Could We Be Fooled about Phantom Crossing?
Ryan E. Keeley, Arman Shafieloo, William L. Matthewson

TL;DR
This paper investigates whether the observed evidence for dark energy crossing the phantom divide line could be a statistical artifact, using Monte Carlo simulations to assess the likelihood of such a false detection.
Contribution
It introduces a Monte Carlo simulation framework to evaluate the probability that data fluctuations mimic phantom crossing in dark energy models.
Findings
3.2% of simulations falsely suggest phantom crossing fits better
Evolving dark energy signals are robust, but crossing behavior needs more data
Statistical fluctuations can sometimes mimic crossing in model fits
Abstract
Recent data from DESI Year 2 BAO, Planck CMB, and various supernova compilations suggest a preference for evolving dark energy, with hints that the equation of state may cross the phantom divide line (). While this behavior is seen in both parametric and non-parametric reconstructions, comparing reconstructions that support such behavior (such as the best fit of CPL) with those that maintain (like the best fit algebraic quintessence) is not straightforward, as they differ in flexibility and structure, and are not necessarily nested within one another. Thus, the question remains as to whether the crossing behavior that we observe, suggested by the data, truly represents a dark energy model that crosses the phantom divide line, or if it could instead be a result of data fluctuations and the way the data are distributed. We investigate the likelihood of this possibility. For…
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Taxonomy
TopicsQuantum Mechanics and Applications
