Sharp threshold for the Erdős–Ko–Rado theorem
Sharp threshold for the Erdős–Ko–Rado theorem
复制标题
ErdÅsâKoâRado 定理的尖锐阈值
DOI:
10.1002/rsa.21090
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发表时间:
2023
影响因子:
1
通讯作者:
Luo, Haoran
中科院分区:
文献类型:
--
作者:
Balogh, József;Krueger, Robert A.;Luo, Haoran
For positive integers n$$ n $$ and k$$ k $$ with n≥2k+1$$ n\ge 2k+1 $$, the Kneser graph K(n,k)$$ K\left(n,k\right) $$ is the graph with vertex set consisting of all k$$ k $$‐sets of {1,…,n}$$ \left\{1,\dots, n\right\} $$, where two k$$ k $$‐sets are adjacent exactly when they are disjoint. The independent sets of K(n,k)$$ K\left(n,k\right) $$ are k$$ k $$‐uniform intersecting families, and hence the maximum size independent sets are given by the Erdős–Ko–Rado Theorem. Let Kp(n,k)$$ {K}_p\left(n,k\right) $$ be a random spanning subgraph of K(n,k)$$ K\left(n,k\right) $$ where each edge is included independently with probability p$$ p $$. Bollobás, Narayanan, and Raigorodskii asked for what p$$ p $$ does Kp(n,k)$$ {K}_p\left(n,k\right) $$ have the same independence number as K(n,k)$$ K\left(n,k\right) $$ with high probability. For n=2k+1$$ n=2k+1 $$, we prove a hitting time result, which gives a sharp threshold for this problem at p=3/4$$ p=3/4 $$. Additionally, completing work of Das and Tran and work of Devlin and Kahn, we determine a sharp threshold function for all n>2k+1$$ n>2k+1 $$.
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DOI:
10.1017/s0963548318000433
发表时间:
2014
期刊:
Combinatorics, Probability and Computing
影响因子:
--
作者:
Arran Hamm;J. Kahn
通讯作者:
J. Kahn
DOI:
10.1017/s0963548309990253
发表时间:
2009
期刊:
Combinatorics, Probability and Computing
影响因子:
--
作者:
J. Balogh;T. Bohman;D. Mubayi
通讯作者:
D. Mubayi
DOI:
10.1016/j.jcta.2015.01.003
发表时间:
2014
期刊:
J. Comb. Theory A
影响因子:
--
作者:
J. Balogh;Shagnik Das;Michelle Delcourt;Hong Liu;M. Sharifzadeh
通讯作者:
M. Sharifzadeh
DOI:
10.1017/fms.2015.21
发表时间:
2015
期刊:
Forum of Mathematics, Sigma
影响因子:
--
作者:
J. Balogh;B. Bollobás;Bhargav P. Narayanan
通讯作者:
Bhargav P. Narayanan
DOI:
10.1137/15m1012992
发表时间:
2015
期刊:
SIAM J. Discret. Math.
影响因子:
--
作者:
Pat Devlin;J. Kahn
通讯作者:
J. Kahn