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Title: Charting an Inflationary Landscape with Random Matrix Theory

We construct a class of random potentials for N >> 1 scalar fields using non-equilibrium random matrix theory, and then characterize multifield inflation in this setting. By stipulating that the Hessian matrices in adjacent coordinate patches are related by Dyson Brownian motion, we define the potential in the vicinity of a trajectory. This method remains computationally efficient at large N, permitting us to study much larger systems than has been possible with other constructions. We illustrate the utility of our approach with a numerical study of inflation in systems with up to 100 coupled scalar fields. A significant finding is that eigenvalue repulsion sharply reduces the duration of inflation near a critical point of the potential: even if the curvature of the potential is fine-tuned to be small at the critical point, small cross-couplings in the Hessian cause the curvature to grow in the neighborhood of the critical point.
Authors:
 [1] ;  [2] ;  [3] ;  [4]
  1. Rudolf Peierls Centre for Theoretical Physics, University of Oxford, 1 Keble Road, Oxford OX1 3NP (United Kingdom)
  2. Department of Physics, Cornell University, Ithaca, NY 14853 (United States)
  3. Department of Physics, Princeton University, Princeton, NJ 08544 (United States)
  4. Stanford Institute for Theoretical Physics, Stanford University, Stanford, CA 94305 (United States)
Publication Date:
OSTI Identifier:
22369916
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Cosmology and Astroparticle Physics; Journal Volume: 2013; Journal Issue: 11; Other Information: Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; 79 ASTROPHYSICS, COSMOLOGY AND ASTRONOMY; BROWNIAN MOVEMENT; COUPLINGS; DIAGRAMS; EIGENVALUES; ELECTRIC UTILITIES; EQUILIBRIUM; GAS UTILITIES; INFLATIONARY UNIVERSE; MATRICES; NUMERICAL ANALYSIS; POTENTIALS; RANDOMNESS; SCALAR FIELDS