A simple trick that every complexity theorist should know but, based on
some recent conversations, not every complexity theorist does
know. Roughly speaking collapses for small resource bounds imply
collapses for large resource bounds. Here is the result for NTIME
(nondeterministic time) and DTIME (deterministic time) but the proof
works for nearly every pair of complexity measures.
Translation Lemma: Let f(n), g(n), h(n) be reasonable (time-constructible)
functions with h(n)>n. Then
The proof uses a technique known as padding. Let L be in
NTIME(f(h(n))) via a machine M. Define A by
A = {x01h(|x|)-|x|-1 | x in L}
We can compute whether x01h(n)-|x|-1 is in A by simulating
M(x) which takes nondeterministic time f(h(|x|))=f(m) where m=h(n) is the
length of the input. So A is in NTIME(f(m)) and by assumption in
DTIME(g(m)).
Now if we want to compute whether x is in L we can use the DTIME(g(m))
algorithm for A on x01h(n)-|x|-1 taking total time g(h(n))
since the input has size m=h(n). QED
As an immediate consequence we get that if P=NP then E=NE (where
E=DTIME(2O(n))) by letting h(n)=2n.
The translation lemma works in only one direction. You need h(n)>n,
you can't unpad an arbitrary x. It's open whether E=NE implies P=NP
for instance.
The lemma has many applications. Here is one example. Theorem: If P=NP then some language in E does not have
subexponential-size circuits.
Proof: In the Σ4 level of the E-time hierarchy
we can compute the
lexicographically-first language A that cannot be simulated by any
2n/2-size circuits. If P=NP then the polynomial-time
hierarchy collapse to P. By
a version of the translation lemma with h(n)=2n the
polynomial-time hiearchy collapsing to P implies
the E-time hierarchy collapses to E. Thus A is in E
but A does not have subexponential-size circuits.