Photometric redshifts of galaxies from SDSS and 2MASS |
| |
| Authors: | Tao Wang Jia-Sheng Huang Qiu-Sheng Gu |
| |
| Institution: | [1]Department of Astronomy, Nanjing University, Nanjing 210093, China [2]Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 |
| |
| Abstract: | In order to find the physical parameters which determine the accuracy of pho- tometric redshifts, we compare the spectroscopic and photometric redshifts (photo-z's) for a large sample of ～ 80 000 SDSS-2MASS galaxies. Photo-z's in this paper are es- timated by using the artificial neural network photometric redshift method (ANNz). For a subset of～40000 randomly selected galaxies, we find that the photometric redshift recovers the spectroscopic redshifi distribution very well with rms of 0.016. Our main results are as follows: (1) Using magnitudes directly as input parameters produces more accurate photo-z's than using colors; (2) The inclusion of 2MASS (3, H, Ks) bands does not improve photo-z's significantly, which indicates that near infrared data might not be important for the low-redshift sample; (3) Adding the concentration index (essentially the steepness of the galaxy brightness profile) as an extra input can improve the photo-z's estimation up to～10 percent; (4) Dividing the sample into early- and late-type galaxies by using the concentration index, normal and abnormal galaxies by using the emission line flux ratios, and red and blue galaxies by using color index (g - r), we can improve the accuracy of photo-z's significantly; (5) Our analysis shows that the outliers (where there is a big difference between the spectroscopic and photometric redshifts) are mainly correlated with galaxy types, e.g., most outliers are late-type (blue) galaxies. |
| |
| Keywords: | galaxies: distances and redshifts -- methods: statistical -- techniques: pho- tometric |
| 本文献已被 维普 万方数据 等数据库收录！ |
|
