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Inflation in random Gaussian landscapes

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arxiv 1612.03960 v2 pith:6M7SOCBA submitted 2016-12-12 hep-th gr-qc

classification hep-thgr-qc
keywords inflationgaussiandistributionslandscapesmethodsnumberrandomtechniques
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abstract

We develop analytic and numerical techniques for studying the statistics of slow-roll inflation in random Gaussian landscapes. As an illustration of these techniques, we analyze small-field inflation in a one-dimensional landscape. We calculate the probability distributions for the maximal number of e-folds and for the spectral index of density fluctuations $n_s$ and its running $\alpha_s$. These distributions have a universal form, insensitive to the correlation function of the Gaussian ensemble. We outline possible extensions of our methods to a large number of fields and to models of large-field inflation. These methods do not suffer from potential inconsistencies inherent in the Brownian motion technique, which has been used in most of the earlier treatments.

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Cited by 1 Pith paper

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  1. Robust non-minimal attractors in many-field inflation

    astro-ph.CO 2025-04 conditional novelty 7.0 of 10

    For non-minimally coupled many-field inflation with at least one ξ ≫ 1, CMB observables match single-field predictions, with explicit large-N formulas for e-folds, Hubble scale, and turn rate.

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