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Swampland Tests in KKLT Scenarios with DKMM Racetrack


Gligovic,  Aleksandar
Max Planck Institute for Physics, Max Planck Society and Cooperation Partners;

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Gligovic, A. (2022). Swampland Tests in KKLT Scenarios with DKMM Racetrack. Master Thesis, LMU, München.

Cite as: https://hdl.handle.net/21.11116/0000-000C-B4CD-2
The huge vacuum degeneracy in string compactifications allows one to derive low energy theories with basically any kinds of particle spectra and mediating forces. The swampland program systematically filters out phenomenologically interesting models by formulating universal quantum gravity constraints and testing those against string theory data. One particular conjecture forbids (meta-)stable and very long-lived de Sitter vacua derived from string theory. It is inspired by the difficulty of reaching de Sitter minima from serious top-down constructions, with the main issues being the stabilization of moduli and controlled supersymmetry breaking. The KKLT scenario, a prominent counterexample, realizes a positive cosmological constant by using fluxes and quantum effects for moduli stabilization and uplifting the negative AdS energy with a D3-brane placed at the tip of a warped throat. The recent DKMM algorithm provides a recipe for constructing suitable flux vectors and stabilizing the axio-dilaton in a racetrack procedure. We work out several parametric problems in such a construction in a model-independent way. First, we derive a familiar bound for the volume modulus for “the throat to fit into the bulk”, using an explicit parametrization of the throat. Then, we collect physical energy scales in two distinct KKLT scenarios, showing that a necessary condition for a sensible mass hierarchy is a high tadpole contribution from the throat fluxes. Nevertheless, one of our scenarios always has a spoiled hierarchy since throat and bulk scales generally mix. In the final part we estimate the lifetime of numerical de Sitter realizations and illustrate a parametric inconsistency with a recent swampland constraint.