Seven Lessons from Manyfield Inflation in Random Potentials

Dias, Mafalda; Marsh, M. c. David; Frazer, Jonathan

Preprint/Report

PUBDB-2017-07908

Seven Lessons from Manyfield Inflation in Random Potentials

Dias, M.DESY* ; Frazer, J.DESY* ; Marsh, M. c. D. (Corresponding author)

2017

[10.3204/PUBDB-2017-07908]

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Please use a persistent id in citations: doi:10.3204/PUBDB-2017-07908

Report No.: DESY-17-082; arXiv:1706.03774

Abstract: We study inflation in models with many interacting fields subject to randomly generated scalar potentials. We use methods from non-equilibrium random matrix theory to construct the potentials and an adaption of the transport method to evolve the two-point correlators during inflation. This construction allows, for the first time, for an explicit study of models with up to 100 interacting fields supporting a period of approximately saddle-point inflation. We determine the statistical predictions for observables by generating over 30,000 models with 2-100 fields supporting at least 60 efolds of inflation. These studies lead us to seven lessons: i) Manyfield inflation is not single-field inflation, ii) The larger the number of fields, the simpler and sharper the predictions, iii) Planck compatibility is not rare, but future experiments may rule out this class of models, iv) The smoother the potentials, the sharper the predictions, v) Hyperparameters can transition from stiff to sloppy, vi) Despite tachyons, isocurvature can decay, vii) Eigenvalue repulsion drives the predictions. We conclude that many of the generic predictions of single-field inflation can be emergent features of complex inflation models.

Keyword(s): matrix model: random ; inflation: model ; potential: random ; potential: scalar ; saddle-point approximation ; correlation function ; isocurvature ; statistical ; tachyon: field theory ; satellite: Planck