Seven lessons from manyfield inflation in random potentials

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) Many field inflation is not single-field inflation, i i) The larger the number of fields, the simpler and sharper the predictions, i i i) Planck compatibility is not rare, but future experiments may rule out this class of models, i v) The smoother the potentials, the sharper the predictions, v) Hyperparameters can transition from stiff to sloppy, v i) Despite tachyons, isocurvature can decay, v i i) 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.