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VERSION:2.0
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PRODID:UW-Madison-Physics-Events
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SEQUENCE:2
UID:UW-Physics-Event-4932
DTSTART:20181130T200000Z
DTEND:20181130T212500Z
DTSTAMP:20210923T045116Z
LAST-MODIFIED:20181123T222141Z
LOCATION:5280 Chamberlin Hall
SUMMARY:Topological Data Analysis for Cosmology and String Theory\, Th
eory Seminar (High Energy/Cosmology)\, Alex Cole\, University of Wisco
nsin-Madison
DESCRIPTION:Persistent homology\, the main technique underlying the fi
eld of Topological Data Analysis\, computes the multiscale topology of
a data set by using a sequence of discrete complexes. Roughly speakin
g\, persistent homology allows us to compute the “shape” of data.
In this talk I will introduce persistent homology and describe applica
tions to data sets in cosmology and string theory. I will demonstrate
how persistence diagrams provide an improved real-space observable for
the Cosmic Microwave Background. In particular\, persistence diagrams
are more sensitive to local non-Gaussianity on a set of simulated tem
perature maps than Betti numbers\, which are in turn more sensitive th
an the genus. I will also use persistent homology to characterize dist
ributions of Type IIB flux vacua and as a framework for understanding
the correlation of different low-energy features in moduli space.
URL:https://www.physics.wisc.edu/events/?id=4932
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