A Free Lunch Theorem For Circuit Complexity
Posted by Lance
A guest post from Dieter van Melkebeek
This week, about 50
computer scientists gather at Schloss
Dagstuhl for a seminar on "Complexity of Boolean Functions." The
setup follows a long tradition that started back in 1944 at Dagstuhl's
mathematical sister institution in Oberwolfach: a flexible program of talks,
ample time for discussion, and Deutsche Gruendlichkeit in a wonderful
setting.
I'll highlight an aspect of roughly one talk per
day. Given the wide variety of topics, the selection is idiosyncratic
rather than representative. For a full list of the talks, check out
the seminar web page.
On Monday, Philipp Woelfel discussed time-space tradeoffs for integer
multiplication. Every program computing the product of two n-bit
integers in time T and space S has to satisfy TS = Ω(n2), and
this lower bound is tight. One may expect that the same time-space
tradeoff holds if we're only interested in the i-th bit of the
product, where i is part of the input. However, Philipp showed a
randomized program (with polynomially small error) that does the job
using only O(n log n) time and O(log n) space, for a product TS of O(n
log2 n). It remains open whether the TS =
Ω(n2) lower bound for the simpler problem holds in
the deterministic setting.
I stole the title for this weblog entry from Peter Bro
Miltersen. Right before lunch on Monday, he presented his "free
lunch theorem": Lower bounds for circuits that consist of a gate
C applied to symmetric functions of ANDs (type I) imply lower bounds
for circuits that consist of a gate C applied to symmetric functions
of AC0 functions (type II). The proof outline goes as
follows. Consider a circuit of type II. By the switching lemma,
hitting it with a random restriction transforms each of the
AC0 functions into small decision trees, each of which can
be written as a small OR of small ANDs. For any given decision tree,
at most one of its ANDs can be true. It follows that a symmetric
function of decision trees is a symmetric function of all the ANDs
involved in these decision trees. This transformation gives us a
circuit of type I that isn't much larger than the original circuit.
Part of Tuesday was devoted to quantum computing.
Andy Yao presented an approach to unify and generalize the known quantum
lower bounds for (i) locating an item in a sorted list of n elements and
(ii) sorting a list of n elements. Both in the classical and in the
quantum setting, we know that (i) takes Ω(log n) comparisons and (ii)
takes Ω(n log n) comparisons. Problems (i) and (ii) are instantiations of
the following more general problem, which is parameterized by a partial
order P on n elements: Using comparisions only, determine an unknown linear
order of n elements that is guaranteed to be consistent with P. We obtain
problem (i) by setting P to be a linear order on all
but one element, and (ii) by making P empty. If we denote by e(P) the
number of linear extensions of P, we have that e(P) = n in case (i) and
e(P) = n! in case (ii). Since there are e(P) different outcomes and
each classical comparison gives us at most one bit of information, we
need at least log e(P) such comparisons. Thus, one obtains the classical
lower bounds for (i) and (ii) in a uniform way. The simple information
theoretic argument breaks down in the quantum setting. Nevertheless,
using the notion of graph entropy, Andy proved a lower bound of
Ω(e(P)) - O(n) for the number of comparisons in the quantum
setting. He conjectured that the O(n) term can be dropped, which would
yield a uniform proof of the quantum lower bounds for (i) and (ii).
On Wednesday morning, Omer Reingold talked about recent progress
towards a simpler or more combinatorial proof of the PCP Theorem.
In particular, he presented a more modular way of composing proof systems,
a crucial step in the known proofs of the PCP Theorem. Wednesday
afternoon was kept free for a hike in the woods - one of the nice
traditions at Dagstuhl.
1:03 PM
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