Title: Seven Lessons from Manyfield Inflation in Random Potentials,
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.