Language Complexity, Part 7

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David A. Tanzer, February 11, 2021, in unit Language Complexity. Cross-posted to the Azimuth Blog.

Higher complexity classes

In Part 6, we saw a program with quadratic complexity. The collection of all languages that can be decided in $O(n^k)$ time for some $k$ is called P, for polynomial time complexity.

Now let’s consider languages that appear to require time that is exponential in the size of the input, and hence lie outside of P.

Here is a decision problem that is believed to be of this sort. Say you are given a description of a boolean circuit, involving AND, OR and NOT gates, which has N inputs and one output. Is there a combination of input values that causes the output to be True?

It appears that any general decision procedure for this problem must resort to some form of searching all the possible input combinations. For N inputs, that’s on the order of $2^N$ combinations to be tried. So the computation takes time that is exponential in the number of inputs.

There is a related decision problem for languages. Consider the language of Boolean formulas like (not(X7) and (X1 or not(X2 and X1)). The query is to find assignments of True/False to each of the variables which satisfy the formula, i.e., which make it evaluate to True.

Note that each Boolean formula is equivalent to a Boolean circuit, and a satisfying assignment to the variables is tantamount to an input combination which causes the circuit to output True.

Let SAT be the language consisting of Boolean formulas which are satisfiable, i.e., for which a satisfying assignment exists. For example, the formula (X1 and X2) belongs to SAT, because it is satisfied by the assignment X1=True, X2=True. On the other hand, (X1 and not(X1)) has no satisfying assignment, and so it does not belong to SAT.

Apparently, a decider for SAT must end up resorting to trying an exponential number of combinations. Now the number of variables in a formula is $O(n)$. A brute force search through input combinations means exponential time complexity.

Could some clever person figure out a better method, which runs in polynomial time? Not if the widely believed conjecture that P != NP holds true.

Copyright © 2021, David A. Tanzer, All Rights Reserved.

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