Search results for " Complexity"

showing 10 items of 623 documents

Classical automata on promise problems

2015

Promise problems were mainly studied in quantum automata theory. Here we focus on state complexity of classical automata for promise problems. First, it was known that there is a family of unary promise problems solvable by quantum automata by using a single qubit, but the number of states required by corresponding one-way deterministic automata cannot be bounded by a constant. For this family, we show that even two-way nondeterminism does not help to save a single state. By comparing this with the corresponding state complexity of alternating machines, we then get a tight exponential gap between two-way nondeterministic and one-way alternating automata solving unary promise problems. Secon…

FOS: Computer and information sciencesNested wordTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESUnary operationGeneral Computer ScienceFormal Languages and Automata Theory (cs.FL)nondeterministic automataComputer Science - Formal Languages and Automata Theoryω-automatonComputational Complexity (cs.CC)Theoretical Computer ScienceContinuous spatial automatonQuantum finite automataDiscrete Mathematics and Combinatoricsalternating automatapromise problemsMathematicsprobabilistic automataNonlinear Sciences::Cellular Automata and Lattice GasesMobile automatonNondeterministic algorithmAlgebra[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]Computer Science - Computational ComplexityTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESAutomata theorydescriptional complexityComputer Science::Formal Languages and Automata Theory
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Exact quantum algorithms have advantage for almost all Boolean functions

2014

It has been proved that almost all $n$-bit Boolean functions have exact classical query complexity $n$. However, the situation seemed to be very different when we deal with exact quantum query complexity. In this paper, we prove that almost all $n$-bit Boolean functions can be computed by an exact quantum algorithm with less than $n$ queries. More exactly, we prove that ${AND}_n$ is the only $n$-bit Boolean function, up to isomorphism, that requires $n$ queries.

FOS: Computer and information sciencesNuclear and High Energy Physics81P68 03D15Parity functionBoolean circuitGeneral Physics and AstronomyFOS: Physical sciencesBoolean algebras canonically definedComputational Complexity (cs.CC)Theoretical Computer ScienceCombinatoricsBoolean expressionBoolean functionMathematical PhysicsComputer Science::DatabasesMathematicsDiscrete mathematicsSymmetric Boolean functionQuantum PhysicsProduct termComputer Science::Information RetrievalStatistical and Nonlinear PhysicsComputer Science - Computational ComplexityComputational Theory and MathematicsMaximum satisfiability problemQuantum Physics (quant-ph)
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Quantum lower bound for inverting a permutation with advice

2014

Given a random permutation $f: [N] \to [N]$ as a black box and $y \in [N]$, we want to output $x = f^{-1}(y)$. Supplementary to our input, we are given classical advice in the form of a pre-computed data structure; this advice can depend on the permutation but \emph{not} on the input $y$. Classically, there is a data structure of size $\tilde{O}(S)$ and an algorithm that with the help of the data structure, given $f(x)$, can invert $f$ in time $\tilde{O}(T)$, for every choice of parameters $S$, $T$, such that $S\cdot T \ge N$. We prove a quantum lower bound of $T^2\cdot S \ge \tilde{\Omega}(\epsilon N)$ for quantum algorithms that invert a random permutation $f$ on an $\epsilon$ fraction of…

FOS: Computer and information sciencesNuclear and High Energy PhysicsComputer Science - Cryptography and SecurityGeneral Physics and AstronomyFOS: Physical sciencesOne-way functionComputational Complexity (cs.CC)Upper and lower boundsTheoretical Computer ScienceCyclic permutationCombinatoricsPermutationMathematical PhysicsMathematicsDiscrete mathematicsQuantum PhysicsBit-reversal permutationStatistical and Nonlinear PhysicsRandom permutationComputer Science - Computational ComplexityComputational Theory and MathematicsQuantum algorithmQuantum Physics (quant-ph)Advice (complexity)Cryptography and Security (cs.CR)MathematicsofComputing_DISCRETEMATHEMATICS
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Whom to befriend to influence people

2020

Alice wants to join a new social network, and influence its members to adopt a new product or idea. Each person $v$ in the network has a certain threshold $t(v)$ for {\em activation}, i.e adoption of the product or idea. If $v$ has at least $t(v)$ activated neighbors, then $v$ will also become activated. If Alice wants to activate the entire social network, whom should she befriend? More generally, we study the problem of finding the minimum number of links that a set of external influencers should form to people in the network, in order to activate the entire social network. This {\em Minimum Links} Problem has applications in viral marketing and the study of epidemics. Its solution can be…

FOS: Computer and information sciencesPhysics - Physics and SocietyGeneral Computer ScienceFOS: Physical sciencesPhysics and Society (physics.soc-ph)0102 computer and information sciences02 engineering and technology01 natural sciencesSocial networksGraphTheoretical Computer ScienceCombinatoricsComputer Science - Data Structures and AlgorithmsGreedy algorithmFOS: Mathematics0202 electrical engineering electronic engineering information engineeringMathematics - CombinatoricsData Structures and Algorithms (cs.DS)Greedy algorithmTime complexityNP-completeMathematicsSocial and Information Networks (cs.SI)Social networkDiscrete mathematicsBinary treeDegree (graph theory)Computer Science (all)Order (ring theory)Computer Science - Social and Information NetworksJoin (topology)Influence maximizationGreedy algorithms010201 computation theory & mathematicsGraphs; Greedy algorithms; Influence maximization; NP-complete; Social networksProduct (mathematics)020201 artificial intelligence & image processingCombinatorics (math.CO)Constant (mathematics)GraphsTheoretical Computer Science
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Classical and Quantum Annealing in the Median of Three Satisfiability

2011

We determine the classical and quantum complexities of a specific ensemble of three-satisfiability problems with a unique satisfying assignment for up to N = 100 and 80 variables, respectively. In the classical limit, we employ generalized ensemble techniques and measure the time that a Markovian Monte Carlo process spends in searching classical ground states. In the quantum limit, we determine the maximum finite correlation length along a quantum adiabatic trajectory determined by the linear sweep of the adiabatic control parameter in the Hamiltonian composed of the problem Hamiltonian and the constant transverse field Hamiltonian. In the median of our ensemble, both complexities diverge e…

FOS: Computer and information sciencesPolynomialComputational complexity theoryQuantum dynamicsFOS: Physical sciencesComputational Complexity (cs.CC)Classical limitClassical capacityQuantum mechanicsddc:530Statistical physicsALGORITHMAmplitude damping channelQuantumQuantum fluctuationCondensed Matter - Statistical MechanicsMathematicsPhysicsQuantum PhysicsStatistical Mechanics (cond-mat.stat-mech)Stochastic processQuantum annealingAdiabatic quantum computationAtomic and Molecular Physics and OpticsSatisfiabilityJComputer Science - Computational ComplexityComputerSystemsOrganization_MISCELLANEOUSQuantum algorithmPHASE-TRANSITIONSQuantum dissipationQuantum Physics (quant-ph)
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Search by quantum walks on two-dimensional grid without amplitude amplification

2011

We study search by quantum walk on a finite two dimensional grid. The algorithm of Ambainis, Kempe, Rivosh (quant-ph/0402107) takes O(\sqrt{N log N}) steps and finds a marked location with probability O(1/log N) for grid of size \sqrt{N} * \sqrt{N}. This probability is small, thus amplitude amplification is needed to achieve \Theta(1) success probability. The amplitude amplification adds an additional O(\sqrt{log N}) factor to the number of steps, making it O(\sqrt{N} log N). In this paper, we show that despite a small probability to find a marked location, the probability to be within an O(\sqrt{N}) neighbourhood (at an O(\sqrt[4]{N}) distance) of the marked location is \Theta(1). This all…

FOS: Computer and information sciencesQuantum PhysicsComputer Science - Computational ComplexityComputer Science - Data Structures and AlgorithmsFOS: Physical sciencesData Structures and Algorithms (cs.DS)Computational Complexity (cs.CC)Nuclear ExperimentQuantum Physics (quant-ph)
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Quantum-over-classical Advantage in Solving Multiplayer Games

2020

We study the applicability of quantum algorithms in computational game theory and generalize some results related to Subtraction games, which are sometimes referred to as one-heap Nim games. In quantum game theory, a subset of Subtraction games became the first explicitly defined class of zero-sum combinatorial games with provable separation between quantum and classical complexity of solving them. For a narrower subset of Subtraction games, an exact quantum sublinear algorithm is known that surpasses all deterministic algorithms for finding solutions with probability $1$. Typically, both Nim and Subtraction games are defined for only two players. We extend some known results to games for t…

FOS: Computer and information sciencesQuantum PhysicsComputer Science - Computational ComplexityComputer Science::Computer Science and Game TheoryComputer Science - Computer Science and Game TheoryComputingMilieux_PERSONALCOMPUTINGFOS: Physical sciencesComputational Complexity (cs.CC)Quantum Physics (quant-ph)Computer Science and Game Theory (cs.GT)
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Parameterized Quantum Query Complexity of Graph Collision

2013

We present three new quantum algorithms in the quantum query model for \textsc{graph-collision} problem: \begin{itemize} \item an algorithm based on tree decomposition that uses $O\left(\sqrt{n}t^{\sfrac{1}{6}}\right)$ queries where $t$ is the treewidth of the graph; \item an algorithm constructed on a span program that improves a result by Gavinsky and Ito. The algorithm uses $O(\sqrt{n}+\sqrt{\alpha^{**}})$ queries, where $\alpha^{**}(G)$ is a graph parameter defined by \[\alpha^{**}(G):=\min_{VC\text{-- vertex cover of}G}{\max_{\substack{I\subseteq VC\\I\text{-- independent set}}}{\sum_{v\in I}{\deg{v}}}};\] \item an algorithm for a subclass of circulant graphs that uses $O(\sqrt{n})$ qu…

FOS: Computer and information sciencesQuantum PhysicsComputer Science - Computational ComplexityComputer Science::Information RetrievalComputer Science - Data Structures and AlgorithmsFOS: Physical sciencesData Structures and Algorithms (cs.DS)Computational Complexity (cs.CC)Quantum Physics (quant-ph)MathematicsofComputing_DISCRETEMATHEMATICS
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New Developments in Quantum Algorithms

2010

In this survey, we describe two recent developments in quantum algorithms. The first new development is a quantum algorithm for evaluating a Boolean formula consisting of AND and OR gates of size N in time O(\sqrt{N}). This provides quantum speedups for any problem that can be expressed via Boolean formulas. This result can be also extended to span problems, a generalization of Boolean formulas. This provides an optimal quantum algorithm for any Boolean function in the black-box query model. The second new development is a quantum algorithm for solving systems of linear equations. In contrast with traditional algorithms that run in time O(N^{2.37...}) where N is the size of the system, the …

FOS: Computer and information sciencesQuantum PhysicsComputer Science - Computational ComplexityComputerSystemsOrganization_MISCELLANEOUSComputer Science - Data Structures and AlgorithmsFOS: Physical sciencesTheoryofComputation_GENERALData Structures and Algorithms (cs.DS)Computational Complexity (cs.CC)Quantum Physics (quant-ph)
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Quantum property testing for bounded-degree graphs

2010

We study quantum algorithms for testing bipartiteness and expansion of bounded-degree graphs. We give quantum algorithms that solve these problems in time O(N^(1/3)), beating the Omega(sqrt(N)) classical lower bound. For testing expansion, we also prove an Omega(N^(1/4)) quantum query lower bound, thus ruling out the possibility of an exponential quantum speedup. Our quantum algorithms follow from a combination of classical property testing techniques due to Goldreich and Ron, derandomization, and the quantum algorithm for element distinctness. The quantum lower bound is obtained by the polynomial method, using novel algebraic techniques and combinatorial analysis to accommodate the graph s…

FOS: Computer and information sciencesQuantum PhysicsComputer Science - Computational ComplexityComputerSystemsOrganization_MISCELLANEOUSTheoryofComputation_GENERALFOS: Physical sciencesComputational Complexity (cs.CC)Quantum Physics (quant-ph)
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