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Article overview
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GAz: A Genetic Algorithm for Photometric Redshift Estimation | | Robert Hogan
; Malcolm Fairbairn
; Navin Seeburn
; | | Date: |
17 Dec 2014 | | Abstract: | We present a new approach to the problem of estimating the redshift of
galaxies from photometric data. The approach uses a genetic algorithm combined
with non-linear regression to model the 2SLAQ LRG data set with SDSS DR7
photometry. The genetic algorithm explores the very large space of high order
polynomials while only requiring optimisation of a small number of terms. We
find a $sigma_{ ext{rms}}=0.0408pm 0.0006$ for redshifts in the range
$0.4<z< 0.7$. These results are competitive with the current state-of-the-art
but can be presented simply as a polynomial which does not require the user to
run any code. For other datasets or applications the code has been made
available at this https URL | | Source: | arXiv, 1412.5997 | | Services: | Forum | Review | PDF | Favorites | |
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