pith. sign in

arxiv: 1101.1676 · v1 · pith:IHSID6B5new · submitted 2011-01-09 · 🌌 astro-ph.HE · astro-ph.CO· gr-qc· hep-th

Study of possible systematics in the L*X - Ta* correlation of Gamma Ray Bursts

classification 🌌 astro-ph.HE astro-ph.COgr-qchep-th
keywords correlationgrbsredshiftsampleanalysisburstscanonicalcorrelations
0
0 comments X
read the original abstract

Gamma Ray Bursts (GRBs) are the most energetic sources in the universe and among the farthest known astrophysical sources. These features make them appealing candidates as standard candles for cosmological applications so that studying the physical mechanisms for the origin of the emission and correlations among their observable properties is an interesting task. We consider here the luminosity L*X - break time Ta* (hereafter LT) correlation and investigate whether there are systematics induced by selection effects or redshift dependent calibra- tion. We perform this analysis both for the full sample of 77 GRBs with known redshift and for the subsample of GRBs having canonical X-ray light curves, hereafter called U0095 sample. We do not find any systematic bias thus con- firming the existence of physical GRB subclasses revealed by tight correlations of their afterglow properties. Furthermore, we study the possibility of applying the LT correlation as a redshift estimator both for the full distribution and for the canonical lightcurves. The large uncertainties and the non negligible intrin- sic scatter make the results not so encouraging, but there are nevertheless some hints motivating a further analysis with an increased U0095 sample.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Model-independent calibration of Gamma-Ray Bursts with neural networks

    astro-ph.CO 2024-11 unverdicted novelty 5.0

    Neural networks calibrate 2D and 3D Dainotti relations on the Platinum GRB sample via ANN-driven MCMC to produce a model-independent Hubble diagram with reduced scatter.

  2. Cosmology Intertwined: A Review of the Particle Physics, Astrophysics, and Cosmology Associated with the Cosmological Tensions and Anomalies

    astro-ph.CO 2022-03 accept novelty 2.0

    The paper reviews cosmological tensions including the H0 and S8 discrepancies and explores new physics models that could explain them.