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SUMMARY:Inverting the central limit theorem - Miguel Navascues (University
  of Bristol)
DTSTART:20111103T141500Z
DTEND:20111103T151500Z
UID:TALK33750@talks.cam.ac.uk
CONTACT:Paul Skrzypczyk
DESCRIPTION:Loosely speaking\, the Central Limit Theorem states that the s
 um of N independently distributed n-tuples of real variables tends to a mu
 ltivariate gaussian distribution for large N\; in a sense\, the CLT maps m
 icroscopic distributions to macroscopic probability densities. Here we pro
 pose to invert this mapping: given a set of n correlated experimental gaus
 sian variables\, we try to infer information about the (discrete) spectrum
  of the microscopic variables whose sum generated such macroscopic statist
 ics. The techniques developed along the research are applied to prove that
  the classical description of certain macroscopic optical experiments is i
 nfinitely more complex than the quantum one. 
LOCATION:MR4\, Centre for Mathematical Sciences
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