49 research outputs found
Sherali-Adams and the binary encoding of combinatorial principles.
We consider the Sherali-Adams ( SA ) refutation system together with the unusual binary encoding of certain combinatorial principles. For the unary encoding of the Pigeonhole Principle and the Least Number Principle, it is known that linear rank is required for refutations in SA , although both admit refutations of polynomial size. We prove that the binary encoding of the Pigeonhole Principle requires exponentially-sized SA refutations, whereas the binary encoding of the Least Number Principle admits logarithmic rank, polynomially-sized SA refutations. We continue by considering a refutation system between SA and Lasserre (Sum-of-Squares). In this system, the unary encoding of the Least Number Principle requires linear rank while the unary encoding of the Pigeonhole Principle becomes constant rank
Resolution and the binary encoding of combinatorial principles.
Res(s) is an extension of Resolution working on s-DNFs. We prove tight n (k) lower bounds for the size
of refutations of the binary version of the k-Clique Principle in Res(o(log log n)). Our result improves that of
Lauria, Pudlák et al. [27] who proved the lower bound for Res(1), i.e. Resolution. The exact complexity of
the (unary) k-Clique Principle in Resolution is unknown. To prove the lower bound we do not use any form of
the Switching Lemma [35], instead we apply a recursive argument specific for binary encodings. Since for the
k-Clique and other principles lower bounds in Resolution for the unary version follow from lower bounds in
Res(log n) for their binary version we start a systematic study of the complexity of proofs in Resolution-based
systems for families of contradictions given in the binary encoding.
We go on to consider the binary version of the weak Pigeonhole Principle Bin-PHPmn
for m > n. Using
the the same recursive approach we prove the new result that for any > 0, Bin-PHPmn
requires proofs of size
2n1− in Res(s) for s = o(log1/2 n). Our lower bound is almost optimal since for m 2
p
n log n there are
quasipolynomial size proofs of Bin-PHPmn
in Res(log n).
Finally we propose a general theory in which to compare the complexity of refuting the binary and unary
versions of large classes of combinatorial principles, namely those expressible as first order formulae in 2-form
and with no finite model