Testing GRBs as Standard Candles

Astronomy and Astrophysics – Astrophysics

Scientific paper

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10 pages, 3 figures. Improved statistical analysis. Minor changes in results. Accepted in MNRAS (to appear)

Scientific paper

10.1111/j.1365-2966.2008.13894.x

Several correlations among Gamma Ray Burst (GRB) observables with available redshifts have been recently identified. Proper evaluation and calibration of these correlations may facilitate the use of GRBs as standard candles constraining the expansion history of the universe up to redshifts of $z>6$. Here we use the 69 GRB dataset recently compiled by Schaefer (astro-ph/0612285) and we test the calibration of five of the above correlations ($1:\epkk-E_\gamma$, $2:\epkk-L$, $3:\tlag-L$, $4:V-L$, $5:\trt-L$) with respect to two potential sources of systematics: Evolution with redshift and cosmological model used in the calibration. In examining the model dependence we assume flat \lcdm and vary $\omm$. Our approach avoids the circularity problem of previous studies since we do not fix $\omm$ to find the correlation parameters. Instead we simultaneously minimize $\chi^2$ with respect to both the log-linear correlation parameters $a$, $b$ and the cosmological parameter $\omm$. We find no statistically significant evidence for redshift dependence of $a$ and $b$ in any of the correlation relations tested. We also find that one of the five correlation relations tested ($\epkk-E_\gamma$) has a significantly lower intrinsic dispersion compared to the other correlations. For this correlation relation, the maximum likelihood method favors the existence of a cosmological constant while the other four correlation favor a flat matter dominated universe $\omm \simeq 1$. Finally, a cross-correlation analysis between the GRBs and SnIa data for various values of $\omm$ has shown that the $E_{peak}-E_\gamma$ relation traces well the SnIa redshift regime. However, even the tightest correlation relation ($E_{peak}-E_\gamma$) provides much weaker constraints on $\omm$ than current SnIa data.

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