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.     

Quantum implicit computational complexity

We introduce a quantum lambda calculus inspired by Lafont’s Soft Linear Logic and capturing the polynomial quantum complexity classes EQP, BQP and ZQP. The calculus is based on the “classical control and quantum data” paradigm. This is the first example of a formal system capturing quantum complexity classes in the spirit of implicit computational complexity — it is machine-free and no explicit bound (e.g., polynomials) appears in its syntax.     

On the arithmetic complexity of matrix Kronecker powers

In this paper we study the arithmetic complexity of computing the pth Kronecker power of an n × n matrix. We first analyze a straightforward inductive computation which requires an asymptotic average of p multiplications and p – 1 additions per computed output. We then apply efficient methods for matrix multiplication to obtain an algorithm that achieves the optimal rate of one multiplication per output at the expense of increasing the number of additions, and an algorithm that requires O(log p) multiplications and O(log²p) additions per output.     

Entropy and algorithmic complexity in quantum information theory

A theorem of Brudno says that the entropy production of classical ergodic information sources equals the algorithmic complexity per symbol of almost every sequence emitted by such sources. The recent advances in the theory and technology of quantum information raise the question whether a same relation may hold for ergodic quantum sources. In this paper, we discuss a quantum generalization of Brudno’s result which connects the von Neumann entropy rate and a recently proposed quantum algorithmic complexity.     

The quantum query complexity of the hidden subgroup problem is polynomial

We present a quantum algorithm which identifies with certainty a hidden subgroup of an arbitrary finite group G in only a polynomial (in log|G|) number of calls to the oracle. This is exponentially better than the best classical algorithm. However our quantum algorithm requires exponential time, as in the classical case. Our algorithm utilizes a new technique for constructing error-free algorithms for non-decision problems on quantum computers.     

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.     

Quantum computing – Facts and folklore

We represent and analyze two important quantumalgorithms – Finding the hidden subgroup and Grover search. As theanalysis goes on, we mention some pieces of ``Fact' and ``Folklore'associated to quantum computing.     

The quantum query complexity of the determinant

In this paper we give tight quantum query complexity bounds of some important linear algebra problems. We prove Θ(n²) quantum query bounds for verify the determinant, rank, matrix inverse and the matrix power problem.     

On the algebraic complexity of set equality and inclusion

We present a linear-time algorithm in the algebraic computation tree model for checking whether two sets of integers are equal. The significance of this result is in the fact that it shows that set equality testing is computationally easier when the elements of the sets are restricted to be integers. In addition, we show a linear-time algorithm for checking set inclusion in a slightly extended computational model.     

On the computational complexity of combinatorial flexibility problems

The concept of flexibility – originated in the context of heat exchanger networks design – is associated with a substructure which allows the same optimal value on the substructure (for example an optimal flow) as in the whole structure, for all the costs in a given range of costs. In this work, we extend the concept of flexibility to general combinatorial optimization problems, and prove several computational complexity results in this new framework. Under some monotonicity conditions, we prove that a combinatorial optimization problem can be polynomially reduced to its associated flexibility problem. However, the minimum cut, maximum weighted matching and shortest path problems have NP-complete associated flexibility problems. In order to obtain polynomial flexibility problems, we have to restrict ourselves to combinatorial optimization problems on matroids.     

An overview of quantum computation models: quantum automata

Quantum automata, as theoretical models of quantum computers, include quantum finite automata (QFA), quantum sequential machines (QSM), quantum pushdown automata (QPDA), quantum Turing machines (QTM), quantum cellular automata (QCA), and the others, for example, automata theory based on quantum logic (orthomodular lattice-valued automata). In this paper, we try to outline a basic progress in the research on these models, focusing on QFA, QSM, QPDA, QTM, and orthomodular lattice-valued automata. Also, other models closely relative to them are mentioned. In particular, based on the existing results in the literature, we finally address a number of problems to be studied in future.     

Compositional and holistic quantum computational semantics

In quantum computational logic meanings of sentences are identified with quantum information quantities: systems of qubits or, more generally, mixtures of systems of qubits. We consider two kinds of quantum computational semantics: (1) a compositional semantics, where the meaning of a compound sentence is determined by the meanings of its parts; (2) a holistic semantics, which makes essential use of the characteristic “holistic” features of the quantum-theoretic formalism. We prove that the compositional and the holistic semantics characterize the same logic.     

The complexity of agent design problems: Determinism and history dependence

The agent design problem is as follows: given a specification of an environment, together with a specification of a task, is it possible to construct an agent that can be guaranteed to successfully accomplish the task in the environment? In this article, we study the computational complexity of the agent design problem for tasks that are of the form “achieve this state of affairs” or “maintain this state of affairs.” We consider three general formulations of these problems (in both non-deterministic and deterministic environments) that differ in the nature of what is viewed as an “acceptable” solution: in the least restrictive formulation, no limit is placed on the number of actions an agent is allowed to perform in attempting to meet the requirements of its specified task. We show that the resulting decision problems are intractable, in the sense that these are non-recursive (but recursively enumerable) for achievement tasks, and non-recursively enumerable for maintenance tasks. In the second formulation, the decision problem addresses the existence of agents that have satisfied their specified task within some given number of actions. Even in this more restrictive setting the resulting decision problems are either pspace-complete or np-complete. Our final formulation requires the environment to be history independent and bounded. In these cases polynomial time algorithms exist: for deterministic environments the decision problems are nl-complete; in non-deterministic environments, p-complete.     

A characterization of average case communication complexity

It is well known that the average case deterministic communication complexity is bounded below by an entropic quantity, which one would now call deterministic information complexity. In this paper we show a corresponding upper bound. We also improve known lower bounds for the public coin Las Vegas communication complexity by a constant factor.