English

Manifolds pinned by a high-dimensional random landscape: Hessian at the global energy minimum

Disordered Systems and Neural Networks 2020-04-22 v1 Statistical Mechanics Mathematical Physics math.MP

Abstract

We consider an elastic manifold of internal dimension dd and length LL pinned in a NN dimensional random potential and confined by an additional parabolic potential of curvature μ\mu. We are interested in the mean spectral density ρ(λ)\rho(\lambda) of the Hessian matrix KK at the absolute minimum of the total energy. We use the replica approach to derive the system of equations for ρ(λ)\rho(\lambda) for a fixed LdL^d in the NN \to \infty limit extending d=0d=0 results of our previous work. A particular attention is devoted to analyzing the limit of extended lattice systems by letting LL\to \infty. In all cases we show that for a confinement curvature μ\mu exceeding a critical value μc\mu_c, the so-called "Larkin mass", the system is replica-symmetric and the Hessian spectrum is always gapped (from zero). The gap vanishes quadratically at μμc\mu\to \mu_c. For μ<μc\mu<\mu_c the replica symmetry breaking (RSB) occurs and the Hessian spectrum is either gapped or extends down to zero, depending on whether RSB is 1-step or full. In the 1-RSB case the gap vanishes in all dd as (μcμ)4(\mu_c-\mu)^4 near the transition. In the full RSB case the gap is identically zero. A set of specific landscapes realize the so-called "marginal cases" in d=1,2d=1,2 which share both feature of the 1-step and the full RSB solution, and exhibit some scale invariance. We also obtain the average Green function associated to the Hessian and find that at the edge of the spectrum it decays exponentially in the distance within the internal space of the manifold with a length scale equal in all cases to the Larkin length introduced in the theory of pinning.

Keywords

Cite

@article{arxiv.1903.07159,
  title  = {Manifolds pinned by a high-dimensional random landscape: Hessian at the global energy minimum},
  author = {Yan V. Fyodorov and Pierre Le Doussal},
  journal= {arXiv preprint arXiv:1903.07159},
  year   = {2020}
}

Comments

44 pages, 5 figures