Journal article
Computation of quark masses from string theory
- Abstract:
- We present a numerical computation, based on neural network techniques, of the physical Yukawa couplings in a heterotic string theory compactification on a smooth Calabi-Yau threefold with non-standard embedding. The model belongs to a large class of heterotic line bundle models that have previously been identified and whose low-energy spectrum precisely matches that of the MSSM plus fields uncharged under the Standard Model group. The relevant quantities for the calculation, that is, the Ricci-flat Calabi-Yau metric, the Hermitian Yang-Mills bundle metrics and the harmonic bundle-valued forms, are all computed by training suitable neural networks. For illustration, we consider a one-parameter family in complex structure moduli space. The computation at each point along this locus takes about half a day on a single twelve-core CPU. Our results for the Yukawa couplings are estimated to be within 10% of the expected analytic result. We find that the effect of the matter field normalisation can be significant and can contribute towards generating hierarchical couplings. We also demonstrate that a zeroth order, semi-analytic calculation, based on the Fubini-Study metric and its counterparts for the bundle metric and the bundle-valued forms, leads to roughly correct results, about 25% away from the numerical ones. The method can be applied to other heterotic line bundle models and generalised to other constructions, including to F-theory models.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.0MB, Terms of use)
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- Publisher copy:
- 10.1016/j.nuclphysb.2024.116778
Authors
+ Science and Technology Facilities Council
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- Funder identifier:
- https://ror.org/057g20z61
- Grant:
- ST/X000761/1
+ Engineering and Physical Sciences Research Council
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- Funder identifier:
- https://ror.org/0439y7842
- Publisher:
- Elsevier
- Journal:
- Nuclear Physics B More from this journal
- Volume:
- 1010
- Article number:
- 116778
- Publication date:
- 2024-12-17
- Acceptance date:
- 2024-12-12
- DOI:
- EISSN:
-
1873-1562
- ISSN:
-
0550-3213
- Language:
-
English
- Pubs id:
-
2073171
- Local pid:
-
pubs:2073171
- Deposit date:
-
2025-08-11
Terms of use
- Copyright holder:
- Constantin et al.
- Copyright date:
- 2025
- Rights statement:
- © 2024 The Author(s). Published by Elsevier B.V. Funded by SCOAP. This is an open access article under the CC BY license.
- Licence:
- CC Attribution (CC BY)
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