Journal
ASTRONOMY & ASTROPHYSICS
Volume 490, Issue 3, Pages 1047-1053Publisher
EDP SCIENCES S A
DOI: 10.1051/0004-6361:200810545
Keywords
gamma rays: bursts; methods: data analysis; techniques: photometric
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Funding
- NWO [639.043.302]
- STFC
- NASA Postdoctoral Program at the NSSTC
- Science and Technology Facilities Council [PP/E002064/1] Funding Source: researchfish
- STFC [ST/F006489/1, PP/E002064/1] Funding Source: UKRI
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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.
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