Model-independently calibrating the luminosity correlations of gamma-ray bursts using deep learning

Understand

Gamma-ray bursts (GRBs) detected at high redshift can be used to trace the Hubble diagram of the Universe.

• However, the distance calibration of GRBs is not as easily as that of type Ia supernovae (SNe Ia).
• For the calibrating method based on the empirical luminosity correlations, there is an underlying assumption that the correlations should be universal over the whole redshift range.
• In this paper, we investigate the possible redshift dependence of six luminosity correlations with a completely model-independent deep learning method.