I heard of a nice new result from Russell Impagliazzo and Valentine
Kabanets yesterday. Consider the language PI (Polynomial Identities)
consisting of multivariate polynomials which are identically zero. PI
is in co-RP by replacing the variables by random values and seeing if
the result is zero. There is a lemma by Schwartz that implies this
randomized algorithm will work with high confidence.
Since we now know Primality is in P, PI is the best remaining example
of a problem with an efficient probabilistic algorithm but no known
deterministic algorithm. Unlike primality, giving
even a weak derandomization for PI will be difficult as it will lead
to circuit lower bounds.
Theorem: (Impagliazzo-Kabanets)
At least one of the following must be true
PI requires deterministic exponential time to solve.
The permanent does not have polynomial-size arithmetic circuits.
NEXP does not have polynomial-size Boolean circuits.
Here is a sketch of the proof. For a matrix A let Aij
represent A with the ith row and jth column removed. Consider the
self-reduction from the permanent of a (k+1)×(k+1) matrix to
permanents of k×k matrices
(*) Perm(A) = Σj a1j Perm(A1j)
Suppose that the permanent has polynomial-size arithmetic circuits.
Then P#P is computable in NPPI by the following
algorithm: Guess the arithmetic circuits for the Permanent for all
sizes k×k up to n×n for some appropriate n. Use PI to verify (*)
for each k<n. If the test is correct on all lengths than the
circuits are correct. Use the circuits to compute the Permanent which is
#P-complete.
Now suppose NEXP has polynomial-size circuits. By
Impagliazzo-Kabanets-Wigderson this implies NEXP = MA ⊆
PH ⊆ P#P ⊆ NPPI. If PI is computable
in subexponential time then NEXP is in nondeterministic subexponential
time, contradicting the nondeterministic time hierarchy.