16,956 research outputs found
Quantum Certificate Complexity
Given a Boolean function f, we study two natural generalizations of the
certificate complexity C(f): the randomized certificate complexity RC(f) and
the quantum certificate complexity QC(f). Using Ambainis' adversary method, we
exactly characterize QC(f) as the square root of RC(f). We then use this result
to prove the new relation R0(f) = O(Q2(f)^2 Q0(f) log n) for total f, where R0,
Q2, and Q0 are zero-error randomized, bounded-error quantum, and zero-error
quantum query complexities respectively. Finally we give asymptotic gaps
between the measures, including a total f for which C(f) is superquadratic in
QC(f), and a symmetric partial f for which QC(f) = O(1) yet Q2(f) = Omega(n/log
n).Comment: 9 page
On the Power of Non-Adaptive Learning Graphs
We introduce a notion of the quantum query complexity of a certificate
structure. This is a formalisation of a well-known observation that many
quantum query algorithms only require the knowledge of the disposition of
possible certificates in the input string, not the precise values therein.
Next, we derive a dual formulation of the complexity of a non-adaptive
learning graph, and use it to show that non-adaptive learning graphs are tight
for all certificate structures. By this, we mean that there exists a function
possessing the certificate structure and such that a learning graph gives an
optimal quantum query algorithm for it.
For a special case of certificate structures generated by certificates of
bounded size, we construct a relatively general class of functions having this
property. The construction is based on orthogonal arrays, and generalizes the
quantum query lower bound for the -sum problem derived recently in
arXiv:1206.6528.
Finally, we use these results to show that the learning graph for the
triangle problem from arXiv:1210.1014 is almost optimal in these settings. This
also gives a quantum query lower bound for the triangle-sum problem.Comment: 16 pages, 1.5 figures v2: the main result generalised for all
certificate structures, a bug in the proof of Proposition 17 fixe
Certificate games
We introduce and study Certificate Game complexity, a measure of complexity
based on the probability of winning a game where two players are given inputs
with different function values and are asked to output such that (zero-communication setting).
We give upper and lower bounds for private coin, public coin, shared
entanglement and non-signaling strategies, and give some separations. We show
that complexity in the public coin model is upper bounded by Randomized query
and Certificate complexity. On the other hand, it is lower bounded by
fractional and randomized certificate complexity, making it a good candidate to
prove strong lower bounds on randomized query complexity. Complexity in the
private coin model is bounded from below by zero-error randomized query
complexity.
The quantum measure highlights an interesting and surprising difference
between classical and quantum query models. Whereas the public coin certificate
game complexity is bounded from above by randomized query complexity, the
quantum certificate game complexity can be quadratically larger than quantum
query complexity. We use non-signaling, a notion from quantum information, to
give a lower bound of on the quantum certificate game complexity of the
function, whose quantum query complexity is , then go on
to show that this ``non-signaling bottleneck'' applies to all functions with
high sensitivity, block sensitivity or fractional block sensitivity.
We consider the single-bit version of certificate games (inputs of the two
players have Hamming distance ). We prove that the single-bit version of
certificate game complexity with shared randomness is equal to sensitivity up
to constant factors, giving a new characterization of sensitivity. The
single-bit version with private randomness is equal to , where
is the spectral sensitivity.Comment: 43 pages, 1 figure, ITCS202
Low-Sensitivity Functions from Unambiguous Certificates
We provide new query complexity separations against sensitivity for total
Boolean functions: a power separation between deterministic (and even
randomized or quantum) query complexity and sensitivity, and a power
separation between certificate complexity and sensitivity. We get these
separations by using a new connection between sensitivity and a seemingly
unrelated measure called one-sided unambiguous certificate complexity
(). We also show that is lower-bounded by fractional block
sensitivity, which means we cannot use these techniques to get a
super-quadratic separation between and . We also provide a
quadratic separation between the tree-sensitivity and decision tree complexity
of Boolean functions, disproving a conjecture of Gopalan, Servedio, Tal, and
Wigderson (CCC 2016).
Along the way, we give a power separation between certificate
complexity and one-sided unambiguous certificate complexity, improving the
power separation due to G\"o\"os (FOCS 2015). As a consequence, we
obtain an improved lower-bound on the
co-nondeterministic communication complexity of the Clique vs. Independent Set
problem.Comment: 25 pages. This version expands the results and adds Pooya Hatami and
Avishay Tal as author
Quantum Proofs
Quantum information and computation provide a fascinating twist on the notion
of proofs in computational complexity theory. For instance, one may consider a
quantum computational analogue of the complexity class \class{NP}, known as
QMA, in which a quantum state plays the role of a proof (also called a
certificate or witness), and is checked by a polynomial-time quantum
computation. For some problems, the fact that a quantum proof state could be a
superposition over exponentially many classical states appears to offer
computational advantages over classical proof strings. In the interactive proof
system setting, one may consider a verifier and one or more provers that
exchange and process quantum information rather than classical information
during an interaction for a given input string, giving rise to quantum
complexity classes such as QIP, QSZK, and QMIP* that represent natural quantum
analogues of IP, SZK, and MIP. While quantum interactive proof systems inherit
some properties from their classical counterparts, they also possess distinct
and uniquely quantum features that lead to an interesting landscape of
complexity classes based on variants of this model.
In this survey we provide an overview of many of the known results concerning
quantum proofs, computational models based on this concept, and properties of
the complexity classes they define. In particular, we discuss non-interactive
proofs and the complexity class QMA, single-prover quantum interactive proof
systems and the complexity class QIP, statistical zero-knowledge quantum
interactive proof systems and the complexity class \class{QSZK}, and
multiprover interactive proof systems and the complexity classes QMIP, QMIP*,
and MIP*.Comment: Survey published by NOW publisher
Quantum Discord and Quantum Computing - An Appraisal
We discuss models of computing that are beyond classical. The primary
motivation is to unearth the cause of nonclassical advantages in computation.
Completeness results from computational complexity theory lead to the
identification of very disparate problems, and offer a kaleidoscopic view into
the realm of quantum enhancements in computation. Emphasis is placed on the
`power of one qubit' model, and the boundary between quantum and classical
correlations as delineated by quantum discord. A recent result by Eastin on the
role of this boundary in the efficient classical simulation of quantum
computation is discussed. Perceived drawbacks in the interpretation of quantum
discord as a relevant certificate of quantum enhancements are addressed.Comment: To be published in the Special Issue of the International Journal of
Quantum Information on "Quantum Correlations: entanglement and beyond." 11
pages, 4 figure
On the Power of Non-adaptive Learning Graphs
We introduce a notion of the quantum query complexity of a certificate structure. This is a formalization of a well-known observation that many quantum query algorithms only require the knowledge of the position of possible certificates in the input string, not the precise values therein.
Next, we derive a dual formulation of the complexity of a non-adaptive learning graph and use it to show that non-adaptive learning graphs are tight for all certificate structures. By this, we mean that there exists a function possessing the certificate structure such that a learning graph gives an optimal quantum query algorithm for it.
For a special case of certificate structures generated by certificates of bounded size, we construct a relatively general class of functions having this property. The construction is based on orthogonal arrays and generalizes the quantum query lower bound for the k-sum problem derived recently by Belovs and Špalek (Proceeding of 4th ACM ITCS, 323–328, 2013).
Finally, we use these results to show that the learning graph for the triangle problem by Lee et al. (Proceeding of 24th ACM-SIAM SODA, 1486–1502, 2013) is almost optimal in the above settings. This also gives a quantum query lower bound for the triangle sum problem.National Science Foundation (U.S.) (Scott Aaronson’s Alan T. Waterman Award
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