Calibrating Redshift Distributions beyond Spectroscopic Limits with Cross-Correlations

By J. Newman. 2008

226 citations recorded by the source corpus.

We describe a new method that can measure the true redshift distribution of any set of objects that are studied only photometrically. Measuring the angular cross-correlation between objects in the photometric sample with objects in some spectroscopic sample as a function of the spectroscopic z, along with other, standard correlation measurements, provides sufficient information to reconstruct the redshift distribution of the photometric sample. The spectroscopic sample need not resemble the photometric sample in galaxy properties, but must fall within its sky coverage. We test this hybrid, photometric-spectroscopic cross-correlation technique with Monte Carlo simulations based on realistic error estimates (including sample variance). The rms errors in recovering both the mean redshift and σ of the redshift distribution for a single photometric redshift bin with true distribution given by a Gaussian are 1.4 × 10−3(σz/0.1)(Σp/10)−0.3(dNs/dz/25,000)−1/2, where σz is the true Gaussian σ , Σp is the surface density of the photometric sample in galaxies arcmin −2, and dNs/dz is the number of galaxies with a spectroscopic redshift per unit z. We test the impact of non-Gaussian redshift outliers and of systematic errors due to unaccounted-for bias evolution, errors in measuring autocorrelations, photometric zero-point variations, or mistaken cosmological assumptions, and find that none will dominate measurement uncertainties in reasonable scenarios. The true redshift distributions of even arbitrarily faint photometric samples may be determined to the precision required by proposed dark energy experiments (Δ⟨z⟩ ≲ 3 × 10−3 at z ∼ 1) with this method.

Subfields: Astronomy and Astrophysics, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/8951c62b5810a58b64b42a72a00637da40d22f0a

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Citations in the corpus

KiDS-450: cosmological parameter constraints from tomographic weak gravitational lensing (2016, methodology): “(ii) CC: an angular cross-correlation-based calibration (Newman 2008) with some of the same spectroscopic catalogues.”
The DESI Experiment Part I: Science,Targeting, and Survey Design (2016, unknown): “For instance, cross correlation of photometric lensing sources with spectroscopic galaxy samples enable the reconstruction of the redshift distribution of the lensing sources [179, 171, 180, 181] providing a critical consistency test on the photometric redshifts used for cosmic shear and/or calibrat”
Cosmological constraints from cosmic shear two-point correlation functions with HSC survey first-year data (2019, methodology): “A possible method to calibrate the photo-z without relying on COSMOS 30- band photo-z is a cross-correlation method (Newman 2008) which we will adopt in a future work.”
THE SDSS-IV EXTENDED BARYON OSCILLATION SPECTROSCOPIC SURVEY: OVERVIEW AND EARLY DATA (2015, methodology): “Spectroscopy from eBOSS offers an alternative approach to photometric redshift calibration through cross-correlation techniques (Newman 2008; Ménard et al. 2013).”
Simultaneous measurement of cosmology and intrinsic alignments using joint cosmic shear and galaxy number density correlations (2009, background): “It may also be possible to infer some additional information frm the cosmic shear data itself (Newman 2008; Schneider et al. 2006; Zhang et al. 2010).”
The first-year shear catalog of the Subaru Hyper Suprime-Cam Subaru Strategic Program Survey (2017, methodology): “…error budget, it will be important to have spectroscopic training samples with better coverage of the faint end of our galaxy sample, and use complementary methods such as clustering redshifts (Newman 2008; Rahman et al. 2015) that benefit from having wider survey areas, as discussed in section 8.”
Gravitational lensing analysis of the Kilo-Degree Survey (2015, methodology): “As a further test of our photometric redshifts, following Newman (2008) we calculate the angular cross-correlation of the positions of GAMA and KiDS galaxies on the sky, grouped by spectroscopic (GAMA) and photometric (KiDS) redshifts.”
LSST: From Science Drivers to Reference Design and Anticipated Data Products (2008, background): “It will be possible to further improve photometric redshift calibration by cross-correlating the photometric sample with redshift surveys of galaxies and quasars in the same fields (Newman 2008; Matthews & Newman 2010; Menard et al. 2013).”
The Intrinsic Alignment of Galaxies and its Impact on Weak Gravitational Lensing in an Era of Precision Cosmology (2014, unknown): “…(1995); Benitez (2000); Budavári et al. (2000); Collister and Lahav (2004); Vanzella et al. (2004); Ilbert et al. (2006); Schneider et al. (2006a); Newman (2008); Bernstein and Huterer (2010); Zhang et al. (2010); Sheldon et al. (2012); Wittman and Dawson (2012); McQuinn and White (2013); de…”
Wide-Field InfrarRed Survey Telescope-Astrophysics Focused Telescope Assets WFIRST-AFTA 2015 Report (2015, methodology): “Photometric redshift uncertainties can be well constrained by combining WFIRST-AFTA and LSST data, to get deep 10band photometry and good morphological information for all galaxies in the joint sample, to calibrate photo-z distributions via clustering cross-correlation with the imaging catalog (Newm”
Dark Energy Survey Year 1 Results: The Photometric Data Set for Cosmology (2017, methodology): “A second, independent indirect validation technique relies on the clustering-redshift technique (Newman 2008; Ménard et al. 2013; Schmidt et al. 2013).”
KiDS-1000 Cosmology: Multi-probe weak gravitational lensing and spectroscopic galaxy clustering constraints (2020, methodology): “This would allow for the optimal combination of information from the clustering cross-correlation of spectroscopic and photometric galaxies (Newman 2008), an observable that we currently only use as an independent tool to validate our photometric redshift calibration (Hildebrandt et al. 2020b).”
KiDS+VIKING-450: Cosmic shear tomography with optical and infrared data (2018, methodology): “This method, originally proposed by Schneider et al. (2006) and Newman (2008) and refined in many follow-up papers (Matthews & Newman 2010; Ménard et al. 2013; Schmidt et al. 2013; McQuinn & White 2013; Morrison et al. 2017), makes very different assumptions to the DIR method.”
KiDS+VIKING-450 and DES-Y1 combined: Cosmology with cosmic shear (2019, background): “We note that the greater depth of HSC (but also future surveys such as LSST) complicates a direct spectroscopic calibration of the redshift distributions and may instead require other approaches such as the cross-correlation between photometric and spectroscopic galaxies (Newman 2008).”
CFHTLenS: Improving the quality of photometric redshifts with precision photometry (2011, methodology): “There are several methods discussed in the literature to correct these redshift probability densities (e.g. Newman 2008; Benjamin et al. 2010) to make them more realistic using angular cross-correlation functions between different 12 It should be noted that the stacked posterior probabilities are…”
DESI and other Dark Energy experiments in the era of neutrino mass measurements (2013, unknown): “, calibrating photo-z systematics [129], or intrinsic alignments, or shear calibration errors [197].”