Constraint on Lorentz Invariance Violation for spectral lag transition in GRB 160625B using profile likelihood

TL;DR

This paper applies the profile likelihood method to analyze spectral lag data from GRB 160625B, providing new lower bounds on the quantum gravity energy scale related to Lorentz Invariance Violation, contrasting previous Bayesian approaches.

Contribution

It introduces the use of profile likelihood inference for constraining LIV from GRB spectral lag data, offering a new statistical approach compared to prior Bayesian methods.

Findings

Lower bounds on $E_{QG}$: $2.55 imes 10^{16}$ GeV (linear), $1.85 imes 10^7$ GeV (quadratic)

Profile likelihood does not find a global minimum below the Planck scale for LIV models

First application of profile likelihood to GRB spectral lag data for LIV constraints

Abstract

We reanalyze the spectral lag data for GRB 160625B using frequentist inference in order to constrain the energy scale ($E_{QG}$) of Lorentz Invariance Violation (LIV). For this purpose, we use profile likelihood to deal with the astrophysical nuisance parameters. This is in contrast to Bayesian inference implemented in previous works, where marginalization was carried out over the nuisance parameters. We show that with profile likelihood, we do not find a global minimum for $\chi^2$ as a function of $E_{QG}$ below the Planck scale for both linear and quadratic models of LIV, whereas bounded credible intervals were previously obtained using Bayesian inference. Therefore, we can set one-sided lower limits in a straightforward manner. We find that $E_{QG} \geq 2.55 \times 10^{16}$ GeV and $E_{QG} \geq 1.85 \times 10^7$ GeV at 95\% c.l., for linear and quadratic LIV, respectively. Therefore, this is the first proof-of-principles application of profile likelihood method to the analysis of GRB spectral lag data to constrain LIV.