An E-value Reanalysis of DESI's Dynamical Dark Energy Signal
Cosmological surveys such as DESI release data in stages, and each release reprocesses earlier observations and supersedes its predecessor. Testing the same hypothesis at every release inflates the false-positive rate, and only the collaboration can estimate the cross-release covariance that an exact combination needs. We show how to combine evidence across such releases using public products alone. From each release we compute an e-value, a non-negative statistic with expectation at most one under the null, and we average these e-values with weights fixed in advance. Provided each release's own likelihood is correct, this average controls the false-positive rate at every release under arbitrary dependence between releases. For DESI BAO at a fixed Planck background, DR2 alone gives an e-value of $33.97$ against $Λ$CDM ($p \le 0.0295$) under our reference test specification, a flat prior on $(w_0, w_a)$ over a fixed box. The equal-weight average of DR1 and DR2 is $17.51$ ($p \le 0.0571$), below the rejection threshold of $20$. We did not fix these weights before DR2 was published, and the weights we now fix ahead of DR3 give $p \le 0.0874$ at DR2. Without a model of the cross-release covariance, an exact combination that counts each observation once can take any value. Under explicit models it ranges from below the threshold to nearly double the DR2 value, depending on the structure assumed. The evidence is concentrated in the LRG2 bin, which also changed most between releases. Without it the DR2 e-value falls to $0.49$, and a look-elsewhere correction over the seven redshift bins leaves no rejection. DR2 does not reject under wider priors either. The signal is therefore fragile and specification-dependent. We recommend that surveys report per-release e-values with a stated test specification and a combination rule fixed in advance, and publish the cross-release covariance.