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Three Aspects of Typicality in Multiverse Cosmology

Azhar, Feraz (2016) Three Aspects of Typicality in Multiverse Cosmology. [Preprint]


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Extracting predictions from cosmological theories that describe a multiverse, for what we are likely to observe in our domain, is crucial to establishing the validity of these theories. One way to extract such predictions is from theory-generated probability distributions that allow for selection effects---generally expressed in terms of assumptions about anthropic conditionalization and how typical we are. In this paper, I urge three lessons about typicality in multiverse settings. (i) Because it is difficult to characterize our observational situation in the multiverse, we cannot assume that we are typical (as in the 'principle of mediocrity'): nor can we ignore the issue of typicality, for it has a measurable impact on predictions for our observations. (ii) There are spectra of assumptions about both conditionalization and typicality, which lead to coincident predictions for our observations, leading to problems of confirmation in multiverse cosmology. And moreover, (iii) when one has the freedom to consider competing theories of the multiverse, the assumption of typicality may not lead to the highest likelihoods for our observations. These three entwined aspects of typicality imply that positive assertions about our typicality, such as the 'principle of mediocrity', are more questionable than has been recently claimed.

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Item Type: Preprint
Additional Information: A version of this paper will appear in the European Philosophy of Science Association 2015 Conference Proceedings, eds. J.-W. Romeijn, G. Schurz, and M. Massimi
Keywords: Typicality; Cosmology; Multiverse; Xerographic distribution
Subjects: Specific Sciences > Physics > Cosmology
Specific Sciences > Probability/Statistics
Depositing User: Dr. Feraz Azhar
Date Deposited: 12 Sep 2016 14:28
Last Modified: 12 Sep 2016 14:28
Item ID: 12422
Subjects: Specific Sciences > Physics > Cosmology
Specific Sciences > Probability/Statistics
Date: 8 September 2016

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