Logconcave Random Graphs
Alan Frieze, Santosh Vempala, Juan C. Vera
Abstract
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Alan Frieze, Santosh Vempala, Juan C. Vera
Abstract
Open-access reader
We propose the following model of a random graph on $n$ vertices. Let $F$ be a distribution in $R_+^{n(n-1)/2}$ with a coordinate for every pair $ij$ with $1 \le i,j \le n$. Then $G_{F,p}$ is the distribution on graphs with $n$ vertices obtained by picking a random point $X$ from $F$ and defining a graph on $n$ vertices whose edges are pairs $ij$ for which $X_{ij} \le p$. The standard Erdős-Rényi model is the special case when $F$ is uniform on the $0$-$1$ unit cube. We examine basic properties such as the connectivity threshold for quite general distributions. We also consider cases where the $X_{ij}$ are the edge weights in some random instance of a combinatorial optimization problem. By choosing suitable distributions, we can capture random graphs with interesting properties such as triangle-free random graphs and weighted random graphs with bounded total weight.
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We propose the following model of a random graph on $n$ vertices. Let $F$ be a distribution in $R_+^{n(n-1)/2}$ with a coordinate for every pair $ij$ with $1 \le i,j \le n$. Then $G_{F,p}$ is the distribution on graphs with $n$ vertices obtained by picking a random point $X$ from $F$ and defining a graph on $n$ vertices whose edges are pairs $ij$ for which $X_{ij} \le p$. The standard Erdős-Rényi model is the special case when $F$ is uniform on the $0$-$1$ unit cube. We examine basic properties such as the connectivity threshold for quite general distributions. We also consider cases where the $X_{ij}$ are the edge weights in some random instance of a combinatorial optimization problem. By choosing suitable distributions, we can capture random graphs with interesting properties such as triangle-free random graphs and weighted random graphs with bounded total weight.
Key concepts: Combinatorics, Mathematics, Random graph, Random regular graph, Bounded function, Graph, Discrete mathematics, Unit cube