Inverting the central limit theorem

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• Miguel Navascues (University of Bristol)
• Thursday 03 November 2011, 14:15-15:15
• MR4, Centre for Mathematical Sciences.

If you have a question about this talk, please contact Paul Skrzypczyk.

Loosely speaking, the Central Limit Theorem states that the sum of N independently distributed n-tuples of real variables tends to a multivariate gaussian distribution for large N; in a sense, the CLT maps microscopic distributions to macroscopic probability densities. Here we propose to invert this mapping: given a set of n correlated experimental gaussian variables, we try to infer information about the (discrete) spectrum of the microscopic variables whose sum generated such macroscopic statistics. The techniques developed along the research are applied to prove that the classical description of certain macroscopic optical experiments is infinitely more complex than the quantum one.

This talk is part of the CQIF Seminar series.

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