics of galaxies and their biases inferred from the statistics of the underlying dark matter using a cosmological hydrodynamic simulation of galaxy formation in low-density and spatially flat (Ohm(0) = 0.3 and lambda(0) = 0.7) cold dark matter cosmogony. Our simulation is based on a particle-particle-particle-mesh ((PM)-M-3) N-body Poisson solver and smoothed particle hydrodynamics. Galaxies in our simulation are identified as clumps of cold and dense gas particles and classified as young and old galaxies according to their formation epochs. We find that the pairwise velocity dispersion (PVD) of all galaxies is significantly lower than that of the dark matter particles and that the PVD of the young galaxies is lower than that of the old types, and even of all galaxies together, especially at small separations. These results are in reasonable agreement with the recent measurements of PVDs in the Las Campanas redshift survey, the IRAS Point Source Catalogue Redshift Survey, and the Sloan Digital Sky Survey data. We also find that the low PVD of young galaxies is due to the effects of dynamical friction as well as the different spatial distribution, while the difference in the PVD between all galaxies and dark matter can be mostly ascribed to their different spatial distributions. We also consider the mean infall velocity and the POTENT density reconstruction that are often used to measure the cosmological parameters, and investigate the effects of spatial bias and dynamical friction. In our simulation, the mean infall velocity of young galaxies is significantly lower than that of all the galaxies or of the old galaxies, and the dynamical bias becomes important on scales less than 3 h(-1) Mpc. The mass density field reconstructed from the velocity field of young galaxies using the POTENT-style method suffers in accuracy from both the spatial bias and the dynamical friction on the smoothing scale of R-s = 8 h(-1) Mpc. On the other hand, in the case of R-s = 12 h(-1) Mpc, which is typically adopted in the actual POTENT analysis, the density reconstruction based on various tracers of galaxies is reasonably accurate. We also analyze the motions of central galaxies and the velocity dispersion of galaxies within halos and discuss their implications for the motion of cD galaxies and the determination of the mass of galaxy groups.

Correlations of Richness and Global Properties in Galaxy Clusters

Richness is a key defining characteristic of a galaxy cluster. We measure the optical richness of galaxy clusters from the Canadian Network for Observational Cosmology Cluster Redshift Survey using the galaxy cluster center correlation amplitude Bgc. We show that the Bgc values measured using photometric catalogs are consistent with those derived from redshift catalogs, indicating that richness can be measured reliably from photometric data alone, even at moderate redshifts of ~0.6. We establish the correlations between optical richness and other important attributes of a galaxy cluster, such as velocity dispersion, mass, radius, and X-ray temperature and luminosity. We find that the scaling relations of these quantities with richness are entirely consistent with those derived by assuming a simple mass density profile at 0.5 h Mpc of ρ ~ r-1.8. The excellent correlations between Bgc and velocity dispersion and X-ray temperature allow one to use richness, an easily measurable quantity using relatively shallow optical imaging data alone, as a predictor of these quantities at moderate redshifts. The Bgc parameter can be used to estimate the velocity dispersion of a cluster to a precision of approximately 15% (~±100 km s-1) and X-ray temperature to about 20%. Similar correlations, but with larger scatter, are also obtained between richness and the characteristic radius and mass of the clusters. We compare the relative merits of Bgc, TX, and LX as predictors of the dynamical mass and find that they are comparable, providing estimates at an accuracy of ~30%. We also perform similar analyses of correlations between richness and velocity dispersion, TX, and LX with a sample of low-redshift Abell clusters and find consistent results, but with larger scatter, which may be the result of a less homogeneous database or sample-dependent effects.

The Search for Intergalactic Hydrogen Clouds in Voids

I present the results of a search for intergalactic hydrogen clouds in voids. Clouds are detected by their HI LyA absorption lines in the HST spectra of low-redshift AGN. The parameter with which the environments of clouds are characterized is the tidal field, which places a lower limit on the cloud mass-density which is dynamically stable against disruption. Galaxy redshift catalogs are used to sum the tidal fields along the lines of sight, sorting clouds according to tidal field upper, or lower limits. The analytical methodology employed is designed to detect gas clouds whose expansion following reionization is restrained by dark matter perturbations. End-products are the cloud equivalent width distribution functions (EWDF) of catalogs formed by sorting clouds according to various tidal field upper, or lower limits. Cumulative EWDFs are steep in voids (S ~ -1.5 \pm 0.2), but flatter in high tidal field zones (S ~ -0.5 \pm 0.1). Most probable cloud Doppler parameters are ~30 km/s in voids and ~60 km/s in proximity to galaxies. In voids, the cumulative line density at low EW (~ 15 mA) is ~ 500 per unit redshift. The void filling factor is found to be 0.87 <= f_v <= 0.94. The void EWDF is remarkably uniform over this volume, with a possible tendency for more massive clouds to be in void centers. The size and nature of the void cloud population suggested by this study is completely unanticipated by the results of published 3-D simulations, which predict that most clouds are in filamentary structures around galaxy concentrations, and that very few observable absorbers would lie in voids. Strategies for modeling this population are briefly discussed.

Caltech Faint Galaxy Redshift Survey. XVI. The Luminosity Function for Galaxies in the Region of the Hubble Deep Field–North toz = 1.5

We have carried out a study of the luminosity function (LF) of galaxies in the region of the Hubble Deep Field-North using our very complete redshift catalog. We divide the sample into five redshift bins covering the range 0.01 < z < 1.5 and consider three primary galaxy spectral classes. We solve for the LF at four rest-frame wavelengths from 0.24 to 2.2 μm. We find that the LFs for quiescent galaxies have shallow faint-end slopes while those of galaxies with detectable emission lines have steeper faint-end slopes. Furthermore, these slopes appear to be independent of redshift out to z = 1.05 for each galaxy spectral grouping and agree well with comparable local determinations. We then fix α to obtain values of L* for each galaxy spectral grouping as a function of redshift. We find that galaxies with strong absorption lines become brighter with z with Q ~ 0.6 at all rest-frame bands studied here, where Q = Δ log /Δz, while galaxies with detectable emission lines (i.e., star-forming galaxies) show a smaller change in L* with redshift at all bands, Q ~ 0.3, with Q becoming significantly larger at rest-frame 2400 A. Passive evolution models of galaxies are in reasonable agreement with these results for absorption-line-dominated galaxies, while plausible star formation histories can reproduce the behavior of the emission-line galaxies. We find a constant comoving number density and stellar mass in galaxies out to z ~ 1.05. By stretching all the correction factors applied to the galaxy counts in the highest redshift bin to their maximum possible values, we can just barely achieve this between z = 1.05 and 1.3. The major epoch(s) of star formation and of galaxy formation must have occurred even earlier. The UV luminosity density, an indicator of the star formation rate, has increased by a factor of ~4 over the period z = 0-1.

The real-space power spectrum of the PSCzsurvey from 0.01 to 300 h Mpc−1

We report a measurement of the real-space (not redshift-space) power spectrum of galaxies over four and a half decades of wavenumber, 0.01 to 300 h Mpc - 1 , from the IRAS Point Source Catalog Redshift Survey (PSCz). Sinceestimates of power are highly correlated in the non-linear regime, we also report results for the pre-whitened power spectrum, which is less correlated. The inferred bias between optically selected APM and IRAS-selected PSCz galaxies is about 1.15 at linear scales ≤0.3 h Mpc - 1 , increasing to about 1.4 at non-linear scales ≥1 h Mpc - 1 . The non-linear power spectrum of PSCz shows a near power-law behaviour to the smallest scales measured, with possible mild upward curvature in the broad vicinity of k 2 h Mpc - 1 . Contrary to the prediction of unbiased dark matter models, there is no prominent inflection at the linear to non-linear transition scale, and no turnover at the transition to the virialized regime. The non-linear power spectrum of PSCz requires scale-dependent bias: all Dark Matter models without scale-dependent bias are ruled out with high confidence.

Voids in the Point Source Catalogue Survey and the Updated Zwicky Catalog

We describe an algorithm to detect voids in galaxy redshift surveys. The method is based on the void finder algorithm of El-Ad & Piran. We apply a series of tests to determine how accurately we are able to recover the volumes of voids using our detection method. We simulate voids of different ellipticity and find that if voids are approximately spherical, our algorithm will recover 100% of the volume of the void. The more elliptical the void, the smaller the fraction of the volume we can recover. We insist that voids lie completely within the survey. Voids close to the edge of the survey will therefore be underestimated in volume. By considering a deeper sample, we estimate that the maximal sphere diameters are correct to within 30%. We apply the algorithm to the Point Source Catalog redshift (PSCz) survey and the Updated Zwicky Catalog (UZC). The PSCz survey is an almost all-sky survey with objects selected from the IRAS catalog. The UZC covers a smaller area of sky but is optically selected and samples the structures more densely. We detect 35 voids in the PSCz and 19 voids in the UZC with diameter larger than 20 h-1 Mpc. Using this minimum size threshold, we find that voids have an average effective diameter of 29.8 ± 3.5 h-1 Mpc (PSCz) and 29.2 ± 2.7 h-1 Mpc (UZC) and that they are underdense regions with δρ/ρ values of -0.92 ± 0.03 (PSCz) and -0.96 ± 0.01 (UZC), respectively. Using this quite stringent threshold for void definition, voids fill up to 40% of the volume of the universe.