# Seven Lessons from Manyfield Inflation in Random Potentials

## TL;DR

This paper investigates inflation models with many interacting fields and random potentials, revealing seven key lessons about their predictions, compatibility with observations, and underlying dynamics, supported by extensive numerical simulations.

## Contribution

It introduces a novel method combining non-equilibrium random matrix theory and an adapted transport method to explicitly study multi-field inflation with up to 100 fields.

## Key findings

- Manyfield inflation differs from single-field models.
- Increasing fields simplifies and sharpens predictions.
- Planck-compatible models are common, but future data may challenge them.

## 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.