Flat Distributions and Incompleteness



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Flat Distributions and Incompleteness

A distribution is flat if . Flat distributions are commonly used in practice. For example, the most frequently used model for undirected random graphs without self-loops is with . It consists of all graphs with vertex set in which vertices are labeled and the edges are chosen independently with probability , which is a function of . So a graph with vertex set and edges in this model occurs with probability . If we assume also that satisfies for some fixed , then is flat [Gur91a], since . Similar distributions for directed graphs are also flat for the same reason [WB95]. Most of the NP-complete graph problems have other parameters as inputs-for example, rather than taking just a graph as input, the input may be , where is often a bound on the number of vertices or the number of edges of some structure the graph may have that the problem is speaking of (clique, etc.). So their distributions are flat. Gurevich [Gur87] showed that dealing with flat distributions to get average-case completeness results using p-time or ap-time reductions is impossible unless .

 

Proof.a problem with a flat distribution is complete under ap-time reductions. Then . Let be an arbitrary decision problem in NTIME for some polynomial . For any , let . Then is in NP. Define by for the appropriate constant and if for any . Then , which implies that there is an ap-time reduction from to . Hence, deciding whether can be done by deciding whether . Since is computable in time polynomial on -average, computing can be carried out in time , due to the particular selection of . Also, for some and for all , where is polynomial on -average and so again due to the definition of . Thus, and so for some polynomial . Since is flat, there is a such that . This implies that .

For reductions that are restricted to be one-one and length-preserving within a polynomial (i.e., there is a polynomial such that, for all , ), Wang and Belanger [WB95] showed that the above incompleteness theorem is true without any assumption. We note that all the natural NP-complete problems are indeed complete under such reductions.

 

Proof.to the contrary that there were an ap-time reduction reducing DH1 to a problem with flat distribution , where is one-one and length-preserving within a polynomial. Then is weakly dominated by with respect to . Since is one-one, is weakly dominated by . Since is flat, there is an such that for all but finitely many . Since is length-preserving within a polynomial, there is a constant such that, for all , . When is sufficiently large and greater than , . So . But , which cannot be weakly dominated by , a contradiction.


next up previous contents
Next: Randomized Average Polynomial Up: Randomization Previous: Randomization



Jie Wang
Tue Feb 4 13:48:58 EST 1997