Answers:
您不应期望获得令人兴奋的加速。我们有
而最著名的空间确定性模拟仍然是Hopcroft-Paul-Valiant定理
因此,不确定性或交替性不会导致加速超过对数因子。(尽管我不确定是否不能使HPV定理代替DSPACE与ATIME一起使用,但我怀疑也没有超线性加速的方法。)
有两个不同的概念:
(1)用非确定性机器对确定性机器进行有效的仿真。
(2)通过一遍又一遍地应用模拟获得的加速结果。
我不知道确定性机器是否可以通过非确定性机器进行任何有效的模拟,但是我知道如果存在有效的模拟,可以使用几种加速结果。
考虑类的语言,这些语言可由运行t (n )时间的非确定性Turing机器仅使用g (n )个不确定性猜测即可确定。换句话说,见证人的长度以g (n )为界。
如果您仅使用 非确定性猜测,那么我相信您可以大大提高速度。特别是,我相信您可以证明以下几点:
如果,然后 d Ť 我中号ë (2 √。
如果您觉得这很有趣,那么我可以写下证明。
赖安·威廉姆斯(Ryan Williams)在“改善穷举搜索意味着超多项式下界”中介绍了一些相关的提速方法。
Here is an explanation for why a general quartic nondeterministic speed-up of deterministic computation even if true would be hard to prove:
Assume that a general quartic nondeterministic speed-up of deterministic computation like holds. For the sake of contradiction, assume that . There is a quadratic-time reduction from any problem in contradicting the time hierarchy theorem.
Therefore, a general quartic nonterministic speed-up of deterministic computation would imply a lower-bound for :
.
Therefore proving a general quadratic nondeterministic speed-up of deterministic computation is at least as hard as proving almost quadratic lower-bounds on .
Similarly, for any well-behaving function :
.
(If in place of we pick a problem which is hard for under linear-time reductions then this would give lower bound for that problem. If we fix the number of the machine tapes to some then we can use Fürer's time hierarchy theorem which does not have the factor.)