Inflation with a graceful exit in a random landscape

TL;DR

This paper models small-field inflation in a string landscape using random matrix theory, deriving probabilities for inflationary trajectories and constraints on the number of light fields based on curvature observations.

Contribution

It introduces a stochastic framework linking inflationary dynamics to Dyson Brownian motion and provides analytical bounds on the number of light fields during inflation.

Findings

Exponential bias against small-field inflation ranges.

Upper bound of N << 10 on light fields from curvature constraints.

Analytical relaxation probability derived for eigenvalue spectra.

Abstract

We develop a stochastic description of small-field inflationary histories with a graceful exit in a random potential whose Hessian is a Gaussian random matrix as a model of the unstructured part of the string landscape. The dynamical evolution in such a random potential from a small-field inflation region towards a viable late-time de Sitter (dS) minimum maps to the dynamics of Dyson Brownian motion describing the relaxation of non-equilibrium eigenvalue spectra in random matrix theory. We analytically compute the relaxation probability in a saddle point approximation of the partition function of the eigenvalue distribution of the Wigner ensemble describing the mass matrices of the critical points. When applied to small-field inflation in the landscape, this leads to an exponentially strong bias against small-field ranges and an upper bound $N\ll 10$ on the number of light fields $N$ participating during inflation from the non-observation of negative spatial curvature.