Human versus Artificial Inteligence; a significant example in astrophysics, alas

TL;DR

Addresses how to adjudicate competing GRB models by contrasting Cannonball and standard fireball pictures through an AI-facilitated Q&A with a tabular comparison of predictions vs observations. It couples a parsimonious CB description with a flexible fireball framework to compare prompt emission, polarization, afterglow light curves, jet breaks, and multi-band correlations, highlighting where each model naturally accounts for data and where tuning is required. The document also discusses the sociology of model preference, arguing that the standard framework's empirical successes and integration with relativistic shock physics sustain its dominance, while acknowledging the CB approach as a compact, alternative interpretation. Overall, it offers a structured, testable framework for GRB model testing and illustrates how methodological biases can influence theoretical allegiance.

Abstract

There are two well documented models of gamma ray bursts (GRBs), the "Standard' model and the "Cannonball" model. They have often been reviewed [1] and sometimes compared [2]. Here, to avoid understandable biases, I show below the results of an experiment: letting an AI compare the data and the two models. All of what follows (but two references, two footnotes and the next sentence) is the result of asking Perplexity.ai to perform this confrontational task. It should be easy for an impartial reader to reach very clear conclusions.