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Decoding Nature with Nature's Tools: Heterotic Line Bundle Models of Particle Physics with Genetic Algorithms and Quantum Annealing

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arxiv 2306.03147 v1 pith:6GABXL6M submitted 2023-06-05 hep-th cs.AI

Decoding Nature with Nature's Tools: Heterotic Line Bundle Models of Particle Physics with Genetic Algorithms and Quantum Annealing

classification hep-th cs.AI
keywords stringalgorithmscompactificationsgeneticheterotickahlerlandscapemanifolds
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The string theory landscape may include a multitude of ultraviolet embeddings of the Standard Model, but identifying these has proven difficult due to the enormous number of available string compactifications. Genetic Algorithms (GAs) represent a powerful class of discrete optimisation techniques that can efficiently deal with the immensity of the string landscape, especially when enhanced with input from quantum annealers. In this letter we focus on geometric compactifications of the $E_8\times E_8$ heterotic string theory compactified on smooth Calabi-Yau threefolds with Abelian bundles. We make use of analytic formulae for bundle-valued cohomology to impose the entire range of spectrum requirements, something that has not been possible so far. For manifolds with a relatively low number of Kahler parameters we compare the GA search results with results from previous systematic scans, showing that GAs can find nearly all the viable solutions while visiting only a tiny fraction of the solution space. Moreover, we carry out GA searches on manifolds with a larger numbers of Kahler parameters where systematic searches are not feasible.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Exploring Line Bundle Standard Models with Transformers

    hep-th 2026-06 unverdicted novelty 7.0

    A Transformer RL agent is trained to generate valid heterotic line bundle sums on CICYs that satisfy gauge embedding, anomaly cancellation, poly-stability, chirality, and no-exotics constraints.

  2. Small Vacuum Energy and Tunneling in a Modified Bousso-Polchinski Model

    hep-th 2026-05 unverdicted novelty 6.0

    In a wafer-modified Bousso-Polchinski model, 99.95% of the 532 million Calabi-Yau fourfold configurations in the Schöller-Skarke database allow vacuum energy spacings of 10^{-120} or smaller, with membrane nucleation ...

  3. Exploring Line Bundle Standard Models with Transformers

    hep-th 2026-06 conditional novelty 5.0

    A Transformer trained by reinforcement learning generates heterotic line-bundle sums that satisfy anomaly-cancellation, stability, and chirality constraints, and its policy transfers usefully across Calabi-Yau geometries.