139 research outputs found
Improved bounds for testing Dyck languages
In this paper we consider the problem of deciding membership in Dyck
languages, a fundamental family of context-free languages, comprised of
well-balanced strings of parentheses. In this problem we are given a string of
length in the alphabet of parentheses of types and must decide if it is
well-balanced. We consider this problem in the property testing setting, where
one would like to make the decision while querying as few characters of the
input as possible.
Property testing of strings for Dyck language membership for , with a
number of queries independent of the input size , was provided in [Alon,
Krivelevich, Newman and Szegedy, SICOMP 2001]. Property testing of strings for
Dyck language membership for was first investigated in [Parnas, Ron
and Rubinfeld, RSA 2003]. They showed an upper bound and a lower bound for
distinguishing strings belonging to the language from strings that are far (in
terms of the Hamming distance) from the language, which are respectively (up to
polylogarithmic factors) the power and the power of the input size
.
Here we improve the power of in both bounds. For the upper bound, we
introduce a recursion technique, that together with a refinement of the methods
in the original work provides a test for any power of larger than .
For the lower bound, we introduce a new problem called Truestring Equivalence,
which is easily reducible to the -type Dyck language property testing
problem. For this new problem, we show a lower bound of to the power of
Testing Low Complexity Affine-Invariant Properties
Invariance with respect to linear or affine transformations of the domain is
arguably the most common symmetry exhibited by natural algebraic properties. In
this work, we show that any low complexity affine-invariant property of
multivariate functions over finite fields is testable with a constant number of
queries. This immediately reproves, for instance, that the Reed-Muller code
over F_p of degree d < p is testable, with an argument that uses no detailed
algebraic information about polynomials except that low degree is preserved by
composition with affine maps.
The complexity of an affine-invariant property P refers to the maximum
complexity, as defined by Green and Tao (Ann. Math. 2008), of the sets of
linear forms used to characterize P. A more precise statement of our main
result is that for any fixed prime p >=2 and fixed integer R >= 2, any
affine-invariant property P of functions f: F_p^n -> [R] is testable, assuming
the complexity of the property is less than p. Our proof involves developing
analogs of graph-theoretic techniques in an algebraic setting, using tools from
higher-order Fourier analysis.Comment: 38 pages, appears in SODA '1
Hardness and Algorithms for Rainbow Connectivity
An edge-colored graph G is rainbow connected if any two vertices are
connected by a path whose edges have distinct colors. The rainbow connectivity
of a connected graph G, denoted rc(G), is the smallest number of colors that
are needed in order to make G rainbow connected. In addition to being a natural
combinatorial problem, the rainbow connectivity problem is motivated by
applications in cellular networks. In this paper we give the first proof that
computing rc(G) is NP-Hard. In fact, we prove that it is already NP-Complete to
decide if rc(G) = 2, and also that it is NP-Complete to decide whether a given
edge-colored (with an unbounded number of colors) graph is rainbow connected.
On the positive side, we prove that for every > 0, a connected graph
with minimum degree at least has bounded rainbow connectivity,
where the bound depends only on , and the corresponding coloring can
be constructed in polynomial time. Additional non-trivial upper bounds, as well
as open problems and conjectures are also pre sented
On the Power of Conditional Samples in Distribution Testing
In this paper we define and examine the power of the {\em
conditional-sampling} oracle in the context of distribution-property testing.
The conditional-sampling oracle for a discrete distribution takes as
input a subset of the domain, and outputs a random sample drawn according to , conditioned on (and independently of all
prior samples). The conditional-sampling oracle is a natural generalization of
the ordinary sampling oracle in which always equals .
We show that with the conditional-sampling oracle, testing uniformity,
testing identity to a known distribution, and testing any label-invariant
property of distributions is easier than with the ordinary sampling oracle. On
the other hand, we also show that for some distribution properties the
sample-complexity remains near-maximal even with conditional sampling
New Results on Quantum Property Testing
We present several new examples of speed-ups obtainable by quantum algorithms
in the context of property testing. First, motivated by sampling algorithms, we
consider probability distributions given in the form of an oracle
. Here the probability \PP_f(j) of an outcome is the
fraction of its domain that maps to . We give quantum algorithms for
testing whether two such distributions are identical or -far in
-norm. Recently, Bravyi, Hassidim, and Harrow \cite{BHH10} showed that if
\PP_f and \PP_g are both unknown (i.e., given by oracles and ), then
this testing can be done in roughly quantum queries to the
functions. We consider the case where the second distribution is known, and
show that testing can be done with roughly quantum queries, which we
prove to be essentially optimal. In contrast, it is known that classical
testing algorithms need about queries in the unknown-unknown case and
about queries in the known-unknown case. Based on this result, we
also reduce the query complexity of graph isomorphism testers with quantum
oracle access. While those examples provide polynomial quantum speed-ups, our
third example gives a much larger improvement (constant quantum queries vs
polynomial classical queries) for the problem of testing periodicity, based on
Shor's algorithm and a modification of a classical lower bound by Lachish and
Newman \cite{lachish&newman:periodicity}. This provides an alternative to a
recent constant-vs-polynomial speed-up due to Aaronson \cite{aaronson:bqpph}.Comment: 2nd version: updated some references, in particular to Aaronson's
Fourier checking proble
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