Mathematics – Logic
Scientific paper
Jun 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010aipc.1241..287s&link_type=abstract
INVISIBLE UNIVERSE: Proceedings of the Conference. AIP Conference Proceedings, Volume 1241, pp. 287-293 (2010).
Mathematics
Logic
Cosmology, Dark Matter, Redshift, Brightness, Observational Cosmology, Dark Energy, Distances, Redshifts, Radial Velocities, Spatial Distribution Of Galaxies, Magnitudes And Colors, Luminosities
Scientific paper
It is known that κ2 statistic and likelihood analysis may not be sensitive to the all features of the data. Despite of the fact that by using κ2 statistic we can measure the overall goodness of fit for a model confronted to a data set, some specific features of the data can stay undetectable. For instance, it has been pointed out that there is an unexpected brightness of the SnIa data at z > 1 in the Union compilation. We quantify this statement by constructing a new statistic, called Binned Normalized Difference (BND) statistic, which is applicable directly on the Type Ia Supernova (SnIa) distance moduli. This statistic is designed to pick up systematic brightness trends of SnIa data points with respect to a best fit cosmological model at high redshifts. According to this statistic there are 2.2%, 5.3% and 12.6% consistency between the Gold06, Union08 and Constitution09 data and spatially flat ΛCDM model when the real data is compared with many realizations of the simulated monte carlo datasets. The corresponding realization probability in the context of a (w0,w1) = (-1.4,2) model is more than 30% for all mentioned datasets indicating a much better consistency for this model with respect to the BND statistic. The unexpected high z brightness of SnIa can be interpreted either as a trend towards more deceleration at high z than expected in the context of ΛCDM or as a statistical fluctuation or finally as a systematic effect perhaps due to a mild SnIa evolution at high z.
Perivolaropoulos Leandros
Shafieloo Arman
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