Monotone properties of random geometric graphs have sharp thresholds
arXiv:math/0310232 · doi:10.1214/105051605000000575
Abstract
Random geometric graphs result from taking uniformly distributed points in the unit cube, , and connecting two points if their Euclidean distance is at most , for some prescribed . We show that monotone properties for this class of graphs have sharp thresholds by reducing the problem to bounding the bottleneck matching on two sets of points distributed uniformly in . We present upper bounds on the threshold width, and show that our bound is sharp for and at most a sublogarithmic factor away for . Interestingly, the threshold width is much sharper for random geometric graphs than for Bernoulli random graphs. Further, a random geometric graph is shown to be a subgraph, with high probability, of another independently drawn random geometric graph with a slightly larger radius; this property is shown to have no analogue for Bernoulli random graphs.
Published at http://dx.doi.org/10.1214/105051605000000575 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Cited by in corpus (10)
- On Topological Properties of Wireless Sensor Networks under the q-Composite Key Predistribution Scheme with On/Off Channels
- The Peculiar Phase Structure of Random Graph Bisection
- Focusing of Maximum Vertex Degrees in Random Faulty Scaled Sector Graphs
- Properties of metrics and infinite geometric graphs
- A Critical Connectivity Radius for Segmenting Randomly-Generated, High Dimensional Data Points
- Non-equilibrium phase transition and cultural drift in the continuous-trait Axelrod model
- On Characterizing the Local Pooling Factor of Greedy Maximal Scheduling in Random Graphs
- On The Sharp Threshold Interval Length of Partially Connected Random Geometric Graphs During K-Means Classification
- On Cycles in Random Graphs
- Infinite random geometric graphs