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arXiv · 2112.10872

Calabi-Yau Metrics, Energy Functionals and Machine-Learning

Anthony Ashmore·Lucille Calmon·Yang-Hui He·Burt A. Ovrut
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Abstract

We apply machine learning to the problem of finding numerical Calabi-Yau metrics. We extend previous work on learning approximate Ricci-flat metrics calculated using Donaldson's algorithm to the much more accurate "optimal" metrics of Headrick and Nassar. We show that machine learning is able to predict the Kähler potential of a Calabi-Yau metric having seen only a small sample of training data.

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Anthony Ashmore, Lucille Calmon, Yang-Hui He, Burt A. Ovrut. 2021-12-20. Calabi-Yau Metrics, Energy Functionals and Machine-Learning. https://doi.org/10.1142/s2810939222500034

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