On the Quantum Query Complexity of Local Search in Two and Three Dimensions

The quantum query complexity of searching for local optima has been a subject of much interest in the recent literature. For the d-dimensional grid graphs, the complexity has been determined asymptotically for all fixed d≥5, but the lower dimensional cases present special difficulties, and considerable gaps exist in our knowledge. In the present paper we present near-optimal lower bounds, showing that the quantum query complexity for the 2-dimensional grid [n]² is Ω(n ^1/2?δ ), and that for the 3-dimensional grid [n]³ is Ω(n ^1?δ ), for any fixed δ>0.A general lower bound approach for this problem, initiated by Aaronson (based on Ambainis’ adversary method for quantum lower bounds), uses random walks with low collision probabilities. This approach encounters obstacles in deriving tight lower bounds in low dimensions due to the lack of degrees of freedom in such spaces. We solve this problem by the novel construction and analysis of random walks with non-uniform step lengths. The proof employs in a nontrivial way sophisticated results of Sárközy and Szemerédi, Bose and Chowla, and Halász from combinatorial number theory, as well as less familiar probability tools like Esseen’s Inequality.     

Unbounded-error quantum query complexity

This work studies the quantum query complexity of Boolean functions in an unbounded-error scenario where it is only required that the query algorithm succeeds with a probability strictly greater than 1/2. We show that, just as in the communication complexity model, the unbounded-error quantum query complexity is exactly half of its classical counterpart for any (partial or total) Boolean function. Moreover, connecting the query and communication complexity results, we show that the “black-box” approach to convert quantum query algorithms into communication protocols by Buhrman-Cleve—Wigderson [STOC’98] is optimal even in the unbounded-error setting.We also study a related setting, called the weakly unbounded-error setting, where the cost of a query algorithm is given by q+log(1/2(p−1/2)), where q is the number of queries made and p>1/2 is the success probability of the algorithm. In contrast to the case of communication complexity, we show a tight multiplicative Θ(logn) separation between quantum and classical query complexity in this setting for a partial Boolean function. The asymptotic equivalence between them is also shown for some well-studied total Boolean functions.     

Nonadaptive quantum query complexity

We study the power of nonadaptive quantum query algorithms, which are algorithms whose queries to the input do not depend on the result of previous queries. First, we show that any bounded-error nonadaptive quantum query algorithm that computes a total boolean function depending on n variables must make Ω(n) queries to the input in total. Second, we show that, if there exists a quantum algorithm that uses k nonadaptive oracle queries to learn which one of a set of m boolean functions it has been given, there exists a nonadaptive classical algorithm using queries to solve the same problem. Thus, in the nonadaptive setting, quantum algorithms for these tasks can achieve at most a very limited speed-up over classical query algorithms.     

Selection problems viaM-ary queries

It is well known that, for fixedk, to find thek-th largest ofn elementsn+(k?1)log₂ n+Θ(1) comparisons are necessary and sufficient. But do the same bounds apply if we use a different type of query? We show that the arity of the queries is relevant. In particular, we present upper and lower bounds for finding the maximum using 3-ary or 4-ary Boolean (YES/NO answers) queries. We also study general (e.g.,max, sort) 3-ary queries, and show bounds for finding the maximum and the second largest. For sort queries we show matching upper and lower bounds.     

Rigidity of a simple extended lower triangular matrix

For the all-ones lower triangular matrices, the upper and lower bounds on rigidity are known to match [P. Pudlak, Z. Vavrin, Computation of rigidity of order n²/r for one simple matrix, Comment Math. Univ. Carolin. 32 (2) (1991) 213-218]. In this short note, we apply these techniques to the all-ones extended lower triangular matrices, to obtain upper and lower bounds with a small gap between the two; we show that the rigidity is .     

A large lower bound on the query complexity of a simple boolean function

Combinatorial property testing, initiated formally by Goldreich, Goldwasser, and Ron (1998) and inspired by Rubinfeld and Sudan (1996), deals with the relaxation of decision problems. Given a property P the aim is to decide whether a given input satisfies the property P or is far from having the property. For a family of boolean functions f=(fn) the associated property is the set of 1-inputs of f. Here, the known lower bounds on the query complexity of properties identified by boolean functions representable by (very) restricted branching programs of small size is improved up to Ω(n1/2), where n is the input length.     

Comparing the strength of query types in property testing: The case of k-colorability

We study the power of four query models in the context of property testing in general graphs, where our main case study is the problem of testing k-colorability. Two query types, which have been studied extensively in the past, are pair queries and neighbor queries. The former corresponds to asking whether there is an edge between any particular pair of vertices, and the latter to asking for the i ^th neighbor of a particular vertex. We show that while for pair queries testing k-colorability requires a number of queries that is a monotone decreasing function in the average degree d, the query complexity in the case of neighbor queries remains roughly the same for every density and for large values of k. We also consider a combined model that allows both types of queries, and we propose a new, stronger, query model, related to the field of Group Testing. We give upper and lower bounds on the query complexity for one-sided error in all the models, where the bounds are nearly tight for three of the models. In some of the cases, our lower bounds extend to two-sided error algorithms. The problem of testing k-colorability was previously studied in the contexts of dense graphs and of sparse graphs, and in our proofs we unify approaches from those cases, and also provide some new tools and techniques that may be of independent interest.     

The communication complexity of the Hamming distance problem

We investigate the randomized and quantum communication complexity of the Hamming Distance problem, which is to determine if the Hamming distance between two n-bit strings is no less than a threshold d. We prove a quantum lower bound of Ω(d) qubits in the general interactive model with shared prior entanglement. We also construct a classical protocol of O(dlogd) bits in the restricted Simultaneous Message Passing model with public random coins, improving previous protocols of O(d²) bits [A.C.-C. Yao, On the power of quantum fingerprinting, in: Proceedings of the 35th Annual ACM Symposium on Theory of Computing, 2003, pp. 77-81], and O(dlogn) bits [D. Gavinsky, J. Kempe, R. de Wolf, Quantum communication cannot simulate a public coin, quant-ph/0411051, 2004].     

A nondeterministic space-time tradeoff for linear codes

We are interested in proving exponential lower bounds on the size of nondeterministic D-way branching programs computing functions in linear time, that is, in time at most kn for a constant k. Ajtai has proved such lower bounds for explicit functions over domains D of size about n, and Beame, Saks and Thathachar for functions over domains of size about k²². We prove an exponential lower bound ²Ω(n/ck) for an explicit function over substantially smaller domain D of size about k². Our function is a universal function of linear codes.     

Quantum Algorithms for Highly Structured Search Problems

We consider the problem of identifying a base k string given an oracle which returns information about the number of correct components in a query, specifically, the Hamming distance between the query and the solution, modulo r = max{2, 6 – k}. Classically this problem requires (nlog _r k) queries. For k {2, 3, 4}, we construct quantum algorithms requiring only a single quantum query. For k > 4, we show that O(k) quantum queries suffice. In both cases the quantum algorithms are optimal. PACS: 03.67.Lx     

Relativized collapsing between BPP and PH under stringent oracle access

We propose a new model of stringent oracle access defined for a general complexity class. For example, when comparing the power of two machine models relative to some oracle set X, we restrict that machines of both types ask queries from the same segment of the set X. In particular, for investigating polynomial-time (or polynomial-size) computability, we propose polynomial stringency, bounding query length to any fixed polynomial of input length. Under such stringent oracle access, we show an oracle G such that BPP^G = PH^G.     

Quasi-optimal upper bounds for simplex range searching and new zone theorems

This paper presents quasi-optimal upper bounds for simplex range searching. The problem is to preprocess a setP ofn points in ?^d so that, given any query simplexq, the points inP ∩q can be counted or reported efficiently. Ifm units of storage are available (n <m <n ^d ), then we show that it is possible to answer any query inO(n ^1+?/m ^1/d ) query time afterO(m ^1+?) preprocessing. This bound, which holds on a RAM or a pointer machine, is almost tight. We also show how to achieveO(logn) query time at the expense ofO(n ^d+?) storage for any fixed ? > 0. To fine-tune our results in the reporting case we also establish new zone theorems for arrangements and merged arrangements of planes in 3-space, which are of independent interest.     

On the uselessness of quantum queries

Given a prior probability distribution over a set of possible oracle functions, we define a number of queries to be useless for determining some property of the function if the probability that the function has the property is unchanged after the oracle responds to the queries. A familiar example is the parity of a uniformly random Boolean-valued function over {1,2,…,N}, for which N−1 classical queries are useless. We prove that if 2k classical queries are useless for some oracle problem, then k quantum queries are also useless. For such problems, which include classical threshold secret sharing schemes, our result also gives a new way to obtain a lower bound on the quantum query complexity, even in cases where neither the function nor the property to be determined is Boolean.     

Even faster parameterized cluster deletion and cluster editing

Cluster Deletion and Cluster Editing ask to transform a graph by at most k edge deletions or edge edits, respectively, into a cluster graph, i.e., disjoint union of cliques. Equivalently, a cluster graph has no conflict triples, i.e., two incident edges without a transitive edge. We solve the two problems in time O^?(k^1.415) and O^?(k^1.76), respectively. These results round off our earlier work by considerably improved time bounds. For Cluster Deletion we use a technique that cuts away small connected components that do no longer contribute to the exponential part of the time complexity. As this idea is simple and versatile, it may lead to improvements for several other parameterized graph problems. The improvement for Cluster Editing is achieved by using the full power of an earlier structure theorem for graphs where no edge is in three conflict triples.     

Computing sparse permanents faster

Bax and Franklin (2002) gave a randomized algorithm for exactly computing the permanent of any n×n zero-one matrix in expected time exp[−Ω(n1/3/(2lnn))]n². Building on their work, we show that for any constant C>0 there is a constant ?>0 such that the permanent of any n×n (real or complex) matrix with at most Cn nonzero entries can be computed in deterministic time n(2−?) and space O(n). This improves on the Ω(n²) runtime of Ryser's algorithm for computing the permanent of an arbitrary real or complex matrix.     

Reviewing bounds on the circuit size of the hardest functions

In this paper we review the known bounds for L(n), the circuit size complexity of the hardest Boolean function on n input bits. The best known bounds appear to be

     

Efficient evaluation of specific queries in constraint databases

Let F₁,…,Fs∈R[X₁,…,Xn] be polynomials of degree at most d, and suppose that F₁,…,Fs are represented by a division free arithmetic circuit of non-scalar complexity size L. Let A be the arrangement of Rn defined by F₁,…,Fs.For any point x∈Rn, we consider the task of determining the signs of the values F₁(x),…,Fs(x) (sign condition query) and the task of determining the connected component of A to which x belongs (point location query). By an extremely simple reduction to the well-known case where the polynomials F₁,…,Fs are affine linear (i.e., polynomials of degree one), we show first that there exists a database of (possibly enormous) size sO(L+n) which allows the evaluation of the sign condition query using only (Ln)^O(1)log(s) arithmetic operations. The key point of this paper is the proof that this upper bound is almost optimal.By the way, we show that the point location query can be evaluated using dO(n)log(s) arithmetic operations. Based on a different argument, analogous complexity upper-bounds are exhibited with respect to the bit-model in case that F₁,…,Fs belong to Z[X₁,…,Xn] and satisfy a certain natural genericity condition. Mutatis mutandis our upper-bound results may be applied to the sparse and dense representations of F₁,…,Fs.     

A note on the search for k elements via quantum walk

In this paper we use the quantum walk search scheme by Magniez et al. (2007) [13] to find k solutions of a search problem. We show that the quantum query complexity is at most of order times the number of queries to find one solution.