Pith. sign in

REVIEW 2 cited by

Complexity of Random Energy Landscapes, Glass Transition and Absolute Value of Spectral Determinant of Random Matrices

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv cond-mat/0401287 v2 pith:6ZCU2WUY submitted 2004-01-16 cond-mat.dis-nn math-phmath.MP

Complexity of Random Energy Landscapes, Glass Transition and Absolute Value of Spectral Determinant of Random Matrices

classification cond-mat.dis-nn math-phmath.MP
keywords randomvaluecomplexitylandscapesphaseabsoluteclasscontrol
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Finding the mean of the total number N_{tot} of critical points for N-dimensional random energy landscapes is reduced to averaging the absolute value of characteristic polynomial of the corresponding Hessian. For any finite N we provide the exact solution to the problem for a class of landscapes corresponding to the "toy model" of manifolds in random environment. For N >>1 our asymptotic analysis reveals a phase transition at some critical value \mu_c of a control parameter \mu from a phase with finite landscape complexity to the phase with vanishing complexity. The same value of the control parameter is known to correspond to an onset of glassy behaviour at zero temperature. Finally, we discuss a method of dealing with the modulus of the spectral determinant applicable to a broad class of problems.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Quantum estimates for classical polynomial optimization

    math-ph 2026-07 conditional novelty 5.0

    A quantum-variational matrix method is proposed for bounding homogeneous polynomials, with converging numerical tensor-eigenvalue estimates and a new conjectured inequality for Biasi's resonant Hamiltonians.

  2. Quantum chaotic systems: a random-matrix approach

    quant-ph 2026-04 unverdicted

    Review of random matrix theory application to quantum chaos, covering symmetry classes, eigenvalue statistics, unfolding, and correlation functions.