Slepian models for Gaussian Random Landscapes

Article

Slepian models for Gaussian Random Landscapes

Blanco-Pillado, J. J.; Sousa, K.; Urkiola, M. A.; Watcher, J.

J. High Energy Phys. 05(10), 142 (2020)

doi ↗ arXiv:1911.07618 ↗

Abstract

Phenomenologically interesting scalar potentials are highly atypical in generic random landscapes. We develop the mathematical techniques to generate constrained random potentials, i.e. Slepian models, which can globally represent low-probability realizations of the landscape. We give analytical as well as numerical methods to construct these Slepian models for constrained realizations of a full Gaussian random field around critical as well as inflection points. We use these techniques to numerically generate in an efficient way a large number of minima at arbitrary heights of the potential and calculate their non-perturbative decay rate. Furthermore, we also illustrate how to use these methods by obtaining statistical information about the distribution of observables in an inflationary inflection point constructed within these models.

Institute authors

Sousa, Kepa

Supported by

GACR 19-01850S — Black-hole and radiative spacetimes: exact methods

BibTeX

@article{UTF833,
  author        = {Blanco-Pillado, J. J. and Sousa, K. and Urkiola, M. A. and Watcher, J.},
  title         = {{Slepian models for Gaussian Random Landscapes}},
  journal       = {J. High Energy Phys.},
  volume        = {05},
  number        = {10},
  pages         = {142},
  year          = {2020},
  doi           = {10.1007/JHEP05(2020)142},
  eprint        = {1911.07618},
  archivePrefix = {arXiv},
}