Mathematics – Logic
Scientific paper
May 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aas...21441405m&link_type=abstract
American Astronomical Society, AAS Meeting #214, #414.05; Bulletin of the American Astronomical Society, Vol. 41, p.681
Mathematics
Logic
Scientific paper
Many of the cosmological tests to be performed by planned dark energy experiments will require extremely well-characterized photometric redshift measurements. Weak lensing analysis from simulations have shown that the true mean redshift of the objects in each photo-z bin must be known to better than 0.002(1+z) if errors in cosmological measurements are not to be degraded. A conventional approach is to calibrate these photometric redshifts with large sets of spectroscopic redshifts. However, at the depths probed by Stage III surveys (such as DES), let alone Stage IV (LSST, JDEM, Euclid), existing large redshift samples have all been highly (25-60%) incomplete, with a strong dependence of success rate on both redshift and galaxy properties.
A powerful alternative approach is to exploit the clustering of galaxies to perform photometric redshift calibrations. Measuring the angular cross-correlation between objects in some photometric redshift bin and objects with known spectroscopic redshift, as a function of the spectroscopic z, allows the true redshift distribution of a photometric sample to be reconstructed in detail, even if it includes objects too faint for spectroscopy or if spectroscopic samples are highly incomplete. We test this technique using mock DEEP2 Galaxy Redshift survey light cones constructed from the Millennium Simulation semi-analytic galaxy catalogs. From these lightcones we construct two galaxy samples; one magnitude limited sample with characteristics similar to the DEEP2 spectroscopic survey, where redshift distribution is assumed known, and one with a distribution assumed unknown, which we attempt to recover using this method. From this realistic test, we find that the true redshift distribution of a photometric sample can, in fact, be determined accurately with cross-correlation techniques. We also compare the empirical error in the reconstruction of redshift distributions to previous analytic predictions, finding that additional components must be included in error budgets to match the simulation results.
No associations
LandOfFree
Calibrating Photometric Redshifts in Mock DEEP2 Catalogs Using Cross Correlations does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Calibrating Photometric Redshifts in Mock DEEP2 Catalogs Using Cross Correlations, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Calibrating Photometric Redshifts in Mock DEEP2 Catalogs Using Cross Correlations will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1106897