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An eprint paper published today on the ArXiv and submitted to MNRAS: The Axis of Evil revisited by Land and Magueijo.
The analysis of the CMB data is statistical by nature and the existence or non-existence of features such as the 'Axis of Evil' is a matter of evaluating its statistical likelihood. Their highly technical paper re-examines the methods used and concludes
Garth
The analysis of the CMB data is statistical by nature and the existence or non-existence of features such as the 'Axis of Evil' is a matter of evaluating its statistical likelihood. Their highly technical paper re-examines the methods used and concludes
To put it more simply:We have highlighted weaknesses with the original AOE statistic (2) that probed m-preference for ℓ = 2−5. These are
primarily:
1) lack of robustness: small changes in the data produce very different results, i.e., the statistics are discontinuous;
2) variations with data-set: it is hard to connect varying results to imperfections in the data or the statistic;
3) need simulations to assess significance: no way of penalizing for extra parameters or comparing competing theories, e.g., planarity V’s general m-preference.
We have found an improved formalism by employing a Bayesian approach, which cures the instabilities. These were due to the existence of multiple solutions for a given multipole. But bringing in a penalization related to the number of parameters of the model enforces “Occams Razor” and selects solutions where parameters are common between the multipoles.
The Bayesian approach also allows a better assessment of the relative evidence for planarity (correlation between ℓ = 2, 3, m′ = ℓ modes) and m-preference (a correlation between ℓ = 2 − 5, m′ not restricted). This extends the work of Magueijo & Sorkin (2006) where the low-ℓ low-power evidence was assessed, as well as planarity for some data-sets.
Comparing Table 2 and Table 5 we see that overall there is more evidence for m-preference than for planarity (the exceptions being the BIC for LILC1 and TOHc3), with slightly stronger evidence from the first-year data. We find that although the Bayesian method is more robust, the various information criteria reach different conclusions. The AIC generally provides strong evidence for planarity and decisive evidence for m-preference. The BIC provides varying results. This is to be compared to the evidence for scalar spectral index nS not equal to 1, where conclusions also differ between IC methodology (Magueijo & Sorkin 2006).
Abstract
We find strong (and sometimes decisive) evidence for the “Axis of Evil” in almost all renditions of the WMAP data. However some significant differences between data-sets remain, and the quantitative aspects of the result depend on the particular information criteria used.
Garth
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