Dynamic or Systematic? Bayesian model selection between dark energy and supernova biases

Abstract DES-5Y supernovae, combined with DESI BAO, appear to favour Chevallier–Polarski–Linder (w0, wa) dynamical dark energy over ΛCDM. It has been suggested in other work that this is driven by a systematic in the DES pipeline, which particularly affects the low-redshift supernovae brought in from legacy surveys. It is difficult to investigate these data in isolation, however, as the complicated supernovae pipelines must properly account for selection effects. In this work, we discover that a magnitude offset between the low- and high-redshift supernovae is favoured by the Bayesian evidence over the flexknot dark energy found in our previous work. In addition, we find that the possible tension between DES-5Y and DESI is significantly reduced by such an offset. The recent DES-Dovekie recalibration partially alleviates this tension, but does not eliminate it. We also take the opportunity to trial Nested Bridge Sampling with Sequential Monte Carlo as an alternative method for calculating Bayes factors.