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Table 1
Methods used for photo-z estimation within PHAT.
Acronym | Participant | Code | Reference | Public |
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BP-t | Coe, D. | BPZ, Bayesian Photometric Redshifts | Benítez (2000); Coe et al. (2006) | √ a |
BP2-t | Benitez, N. | BPZ, Bayesian Photometric Redshifts | Benítez (2000); Benítez 2010 (in prep.) | √ a |
EA-t | Brammer, G. | EAZY, Easy and Accurate Redshifts from Yale | Brammer et al. (2008) | √ b |
GA-t | Kotulla, R. | GALEV, GALaxy EVolution | Kotulla et al. (2009) | √ c |
GO-t | Dahlen, T. | GOODZ | Dahlen et al. (2005, 2007) | |
HY-t | Miralles, J.-M. | Hyperz | Bolzonella et al. (2000) | √ d |
KR-t | Schmidt, S. | Kernelz, Kernel Regression | Schmidt & Brewer (in prep.) | |
LP-t | Arnouts, S. | Le Phare | Ilbert et al. (2006) | √ e |
Ilbert, O. | ||||
LR-t | Assef, R. | LRT, Low-Resolution Spectral Templates | Assef et al. (2008, 2010) | √ f |
PT-t | Purger, N. | Template Repair | Adelman-McCarthy et al. (2007) | √ g |
ZE-t | Feldmann, R. | ZEBRA, Zurich Extragalactic Bayesian Redshift Analyzer | Feldmann et al. (2006) | √ h |
ZE2-t | Gillis, B. | ZEBRA, Zurich Extragalactic Bayesian Redshift Analyzer | Feldmann et al. (2006) | √ h |
AN-e | Abdalla, F. | ANNz, Artificial Neural Network | Collister & Lahav (2004) | √ i |
Banerji, M. | ||||
DT-e | Gerdes, D. | BDT, Boosted Decision Trees | Gerdes et al. (2010) | |
EC-e | Wolf, C. | Empirical χ2 | Wolf (2009) | |
PN-e | Purger, N. | Nearest-Neighbour Fit | Abazajian et al. (2009) | √ g |
PO-e | Li, I. H. | Polynomial Fit | Li & Yee (2008) | |
RT-e | Carliles, S. | Regression Trees | Carliles et al. (2010) | √ j |
SN-e | Singal, J. | Neural Network | – | √ k |
Notes.
(a)
http://acs.pha.jhu.edu/~txitxo/; version 1.99.3 used for PHAT: http://www.its.caltech.edu/~coe/BPZ/
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