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Manifolds Pinned by a High-Dimensional Random Landscape: Hessian at the Global Energy Minimum
- Source :
- Phys.Rev.E, Phys.Rev.E, 2020, 101 (2), pp.020101. ⟨10.1103/PhysRevE.101.020101⟩, Physical Review E : Statistical, Nonlinear, and Soft Matter Physics, Physical Review E : Statistical, Nonlinear, and Soft Matter Physics, American Physical Society, 2020, 101 (2), pp.020101. ⟨10.1103/PhysRevE.101.020101⟩, Journal of Statistical Physics, Journal of Statistical Physics, Springer Verlag, 2020, 179 (1), pp.176-215. ⟨10.1007/s10955-020-02522-2⟩
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- We consider an elastic manifold of internal dimension $d$ and length $L$ pinned in a $N$ dimensional random potential and confined by an additional parabolic potential of curvature $\mu$. We are interested in the mean spectral density $\rho(\lambda)$ of the Hessian matrix $K$ at the absolute minimum of the total energy. We use the replica approach to derive the system of equations for $\rho(\lambda)$ for a fixed $L^d$ in the $N \to \infty$ limit extending $d=0$ results of our previous work. A particular attention is devoted to analyzing the limit of extended lattice systems by letting $L\to \infty$. In all cases we show that for a confinement curvature $\mu$ exceeding a critical value $\mu_c$, the so-called "Larkin mass", the system is replica-symmetric and the Hessian spectrum is always gapped (from zero). The gap vanishes quadratically at $\mu\to \mu_c$. For $\mu<br />Comment: 44 pages, 5 figures
- Subjects :
- Length scale
Hessian matrix
[PHYS.MPHY]Physics [physics]/Mathematical Physics [math-ph]
FOS: Physical sciences
Curvature
01 natural sciences
010305 fluids & plasmas
symbols.namesake
Lattice (order)
0103 physical sciences
Symmetry breaking
010306 general physics
Condensed Matter - Statistical Mechanics
Mathematical Physics
Mathematical physics
Physics
Statistical Mechanics (cond-mat.stat-mech)
Statistical Physics
Spectral density
Statistical and Nonlinear Physics
Disordered Systems and Neural Networks (cond-mat.dis-nn)
Mathematical Physics (math-ph)
Condensed Matter - Disordered Systems and Neural Networks
Scale invariance
[PHYS.PHYS.PHYS-GEN-PH]Physics [physics]/Physics [physics]/General Physics [physics.gen-ph]
Manifold
symbols
Subjects
Details
- ISSN :
- 15729613, 00224715, 15393755, and 15502376
- Volume :
- 179
- Database :
- OpenAIRE
- Journal :
- Journal of Statistical Physics
- Accession number :
- edsair.doi.dedup.....70cd828d95d3f9c34db51d16bfb22196