EDP Sciences
Free access
Volume 490, Number 3, November II 2008
Page(s) 1047 - 1053
Section Extragalactic astronomy
DOI http://dx.doi.org/10.1051/0004-6361:200810545
Published online 11 September 2008

A&A 490, 1047-1053 (2008)
DOI: 10.1051/0004-6361:200810545

Robust photometric redshift determinations of gamma-ray burst afterglows at z$\gtrsim$ 2

P. A. Curran1, R. A. M. J. Wijers1, M. H. M. Heemskerk1, R. L. C. Starling2, K. Wiersema2, and A. J. van der Horst3

1  Astronomical Institute, University of Amsterdam, Kruislaan 403, 1098 SJ Amsterdam, The Netherlands
    e-mail: pcurran@science.uva.nl
2  Department of Physics and Astronomy, University of Leicester, University Road, Leicester LE1 7RH, UK
3  NASA Postdoctoral Program Fellow, NSSTC, 320 Sparkman Drive, Huntsville, AL 35805, USA

Received 8 July 2008 / Accepted 6 September 2008

Context. Theory suggests that about 10% of Swift-detected gamma-ray bursts (GRBs) will originate at redshifts, z, greater than 5 yet a number of high redshift candidates may be left unconfirmed due to the lack of measured redshifts.
Aims. Here we introduce our code, GRBz, a method of simultaneous multi-parameter fitting of GRB afterglow optical and near infrared, spectral energy distributions. It allows for early determinations of the photometric redshift, spectral index and host extinction to be made.
Methods. We assume that GRB afterglow spectra are well represented by a power-law decay and model the effects of absorption due to the Lyman forest and host extinction. We use a genetic algorithm-based routine to simultaneously fit the parameters of interest, and a Monte Carlo error analysis.
Results. We use GRBs of previously determined spectroscopic redshifts to prove our method, while also introducing new near infrared data of GRB 990510 which further constrains the value of the host extinction.
Conclusions. Our method is effective in estimating the photometric redshift of GRBs, relatively unbiased by assumptions of the afterglow spectral index or the host galaxy extinction. Monte Carlo error analysis is required as the method of error estimate based on the optimum population of the genetic algorithm underestimates errors significantly.

Key words: gamma rays: bursts -- methods: data analysis -- techniques: photometric

© ESO 2008