Stability analysis on the finite-temperature replica-symmetric and first-step replica-symmetry-broken cavity solutions of the random vertex cover problem
arXiv:0901.2635 · doi:10.1103/PhysRevE.80.021122
Abstract
The vertex-cover problem is a prototypical hard combinatorial optimization problem. It was studied in recent years by physicists using the cavity method of statistical mechanics. In this paper, the stability of the finite-temperature replica-symmetric (RS) and the first-step replica-symmetry-broken (1RSB) cavity solutions of the vertex cover problem on random regular graphs of finite vertex-degree are analyzed by population dynamics simulations. We found that (1) the lowest temperature for the RS solution to be stable, , is not a monotonic function of , and (2) at relatively large connectivity and temperature slightly below the dynamic transition temperature , the 1RSB solutions with small but non-negative complexity values are stable. Similar results are obtained on random Poissonian graphs.
arXiv comment15 pages, 9 figures
References in corpus (26)
- The Bethe lattice spin glass revisited
- Gibbs States and the Set of Solutions of Random Constraint Satisfaction Problems
- The random K-satisfiability problem: from an analytic solution to an efficient algorithm
- Phase Transitions in the Coloring of Random Graphs
- On the nature of the low-temperature phase in discontinuous mean-field spin glasses
- Loop series for discrete statistical models on graphs
- Reconstruction on trees and spin glass transition
- The number of matchings in random graphs
- Glass models on Bethe lattices
- Clusters of solutions and replica symmetry breaking in random k-satisfiability
- Instability of one-step replica-symmetry-broken phase in satisfiability problems
- Core percolation in random graphs: a critical phenomena analysis
- On the dynamics of the glass transition on Bethe lattices
- Immunization of Real Complex Communication Networks
- Minimal vertex covers on finite-connectivity random graphs - a hard-sphere lattice-gas picture
- Threshold values, stability analysis and high-q asymptotics for the coloring problem on random graphs
- Vertex cover problem studied by cavity method: Analytics and population dynamics
- Message passing for vertex covers
- Locked constraint satisfaction problems
- Constraint satisfaction problems with isolated solutions are hard
- Potts Glass on Random Graphs
- Long Range Frustrations in a Spin Glass Model of the Vertex Cover Problem
- Near optimal configurations in mean field disordered systems
- Ground-State Entropy of the Random Vertex-Cover Problem
- mean-field population dynamics approach for the random 3-satisfiability problem
- Long-range frustration in T=0 first-step replica-symmetry-broken solutions of finite-connectivity spin glasses
Cited by in corpus (17)
- Avalanches in mean-field models and the Barkhausen noise in spin-glasses
- Tropical Tensor Network for Ground States of Spin Glasses
- The hard-core model on random graphs revisited
- Solving Statistical Mechanics on Sparse Graphs with Feedback Set Variational Autoregressive Networks
- Statistical physics of hard combinatorial optimization: The vertex cover problem
- Solution space structure of random constraint satisfaction problems with growing domains
- Cavity approach to the Sourlas code system
- Minimal Dominating Set problem studied by simulated annealing and cavity method: Analytics and population dynamics
- Two faces of greedy leaf removal procedure on graphs
- Spin glass phase transitions in the random feedback vertex set problem
- Spin-glass model for the C-dismantling problem
- Effect of Constraint Relaxation on the Minimum Vertex Cover Problem in Random Graphs
- Typical Performance of Approximation Algorithms for NP-hard Problems
- The network source location problem: ground state energy, entropy and effects of freezing
- K-core attack, equilibrium K-core, and kinetically constrained spin system
- Constructing Concrete Hard Instances of the Maximum Independent Set Problem
- Statistical mechanics of the minimum vertex cover problem in stochastic block models