Pedagogic Null Tests of Dynamical Dark Energy Hints: Reconstructing LambdaCDM with Consistent BAO, CMB, and SNe Mocks
Seokcheon Lee

TL;DR
This study uses realistic mock datasets to perform a null test on dark energy models, demonstrating that apparent deviations can arise from dataset degeneracies and likelihood geometry rather than true physics.
Contribution
It introduces a controlled null test with comprehensive mock datasets to clarify how dataset degeneracies can mimic evidence for dynamical dark energy.
Findings
Individual probes show apparent deviations in (w0,wa) space.
Two-probe combinations with supernovae recover fiducial parameters but lack absolute scale.
Full multi-probe likelihood breaks degeneracies and accurately recovers the true cosmology.
Abstract
Hints of a dynamical dark-energy equation of state have appeared in several combined cosmological probes. However, such indications may instead arise from the intrinsic likelihood geometry of individual datasets, residual inter-probe tension, or restrictive priors. These factors can mimic evidence for dynamical dark energy. To clarify these issues, we perform a controlled null test. We use realistic mock BAO, CMB, and Type~Ia supernova datasets generated from a common fiducial LambdaCDM cosmology. These mocks include the DESI~DR2 BAO covariance, the Planck~2018 distance-prior covariance, and the full Pantheon+ SH0ES supernova covariance. This setup isolates physical information from geometric or statistical effects in the CPL parametrization. We find that individual probes and most two-probe combinations show apparent deviations in the (w0,wa) plane. These could be mistaken for phantom…
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Taxonomy
TopicsCosmology and Gravitation Theories · Galaxies: Formation, Evolution, Phenomena · Particle physics theoretical and experimental studies
