Abstract
Building on the first paper in this series (Duncan et al. 2018), we present a study investigating the performance of Gaussian process photometric redshift (photo-z) estimates for galaxies ...and active galactic nuclei (AGNs) detected in deep radio continuum surveys. A Gaussian process redshift code is used to produce photo-z estimates targeting specific subsets of both the AGN population – infrared (IR), X-ray, and optically selected AGNs – and the general galaxy population. The new estimates for the AGN population are found to perform significantly better at z > 1 than the template-based photo-z estimates presented in our previous study. Our new photo-z estimates are then combined with template estimates through hierarchical Bayesian combination to produce a hybrid consensus estimate that outperforms both of the individual methods across all source types. Photo-z estimates for radio sources that are X-ray sources or optical/IR AGNs are significantly improved in comparison to previous template-only estimates – with outlier fractions and robust scatter reduced by up to a factor of ∼4. The ability of our method to combine the strengths of the two input photo-z techniques and the large improvements we observe illustrate its potential for enabling future exploitation of deep radio continuum surveys for both the study of galaxy and black hole coevolution and for cosmological studies.
In this paper, we describe the first data release of the Visible and Infrared Survey Telescope for Astronomy (VISTA) Deep Extragalactic Observations (VIDEO) survey. VIDEO is a ∼12 deg2 survey in the ...near-infrared Z, Y, J, H and K
s bands, specifically designed to enable the evolution of galaxies and large structures to be traced as a function of both epoch and environment from the present day out to z = 4, and active galactic nuclei (AGNs) and the most massive galaxies up to and into the epoch of reionization. With its depth and area, VIDEO will be able to fully explore the period in the Universe where AGN and starburst activity were at their peak and the first galaxy clusters were beginning to virialize. VIDEO therefore offers a unique data set with which to investigate the interplay between AGN, starbursts and environment, and the role of feedback at a time when it was potentially most crucial.
We provide data over the VIDEO-XMM3 tile, which also covers the Canada-France-Hawaii Telescope Legacy Survey Deep-1 field (CFHTLS-D1). The released VIDEO data reach a 5σ AB-magnitude depth of Z = 25.7, Y = 24.5, J = 24.4, H = 24.1 and K
s = 23.8 in 2 arcsec diameter apertures (the full depth of Y = 24.6 will be reached within the full integration time in future releases). The data are compared to previous surveys over this field and we find good astrometric agreement with the Two Micron All Sky Survey, and source counts in agreement with the recently released UltraVISTA survey data. The addition of the VIDEO data to the CFHTLS-D1 optical data increases the accuracy of photometric redshifts and significantly reduces the fraction of catastrophic outliers over the redshift range 0 < z < 1 from 5.8 to 3.1 per cent in the absence of an i-band luminosity prior. However, we expect that the main improvement in photometric redshifts will come in the redshift range 1 < z < 4 due to the sensitivity to the Balmer and 4000 Å breaks provided by the near-infrared VISTA filters. All images and catalogues presented in this paper are publicly available through ESO's phase 3 archive and the VISTA Science Archive.
The next generation of cosmology experiments will be required to use photometric redshifts rather than spectroscopic redshifts. Obtaining accurate and well-characterized photometric redshift ...distributions is therefore critical for Euclid, the Large Synoptic Survey Telescope and the Square Kilometre Array. However, determining accurate variance predictions alongside single point estimates is crucial, as they can be used to optimize the sample of galaxies for the specific experiment (e.g. weak lensing, baryon acoustic oscillations, supernovae), trading off between completeness and reliability in the galaxy sample. The various sources of uncertainty in measurements of the photometry and redshifts put a lower bound on the accuracy that any model can hope to achieve. The intrinsic uncertainty associated with estimates is often non-uniform and input-dependent, commonly known in statistics as heteroscedastic noise. However, existing approaches are susceptible to outliers and do not take into account variance induced by non-uniform data density and in most cases require manual tuning of many parameters. In this paper, we present a Bayesian machine learning approach that jointly optimizes the model with respect to both the predictive mean and variance we refer to as Gaussian processes for photometric redshifts (GPz). The predictive variance of the model takes into account both the variance due to data density and photometric noise. Using the Sloan Digital Sky Survey (SDSS) DR12 data, we show that our approach substantially outperforms other machine learning methods for photo-z estimation and their associated variance, such as tpz and annz2. We provide a matlab and python implementations that are available to download at https://github.com/OxfordML/GPz.
We propose a flexible method for estimating luminosity functions (LFs) based on kernel density estimation (KDE), the most popular nonparametric density estimation approach developed in modern ...statistics, to overcome issues surrounding the binning of LFs. One challenge in applying KDE to LFs is how to treat the boundary bias problem, as astronomical surveys usually obtain truncated samples predominantly due to the flux-density limits of surveys. We use two solutions, the transformation KDE method ( ) and the transformation-reflection KDE method ( ) to reduce the boundary bias. We develop a new likelihood cross-validation criterion for selecting optimal bandwidths, based on which the posterior probability distribution of the bandwidth and transformation parameters for and are derived within a Markov Chain Monte Carlo sampling procedure. The simulation result shows that and perform better than the traditional binning method, especially in the sparse data regime around the flux limit of a survey or at the bright end of the LF. To further improve the performance of our KDE methods, we develop the transformation-reflection adaptive KDE approach ( ). Monte Carlo simulations suggest that it has good stability and reliability in performance, and is around an order of magnitude more accurate than using the binning method. By applying our adaptive KDE method to a quasar sample, we find that it achieves estimates comparable to the rigorous determination in a previous work, while making far fewer assumptions about the LF. The KDE method we develop has the advantages of both parametric and nonparametric methods.
ABSTRACT
We examine the 1.4 GHz radio luminosities of galaxies arising from star formation and active galactic nuclei (AGNs) within the state-of-the-art cosmological hydrodynamic simulation Simba. ...Simba grows black holes via gravitational torque limited accretion from cold gas and Bondi accretion from hot gas, and employs AGN feedback including jets at low Eddington ratios. We define a population of radio loud AGNs (RLAGNs) based on the presence of ongoing jet feedback. Within RLAGN, we define high and low excitation radio galaxies (HERGs and LERGs) based on their dominant mode of black hole accretion: torque limited accretion representing feeding from a cold disc, or Bondi representing advection-dominated accretion from a hot medium. Simba predicts good agreement with the observed radio luminosity function (RLF) and its evolution, overall as well as separately for HERGs and LERGs. Quiescent galaxies with AGN-dominated radio flux dominate the RLF at $\gtrsim 10^{22-23}$ W Hz−1, while star formation dominates at lower radio powers. Overall, RLAGNs have higher black hole accretion rates and lower star formation rates than non-RLAGN at a given stellar mass or velocity dispersion, but have similar black hole masses. Simba predicts an LERG number density of 8.53 Mpc−3, ∼10× higher than for HERGs, broadly as observed. While LERGs dominate among most massive galaxies with the largest black holes and HERGs dominate at high specific star formation rates, they otherwise largely populate similar-sized dark matter haloes and have similar host galaxy properties. Simba thus predicts that deeper radio surveys will reveal an increasing overlap between the host galaxy demographics of HERGs and LERGs.
ABSTRACT
We measure the harmonic-space auto-power spectrum of the galaxy overdensity in the LOFAR Two-metre Sky Survey (LoTSS) first data release and its cross-correlation with the map of the lensing ...convergence of the cosmic microwave background (CMB) from the Planck collaboration. We report a ∼5σ detection of the cross-correlation. We show that the combination of the clustering power spectrum and CMB lensing cross-correlation allows us to place constraints on the high-redshift tail of the redshift distribution, one of the largest sources of uncertainty in the use of continuum surveys for cosmology. Our analysis shows a preference for a broader redshift tail than that predicted by the photometric redshifts contained in the LoTSS value-added catalogue, as expected, and more compatible with predictions from simulations and spectroscopic data. Although the ability of CMB lensing to constrain the width and tail of the redshift distribution could also be valuable for the analysis of current and future photometric weak lensing surveys, we show that its performance relies strongly on the redshift evolution of the galaxy bias. Assuming the redshift distribution predicted by the Square Kilometre Array Design simulations, we use our measurements to place constraints on the linear bias of radio galaxies and the amplitude of matter inhomogeneities σ8, finding $\sigma _8=0.69^{+0.14}_{-0.21}$ assuming the galaxy bias scales with the inverse of the linear growth factor, and $\sigma _8=0.79^{+0.17}_{-0.32}$ assuming a constant bias.
ABSTRACT
Tighter constraints on measurements of primordial non-Gaussianity (PNG) will allow the differentiation of inflationary scenarios. The cosmic microwave background bispectrum – the standard ...method of measuring the local non-Gaussianity – is limited by cosmic variance. Therefore, it is sensible to investigate measurements of non-Gaussianity using the large-scale structure. This can be done by investigating the effects of non-Gaussianity on the power spectrum on large scales. In this study, we forecast the constraints on the local PNG parameter fNL that can be obtained with future radio surveys. We utilize the multitracer method that reduces the effect of cosmic variance and takes advantage of the multiple radio galaxy populations that are differently biased tracers of the same underlying dark matter distribution. Improvements on previous work include the use of observational bias and halo mass estimates, updated simulations, and realistic photometric redshift expectations, thus producing more realistic forecasts. Combinations of Square Kilometre Array simulations and radio observations were used as well as different redshift ranges and redshift bin sizes. It was found that in the most realistic case the 1σ error on fNL falls within the range 4.07–6.58, rivalling the tightest constraints currently available.
Imaging surveys of galaxies will have a high number density and angular resolution yet a poor redshift precision. Intensity maps of neutral hydrogen will have accurate redshift resolution yet will ...not resolve individual sources. Using this complementarity, we show how the clustering redshifts approach proposed for spectroscopic surveys can also be used in combination with intensity mapping observations to calibrate the redshift distribution of galaxies in an imaging survey and, as a result, reduce uncertainties in photometric-redshift measurements. We show how the intensity mapping surveys to be carried out with the MeerKAT, HIRAX and SKA instruments can improve photometric-redshift uncertainties to well below the requirements of DES and LSST. The effectiveness of this method as a function of instrumental parameters, foreground subtraction and other potential systematic errors is discussed in detail.
Abstract
The next generation of large-scale imaging surveys (such as those conducted with the Large Synoptic Survey Telescope and Euclid) will require accurate photometric redshifts in order to ...optimally extract cosmological information. Gaussian Process for photometric redshift estimation (GPz) is a promising new method that has been proven to provide efficient, accurate photometric redshift estimations with reliable variance predictions. In this paper, we investigate a number of methods for improving the photometric redshift estimations obtained using GPz (but which are also applicable to others). We use spectroscopy from the Galaxy and Mass Assembly Data Release 2 with a limiting magnitude of r < 19.4 along with corresponding Sloan Digital Sky Survey visible (ugriz) photometry and the UKIRT Infrared Deep Sky Survey Large Area Survey near-IR (YJHK) photometry. We evaluate the effects of adding near-IR magnitudes and angular size as features for the training, validation, and testing of GPz and find that these improve the accuracy of the results by ∼15–20 per cent. In addition, we explore a post-processing method of shifting the probability distributions of the estimated redshifts based on their Quantile–Quantile plots and find that it improves the bias by ∼40 per cent. Finally, we investigate the effects of using more precise photometry obtained from the Hyper Suprime-Cam Subaru Strategic Program Data Release 1 and find that it produces significant improvements in accuracy, similar to the effect of including additional features.
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