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SUMMARY:Ellie Heyes (City\, University of London)
DTSTART:20240417T090000Z
DTEND:20240417T100000Z
DTSTAMP:20260423T021044Z
UID:CompAlg/33
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/CompAlg/33/"
 >Generating Calabi–Yau Manifolds with Machine Learning</a>\nby Ellie Hey
 es (City\, University of London) as part of Machine Learning Seminar\n\n\n
 Abstract\nCalabi–Yau n-folds can be obtained as hypersurfaces in toric v
 arieties built from (n+1)-dimensional reflexive polytopes. Calabi–Yau 3-
 folds are of particular interest in string theory as they reduce 10-dimens
 ional superstring theory to 4-dimensional quantum field theories with N=1 
 supersymmetry. We generate Calabi–Yau 3-folds by generating 4-dimensiona
 l reflexive polytopes and their triangulations using genetic algorithms an
 d reinforcement learning respectively. We show how\, by modifying the fitn
 ess function of the genetic algorithm\, one can generate Calabi–Yau mani
 folds with specific properties that give rise to certain string models of 
 particular interest.\n
LOCATION:https://researchseminars.org/talk/CompAlg/33/
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