101 research outputs found
Optimal Quantum Sample Complexity of Learning Algorithms
In learning theory, the VC dimension of a
concept class is the most common way to measure its "richness." In the PAC
model \Theta\Big(\frac{d}{\eps} + \frac{\log(1/\delta)}{\eps}\Big)
examples are necessary and sufficient for a learner to output, with probability
, a hypothesis that is \eps-close to the target concept . In
the related agnostic model, where the samples need not come from a , we
know that \Theta\Big(\frac{d}{\eps^2} + \frac{\log(1/\delta)}{\eps^2}\Big)
examples are necessary and sufficient to output an hypothesis whose
error is at most \eps worse than the best concept in .
Here we analyze quantum sample complexity, where each example is a coherent
quantum state. This model was introduced by Bshouty and Jackson, who showed
that quantum examples are more powerful than classical examples in some
fixed-distribution settings. However, Atici and Servedio, improved by Zhang,
showed that in the PAC setting, quantum examples cannot be much more powerful:
the required number of quantum examples is
\Omega\Big(\frac{d^{1-\eta}}{\eps} + d + \frac{\log(1/\delta)}{\eps}\Big)\mbox{
for all }\eta> 0. Our main result is that quantum and classical sample
complexity are in fact equal up to constant factors in both the PAC and
agnostic models. We give two approaches. The first is a fairly simple
information-theoretic argument that yields the above two classical bounds and
yields the same bounds for quantum sample complexity up to a \log(d/\eps)
factor. We then give a second approach that avoids the log-factor loss, based
on analyzing the behavior of the "Pretty Good Measurement" on the quantum state
identification problems that correspond to learning. This shows classical and
quantum sample complexity are equal up to constant factors.Comment: 31 pages LaTeX. Arxiv abstract shortened to fit in their
1920-character limit. Version 3: many small changes, no change in result
Optimizing the Number of Gates in Quantum Search
In its usual form, Grover's quantum search algorithm uses
queries and other elementary gates to find a solution in
an -bit database. Grover in 2002 showed how to reduce the number of other
gates to for the special case where the database has a
unique solution, without significantly increasing the number of queries. We
show how to reduce this further to gates for any
constant , and sufficiently large . This means that, on average, the
gates between two queries barely touch more than a constant number of the qubits on which the algorithm acts. For a very large that is a power of
2, we can choose such that the algorithm uses essentially the minimal
number of queries, and only
other gates.Comment: 11 pages LaTeX. Version 2: small improvements in the proof
A Survey of Quantum Learning Theory
This paper surveys quantum learning theory: the theoretical aspects of
machine learning using quantum computers. We describe the main results known
for three models of learning: exact learning from membership queries, and
Probably Approximately Correct (PAC) and agnostic learning from classical or
quantum examples.Comment: 26 pages LaTeX. v2: many small changes to improve the presentation.
This version will appear as Complexity Theory Column in SIGACT News in June
2017. v3: fixed a small ambiguity in the definition of gamma(C) and updated a
referenc
Quantum Query Algorithms are Completely Bounded Forms
We prove a characterization of -query quantum algorithms in terms of the
unit ball of a space of degree- polynomials. Based on this, we obtain a
refined notion of approximate polynomial degree that equals the quantum query
complexity, answering a question of Aaronson et al. (CCC'16). Our proof is
based on a fundamental result of Christensen and Sinclair (J. Funct. Anal.,
1987) that generalizes the well-known Stinespring representation for quantum
channels to multilinear forms. Using our characterization, we show that many
polynomials of degree four are far from those coming from two-query quantum
algorithms. We also give a simple and short proof of one of the results of
Aaronson et al. showing an equivalence between one-query quantum algorithms and
bounded quadratic polynomials.Comment: 24 pages, 3 figures. v2: 27 pages, minor changes in response to
referee comment
The asymptotic induced matching number of hypergraphs: balanced binary strings
We compute the asymptotic induced matching number of the -partite
-uniform hypergraphs whose edges are the -bit strings of Hamming weight
, for any large enough even number . Our lower bound relies on the
higher-order extension of the well-known Coppersmith-Winograd method from
algebraic complexity theory, which was proven by Christandl, Vrana and Zuiddam.
Our result is motivated by the study of the power of this method as well as of
the power of the Strassen support functionals (which provide upper bounds on
the asymptotic induced matching number), and the connections to questions in
tensor theory, quantum information theory and theoretical computer science.
Phrased in the language of tensors, as a direct consequence of our result, we
determine the asymptotic subrank of any tensor with support given by the
aforementioned hypergraphs. In the context of quantum information theory, our
result amounts to an asymptotically optimal -party stochastic local
operations and classical communication (slocc) protocol for the problem of
distilling GHZ-type entanglement from a subfamily of Dicke-type entanglement
Quantum hedging in two-round prover-verifier interactions
We consider the problem of a particular kind of quantum correlation that
arises in some two-party games. In these games, one player is presented with a
question they must answer, yielding an outcome of either 'win' or 'lose'.
Molina and Watrous (arXiv:1104.1140) studied such a game that exhibited a
perfect form of hedging, where the risk of losing a first game can completely
offset the corresponding risk for a second game. This is a non-classical
quantum phenomenon, and establishes the impossibility of performing strong
error-reduction for quantum interactive proof systems by parallel repetition,
unlike for classical interactive proof systems. We take a step in this article
towards a better understanding of the hedging phenomenon by giving a complete
characterization of when perfect hedging is possible for a natural
generalization of the game in arXiv:1104.1140. Exploring in a different
direction the subject of quantum hedging, and motivated by implementation
concerns regarding loss-tolerance, we also consider a variation of the protocol
where the player who receives the question can choose to restart the game
rather than return an answer. We show that in this setting there is no possible
hedging for any game played with state spaces corresponding to
finite-dimensional complex Euclidean spaces.Comment: 34 pages, 1 figure. Added work on connections with other result
Quantum Query Algorithms are Completely Bounded Forms
We prove a characterization of quantum query algorithms in terms of polynomials satisfying a certain (completely bounded) norm constraint. Based on this, we obtain a refined notion of approximate polynomial degree that equals the quantum query complexity, answering a question of Aaronson et al. (CCC\u2716). Using this characterization, we show that many polynomials of degree at least 4 are far from those coming from quantum query algorithms.
Our proof is based on a fundamental result of Christensen and Sinclair (J. Funct. Anal., 1987) that generalizes the well-known Stinespring representation for quantum channels to multilinear forms.
We also give a simple and short proof of one of the results of Aaronson et al. showing an equivalence between one-query quantum algorithms and bounded quadratic polynomials
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