Astronomy and Astrophysics – Astronomy
Scientific paper
Oct 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aspc..408..215w&link_type=abstract
The Starburst-AGN Connection. ASP Conference Series, Vol. 408, proceedings of the conference held 27-31 October 2008, at Shangha
Astronomy and Astrophysics
Astronomy
Scientific paper
We compute accurate photometric redshifts for a sample of ˜ 80,000 SDSS-2MASS galaxies with known spectroscopic redshifts, aiming to find the physical parameters which determine the accuracy of photometric redshifts. We find that the photometric redshift derived form the artificial neural network photometric redshift method (ANNz) recover the spectroscopic redshift distribution very well with rms of 0.017. Our main results include that: using magnitudes directly as input parameters produces more accurate photo-z's than using the color index; the inclusion of 2MASS (J, H, K) bands does not improve photo-z's significantly while the inclusion of the concentration index can improve the photo-z's estimation up to ˜ 10 percent. Moreover, if we divide the sample into early- and late- type galaxies or red and blue galaxies, and estimate their photo-z's respectively, we can derive photo-z's more accurately. Finally, our analysis show that the outliers in each case we considered are correlated well with galaxy types, that is, most outliers are late-type (blue) galaxies.
Gu Qiu-Sheng
Huang Sheng-Jun
Wang Tower
No associations
LandOfFree
Improving Photometric Redshifts Using Different Photometric Parameters 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 Improving Photometric Redshifts Using Different Photometric Parameters, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Improving Photometric Redshifts Using Different Photometric Parameters will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1354005