Data discrepancies may affect scientific understanding of the universe
New IOI tools discover inconsistencies through various techniques administered by university researchers.

Leah Williams | 4 hours ago

UT Dallas researchers have developed a new technique, named index of inconsistency (IOI), which produces a numerical value to the degree of discordance between two or more data sets.

Comparisons with an IOI greater than 1 are considered inconsistent. Those with an IOI over 5 are ranked as strongly inconsistent.

The team of researchers used their IOI to compare five different techniques for determining the Hubble parameter, which is related to the rate at which the universe is expanding.

Local measurement is one of the methods that rely on measuring the distances to relatively nearby exploding stars called supernovae. The alternative method relies on the evaluations of different phenomena at much greater lengths.

"We found that there is an agreement between four out of five of these methods, but the Hubble parameter from local measurement of supernovae is not in agreement. It's like an outlier," Ishak-Boushaki said. "In particular, there is a clear tension between the local measurement and that from the Planck science mission, which characterized the cosmic microwave background radiation."

Discrepancies begin to form when multiple methods have been used to determine that local measurement, producing similar Hubble value. Relatively, they are still in disagreement with Planck and other results.

"This is very intriguing. This is telling us that the universe at the largest observable scales may behave differently from the universe at intermediate or local scales," Ishak-Boushaki said. "This leads us to question whether Albert Einstein's theory of gravity is valid all the way from small scales to very large scales in the universe."

The UT Dallas researchers have made their IOI tool available for other scientists to use. Ishak-Boushaki further explained the Dark Energy Science Collaboration, part of the Large Synoptic Survey Telescope project, will use the tool to look for inconsistencies among data sets.

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