Akaike Model Selection Criterion Applied to Supernovae Data

Details Akaike Model Selection Criterion Applied to Supernovae Data Akaike Model Selection Criterion Applied to Supernovae Data

Aug 2007

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007idm..conf..655b&link_type=abstract

THE IDENTIFICATION OF DARK MATTER. Proceedings of the Sixth International Workshop. Held 11-16 September 2006 in Rhodes, Greece.

Mathematics

Logic

Classical Tests Of Cosmology, Dark Energy Theory

Scientific paper

In this contribution we apply model selection approach based on Akaike criterion as an estimator of Kullback-Leibler entropy. In particular, we present the proper way of ranking the competing models based on Akaike weights (in Bayesian language - posterior probabilities of the models). This important ingredient is missing in alternative studies dealing with cosmological applications of Akaike criterion.
Out of many particular models of dark energy we focus on four: quintessence, quintessence with time varying equation of state, brane-world and generalized Chaplygin gas model and test them on Riess' Gold sample.
As a result we obtain that the best model - in terms of Akaike Criterion - is the quintessence model with evolving equation of state. The odds suggest that although there exist differences in the support given to specific scenarios by supernova data all models considered receive similar support. One can also notice that models similar in structure i.e. ΛCDM, quintessence and quintessence with variable equation of state are closer to each other in terms of Kullback-Leibler entropy. Models having different structure i.e. Chaplygin gas or brane-world scenario are more distant (in Kullback-Leibler sense) from the best one.

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