1,577 research outputs found
Quantum Property Testing
A language L has a property tester if there exists a probabilistic algorithm
that given an input x only asks a small number of bits of x and distinguishes
the cases as to whether x is in L and x has large Hamming distance from all y
in L. We define a similar notion of quantum property testing and show that
there exist languages with quantum property testers but no good classical
testers. We also show there exist languages which require a large number of
queries even for quantumly testing
Every locally characterized affine-invariant property is testable
Let F = F_p for any fixed prime p >= 2. An affine-invariant property is a
property of functions on F^n that is closed under taking affine transformations
of the domain. We prove that all affine-invariant property having local
characterizations are testable. In fact, we show a proximity-oblivious test for
any such property P, meaning that there is a test that, given an input function
f, makes a constant number of queries to f, always accepts if f satisfies P,
and rejects with positive probability if the distance between f and P is
nonzero. More generally, we show that any affine-invariant property that is
closed under taking restrictions to subspaces and has bounded complexity is
testable.
We also prove that any property that can be described as the property of
decomposing into a known structure of low-degree polynomials is locally
characterized and is, hence, testable. For example, whether a function is a
product of two degree-d polynomials, whether a function splits into a product
of d linear polynomials, and whether a function has low rank are all examples
of degree-structural properties and are therefore locally characterized.
Our results depend on a new Gowers inverse theorem by Tao and Ziegler for low
characteristic fields that decomposes any polynomial with large Gowers norm
into a function of low-degree non-classical polynomials. We establish a new
equidistribution result for high rank non-classical polynomials that drives the
proofs of both the testability results and the local characterization of
degree-structural properties
Property Testing via Set-Theoretic Operations
Given two testable properties and , under
what conditions are the union, intersection or set-difference of these two
properties also testable? We initiate a systematic study of these basic
set-theoretic operations in the context of property testing. As an application,
we give a conceptually different proof that linearity is testable, albeit with
much worse query complexity. Furthermore, for the problem of testing
disjunction of linear functions, which was previously known to be one-sided
testable with a super-polynomial query complexity, we give an improved analysis
and show it has query complexity O(1/\eps^2), where \eps is the distance
parameter.Comment: Appears in ICS 201
Testing Linear-Invariant Non-Linear Properties
We consider the task of testing properties of Boolean functions that are
invariant under linear transformations of the Boolean cube. Previous work in
property testing, including the linearity test and the test for Reed-Muller
codes, has mostly focused on such tasks for linear properties. The one
exception is a test due to Green for "triangle freeness": a function
f:\cube^{n}\to\cube satisfies this property if do not all
equal 1, for any pair x,y\in\cube^{n}.
Here we extend this test to a more systematic study of testing for
linear-invariant non-linear properties. We consider properties that are
described by a single forbidden pattern (and its linear transformations), i.e.,
a property is given by points v_{1},...,v_{k}\in\cube^{k} and
f:\cube^{n}\to\cube satisfies the property that if for all linear maps
L:\cube^{k}\to\cube^{n} it is the case that do
not all equal 1. We show that this property is testable if the underlying
matroid specified by is a graphic matroid. This extends
Green's result to an infinite class of new properties.
Our techniques extend those of Green and in particular we establish a link
between the notion of "1-complexity linear systems" of Green and Tao, and
graphic matroids, to derive the results.Comment: This is the full version; conference version appeared in the
proceedings of STACS 200
Deleting and Testing Forbidden Patterns in Multi-Dimensional Arrays
Understanding the local behaviour of structured multi-dimensional data is a
fundamental problem in various areas of computer science. As the amount of data
is often huge, it is desirable to obtain sublinear time algorithms, and
specifically property testers, to understand local properties of the data.
We focus on the natural local problem of testing pattern freeness: given a
large -dimensional array and a fixed -dimensional pattern over a
finite alphabet, we say that is -free if it does not contain a copy of
the forbidden pattern as a consecutive subarray. The distance of to
-freeness is the fraction of entries of that need to be modified to make
it -free. For any and any large enough pattern over
any alphabet, other than a very small set of exceptional patterns, we design a
tolerant tester that distinguishes between the case that the distance is at
least and the case that it is at most , with query
complexity and running time , where and
depend only on .
To analyze the testers we establish several combinatorial results, including
the following -dimensional modification lemma, which might be of independent
interest: for any large enough pattern over any alphabet (excluding a small
set of exceptional patterns for the binary case), and any array containing
a copy of , one can delete this copy by modifying one of its locations
without creating new -copies in .
Our results address an open question of Fischer and Newman, who asked whether
there exist efficient testers for properties related to tight substructures in
multi-dimensional structured data. They serve as a first step towards a general
understanding of local properties of multi-dimensional arrays, as any such
property can be characterized by a fixed family of forbidden patterns
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