CYJAX: A package for Calabi-Yau metrics with JAX

Gerdes, Mathis and Krippendorf, Sven (2023) CYJAX: A package for Calabi-Yau metrics with JAX. Machine Learning: Science and Technology, 4 (2). 025031. ISSN 2632-2153

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Abstract

We present the first version of CYJAX, a package for machine learning Calabi–Yau metrics using JAX. It is meant to be accessible both as a top-level tool and as a library of modular functions. CYJAX is currently centered around the algebraic ansatz for the Kähler potential which automatically satisfies Kählerity and compatibility on patch overlaps. As of now, this implementation is limited to varieties defined by a single defining equation on one complex projective space. We comment on some planned generalizations.

Item Type: Article
Subjects: STM Repository > Multidisciplinary
Depositing User: Managing Editor
Date Deposited: 10 Oct 2023 05:39
Last Modified: 10 Oct 2023 05:39
URI: http://classical.goforpromo.com/id/eprint/3700

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