Spectroscopic failures in photometric redshift calibration: cosmological biases and survey requirements
| Autor: | Dragan Huterer, M. T. Busha, Risa H. Wechsler, Carlos E. Cunha, Huan Lin |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: |
Physics
Cosmology and Nongalactic Astrophysics (astro-ph.CO) Estimation theory Estimator Astronomy FOS: Physical sciences Astronomy and Astrophysics Astrophysics Astrophysics::Cosmology and Extragalactic Astrophysics Photometry (optics) Space and Planetary Science Dark energy Astrophysics::Solar and Stellar Astrophysics Spectroscopy Astrophysics - Instrumentation and Methods for Astrophysics Spectrograph Instrumentation and Methods for Astrophysics (astro-ph.IM) Weak gravitational lensing Astrophysics::Galaxy Astrophysics Photometric redshift Astrophysics - Cosmology and Nongalactic Astrophysics |
| Popis: | We use N-body-spectro-photometric simulations to investigate the impact of incompleteness and incorrect redshifts in spectroscopic surveys to photometric redshift training and calibration and the resulting effects on cosmological parameter estimation from weak lensing shear-shear correlations. The photometry of the simulations is modeled after the upcoming Dark Energy Survey and the spectroscopy is based on a low/intermediate resolution spectrograph with wavelength coverage of 5500{\AA} < {\lambda} < 9500{\AA}. The principal systematic errors that such a spectroscopic follow-up encounters are incompleteness (inability to obtain spectroscopic redshifts for certain galaxies) and wrong redshifts. Encouragingly, we find that a neural network-based approach can effectively describe the spectroscopic incompleteness in terms of the galaxies' colors, so that the spectroscopic selection can be applied to the photometric sample. Hence, we find that spectroscopic incompleteness yields no appreciable biases to cosmology, although the statistical constraints degrade somewhat because the photometric survey has to be culled to match the spectroscopic selection. Unfortunately, wrong redshifts have a more severe impact: the cosmological biases are intolerable if more than a percent of the spectroscopic redshifts are incorrect. Moreover, we find that incorrect redshifts can also substantially degrade the accuracy of training set based photo-z estimators. The main problem is the difficulty of obtaining redshifts, either spectroscopically or photometrically, for objects at z > 1.3. We discuss several approaches for reducing the cosmological biases, in particular finding that photo-z error estimators can reduce biases appreciably. Comment: 18 pages, 8 figures, 4 tables |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|