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Let $\pi \in S_n$ be an arbitrary permutation. By permutation graph, we refer to a simple graph with nodes $[n]$ and edges that connect pairs of nodes that appear sorted in $\pi$. Formally, $G=(V=[n],E=\{\{i,j\}\colon i<j\;\&\; \pi_i<\pi_j\})$. It is clear from the definition that an increasing subsequence in $\pi$ would correspond to a clique in $G$. As a consequence maximum clique size $k(G)$ is equal to longest increasing subsequence (LIS) in the permutation $LIS(\pi)$. If $A$ denotes the adjacency matrix of $G$ (which is symmetric and transitive), question is: What can be said about spectral properties of $A$ and $LIS(\pi)$? The general clique problem is known to be NP-hard, but there some interesting spectral bounds, for instance: $$k(G)\ge \frac{n}{n-\lambda_1(A)}$$ derived using the theorem by Motzkin and Straus (link). but since we know that this specific problem has a dynamic programming solution, I am wondering if tighter bounds exist? Moroever, are there also upper bounds for $k(G)$?

This might seem like formulating an easy problem by a much harder one, but for reasons not discussed here, the spectral properties of permutation graph are of interest.

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Permutation graphs are perfect, therefore Lovasz theta, which is essentially a spectral bound, computes the clique number in polynomial time in polynomial time for this class of graphs.

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  • $\begingroup$ do you think Lovas theta function in this special case related to bound $max_{x\in S} \langle x, A x \rangle \ge \frac{1}{2}(1-\frac{1}{k(G)})$ on the simplex: $S = \{x\in[0,1]^n\colon \sum_i x_i =1\}$ given in the Motzkin and Straus paper? $\endgroup$
    – kvphxga
    Commented Jul 17, 2019 at 19:22
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    $\begingroup$ yes, these are related, as we showed in pure.uvt.nl/ws/portalfiles/portal/844532/approxim.pdf (see Lemma 5.2) - you get a slightly different function, $\theta'$, due to A.Schrijver, but they are the same for perfect graphs, IIRC. $\endgroup$ Commented Jul 17, 2019 at 20:25
  • $\begingroup$ in case of the permutation adjacency matrix, can the SDP be approximated more efficiently than running Ellipsoid? How tight can the final value is related to the singular values of $A$? Maybe the result can be approximated by something like power iterations? $\endgroup$
    – kvphxga
    Commented Jul 17, 2019 at 21:14
  • $\begingroup$ In practice noone runs the ellipsoid method (it's just the one for which the performance is understood well). $\endgroup$ Commented Jul 17, 2019 at 21:20

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