From String Theory to Machine-Learning Mathematical Structures

Abstract: We report and summarize some of the recent experiments in machine-learning of various structures from different fields of mathematics, ranging from the string landscape, to geometry, to representation theory, to combinatorics, to number theory. We speculate on a hierarchy of inherent difficulty and where string theoretic problems tend to reside.

other condensed matterstatistical mechanicsstrongly correlated electronsgeneral relativity and quantum cosmologyHEP - theorymathematical physicsalgebraic geometrydifferential geometrydynamical systemsgroup theorynumber theoryquantum algebrarepresentation theory

Audience: researchers in the discipline

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Number theory, Arithmetic and Algebraic Geometry, and Physics

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