Source-linked AI summary

Hiding Quiet Solutions in Random Constraint Satisfaction Problems

Florent Krzakala, Lenka Zdeborová

arXiv:0901.2130v2cond-mat.stat-mechcond-mat.dis-nncs.AIcs.CC

TL;DR

Planting guarantees satisfiability, but can alter an ensemble, and when planted instances remain difficult is less understood than for purely random CSPs. The paper analyzes quiet planting through q-coloring, finding planted/random ensemble equivalence below c_c and a hard/easy boundary at c_l=(q−1)^2.

  • Problem

    Planting guarantees satisfiability, but it changes ensemble properties, and when planted instances remain difficult is less understood than for purely random CSPs.

    Source: p. 1
  • Method

    The paper studies a natural quiet-planting scheme for q-coloring and uses the cavity method to analyze its solution structure and phase diagram.

    Source: p. 1
  • Results

    For q-coloring, planted and purely random ensembles are asymptotically equivalent for c < c_c, and the hard/easy transition coincides with liquid instability at c_l=(q−1)^2.

    Source: pp. 3–4
  • Takeaways & Limitations

    Quiet planting can generate planted instances without influencing most ensemble characteristics in CSPs whose purely random BP fixed point is uniform.

    Source: pp. 1, 4

    The results apply to CSPs with a uniform BP fixed point in the purely random ensemble; random satisfiability, whose fixed point is nonuniform, is not covered.

    Source: p. 4

Abstract

from arXiv · show

We study constraint satisfaction problems on the so-called 'planted' random ensemble. We show that for a certain class of problems, e.g. graph coloring, many of the properties of the usual random ensemble are quantitatively identical in the planted random ensemble. We study the structural phase transitions, and the easy/hard/easy pattern in the average computational complexity. We also discuss the finite temperature phase diagram, finding a close connection with the liquid/glass/solid phenomenology.

Loading 0901.2130v2…