Spectroscopic needs for imaging dark energy experiments

Abstract

Ongoing and near-future imaging-based dark energy experiments are critically dependent upon photometric redshifts (a.k.a. photo-z's): i.e., estimates of the redshifts of objects based only on flux information obtained through broad filters. Higher-quality, lower-scatter photo-z's will result in smaller random errors on cosmological parameters; while systematic errors in photometric redshift estimates, if not constrained, may dominate all other uncertainties from these experiments. The desired optimization and calibration is dependent upon spectroscopic measurements for secure redshift information; this is the key application of galaxy spectroscopy for imaging-based dark energy experiments.Hence, to achieve their full potential, imaging-based experiments will require large sets of objects with spectroscopically-determined redshifts, for two purposes:• Training: Objects with known redshift are needed to map out the relationship between object color and z (or, equivalently, to determine empirically-calibrated templates describing the restframe spectra of the full range of galaxies, which may be used to predict the color-z relation). The ultimate goal of training is to minimize each moment of the distribution of differences between photometric redshift estimates and the true redshifts of objects, making the relationship between them as tight as possible. The larger and more complete our "training set" of spectroscopic redshifts is, the smaller the RMS photo-z errors should be, increasing the constraining power of imaging experiments.Requirements: Spectroscopic redshift measurements for ∼30,000 objects over >∼15 widelyseparated regions, each at least ∼20 arcmin in diameter, and reaching the faintest objects used in a given experiment, will likely be necessary if photometric redshifts are to be trained and calibrated with conventional techniques. Larger, more complete samples (i.e., with longer exposure times) can improve photo-z algorithms and reduce scatter further, enhancing the science return from planned experiments greatly (increasing the Dark Energy Task Force figure of merit by up to ∼50%).

Scientific Synergy between LSST and Euclid

“…The planned C3R2 sample is comparable in size, and the cosmic variance across six distinct 1 deg 2 fields (as envisioned for C3R2) would be comparable to that from the fifteen 0.1 deg 2 fields established as the LSST requirement in Newman et al (2015). Therefore, C3R2 should be sufficient for both surveys.…”

“…The alternative is to measure the angular crosscorrelations between the photometric samples and large, widearea spectroscopic surveys. The true redshift distribution for the photometric sample is then reconstructed from this crosscorrelation (Newman et al 2015;Rahman et al 2015). The requirements on the spectroscopic samples needed by both LSST and Euclid will be similar because of their overlap in area, redshift range, survey depth and calibration accuracy required.…”

“…Based on previous studies, Newman et al (2015) estimate that ∼20,000 spectra in total would be needed to calibrate the LSST color-redshift relation down to the LSST weak-lensing imaging depth. The planned C3R2 sample is comparable in size, and the cosmic variance across six distinct 1 deg 2 fields (as envisioned for C3R2) would be comparable to that from the fifteen 0.1 deg 2 fields established as the LSST requirement in Newman et al (2015).…”

“…As described in Newman et al (2015), LSST calibration using this technique will require at minimum 100,000 objects distributed over multiple widely separated fields of several hundred square degrees, spanning the full redshift range of the weak-lensing samples used for dark energy analyses. Euclid requirements have been estimated to be 0.4 galaxies deg −2 per D = z 0.05 bin for < < z 0 6 over an area of at least 2000 deg 2 , corresponding to 96,000 galaxies.…”

Probing the sparse tails of redshift distributions with Voronoi tessellations

“…This is an ill-posed problem since in general there is a distribution of redshift that can result in consistent color measurements; however, it is this redshift distribution that is the key to unlock the statistical power of photometric surveys (Newman et al, 2015). The accurate estimation of redshift distributions is an essential step of the analysis of photometric surveys and is necessary to extract cosmological measurements of the baryon acoustic scale, the growth rate of structure through redshift-space distortions as well as the signal encoded in the lensed shape correlations (Mandelbaum et al, 2008;Myers et al, 2009;Wittman, 2009;Asorey et al, 2016).…”