境界...
私たちは、実際に持っているN F A (L )≥ C O V (M )+ C O V (N )、(グルーバー&ホルツァー2006)における定理4を参照してください。上限については、我々は2 C O V (M )+ C O V (N ) ≥ D F A (L )≥ N F A (Lが)、同じ論文で定理11を参照してください。 NFA(L)≥Cov(M)+Cov(N)2Cov(M)+Cov(N)≥DFA(L)≥NFA(L)
...大幅に改善することはできません
準指数との間に隙間があってもよいC O V (M )+ C O V (N )及びN F A (L )。次の例とギャップの証明は、(Hromkovičet al。2009)の非決定論的な状態の複雑さの下限を証明するための2パーティプロトコルの制限を示す同様の例の適応です。Cov(M)+Cov(N)NFA(L)
アルファベット[ n ] = {1 、2 、... 、n個}。レッツ L = {[n]={1,2,…,n}X 、Y 、Z ∈ [ N ] 3 | X = Y ∨ X ≠ Z}。L={xyz∈[n]3∣x=y∨x≠z}
最初にC o v (M )を処理します。場合に観察W = X 、Y 、Zと、Y = Z、次いで
W ∈ L場合:X = Y、W ∈ Lとケースでは、xは≠ yは、我々はまた、持っている
X ≠ Zしたがってwは∈ L。場合にも、wは形式であるxは、Y 、Zを用いて
、Y ≠ Z次に、Cov(M)w=xyzy=zw∈Lx=yw∈Lx≠yx≠zw∈Lwxyzy≠zw∈Lw∈L iff x≠zx≠z. So we can write L=L′∪L″L=L′∪L′′,
with L′={xyz∈[n]3∣y=z}L′={xyz∈[n]3∣y=z} and L″={xyz∈[n]3∣y≠z∧x≠z}L′′={xyz∈[n]3∣y≠z∧x≠z}.
Now consider the bipartite graphs G′=(U′,V′,E′)G′=(U′,V′,E′) with U′=[n]U′=[n], V′={yz∈[n]2∣y=z}V′={yz∈[n]2∣y=z}, E′=U′×V′E′=U′×V′, as well
as G″=(U″,V″,E″)G′′=(U′′,V′′,E′′) with U″=[n]U′′=[n], V″={yz∈[n]2∣y≠z}V′′={yz∈[n]2∣y≠z},
E″={(x,yz)∣x≠z}E′′={(x,yz)∣x≠z}, and G=(U′∪U″,V′∪V″,E′∪E″)G=(U′∪U′′,V′∪V′′,E′∪E′′).
Then a biclique edge cover for the graph
GG gives rise to a covering of MM with 11-monochromatic
submatrices, and vice versa (Theorem 21 in Gruber & Holzer 2006).
A simple kernelization trick for computing a biclique edge cover for G′G′
is to put the twin vertices from U′U′ into equivalence classes. Then we do the same in the resulting graph for the twin vertices from V′V′.
Twin vertices are those with identical neighborhood.
This step does not alter the minimum number of bicliques needed to cover all
edges in the respective graph.
The kernelization step collapses G′G′ into a graph with two vertices and
a single edge. Thus, the edges of G′G′ can be covered with a single
biclique. Applying the kernelization step to G″G′′ yields a crown graph
on 2n2n vertices, whose bipartite dimension (the minimum biclique edge
cover number) is known to be σ(n)σ(n), where σσ is the inverse
function of the middle binomial coefficient (De Caen et al. 1981). Notice that σ(n)=O(logn)σ(n)=O(logn).
Thus the bipartite dimension of GG is 1+σ(n)1+σ(n), which is identical
to Cov(M)Cov(M).
Now consider Cov(N)Cov(N). Observe that if w=xyzw=xyz with x=yx=y, then w∈Lw∈L. If x≠yx≠y, then x∈Lx∈L iff x≠zx≠z. So we can write L=L‴∪L⁗L=L′′′∪L′′′′
with L‴={xyz∈[n]3∣x=y}L′′′={xyz∈[n]3∣x=y} and L⁗={xyz∈[n]3∣x≠y∧x≠z}L′′′′={xyz∈[n]3∣x≠y∧x≠z}. Almost the same argument as above yields
Cov(N)=1+σ(n)Cov(N)=1+σ(n).
It remains to give a lower bound on the nondeterministic state
complexity of LL. Observe that LL contains all words of the form xxxxxx
with x∈[n]x∈[n]. For each such word xxxxxx fix an accepting computation of a minimal
NFA accepting L. Let px denote the state reached after reading the
prefix x, and let qx denote the state reached after reading the
prefix xx of the input word xxx. Then all pairs (px,qx) must be
different. For the sake of contradiction, assume (px,qx)=(py,qy)
for some x≠y. Then we can construct an accepting computation
on input xyx, such that the NFA is in state px=qx after reading
the prefix x, and in state qy=qx after reading the prefix xy.
But the string xyx is not in L. For the state set Q of the NFA, this shows
that |Q|2≥n. Thus,
for large n, we obtain a subexponential separation between Cov(M)+Cov(N) and |Q| (the nondeterministic state complexity of L).
References
Dominique de Caen, David A. Gregory, Norman J. Pullman: The Boolean rank of zero-one matrices, in: Cadogan, Charles C. (ed.), 3rd Caribbean Conference on Combinatorics and Computing, Department of Mathematics, University of the West Indies, pp. 169–173 (1981)
Hermann Gruber and Markus Holzer. Finding Lower Bounds for Nondeterministic State Complexity is Hard. Report TR06-027, Electronic Colloquium on Computational Complexity (ECCC), March 2006. Short version appeared in: Oscar H. Ibarra and Zhe Dang, editors, 10th International Conference on Developments in Language Theory (DLT 2006), Santa Barbara (CA), USA, volume 4036 of LNCS, pages 363-374. Springer, June 2006.
Juraj Hromkovic, Holger Petersen, Georg Schnitger: On the limits of the
communication complexity technique for proving lower bounds on the size
of minimal NFAs. Theor. Comput. Sci. 410(30–32): 2972–2981 (2009)