Search results for "Quantum algorithm"

showing 10 items of 103 documents

Quantum algorithm for tree size estimation, with applications to backtracking and 2-player games

2017

We study quantum algorithms on search trees of unknown structure, in a model where the tree can be discovered by local exploration. That is, we are given the root of the tree and access to a black box which, given a vertex $v$, outputs the children of $v$. We construct a quantum algorithm which, given such access to a search tree of depth at most $n$, estimates the size of the tree $T$ within a factor of $1\pm \delta$ in $\tilde{O}(\sqrt{nT})$ steps. More generally, the same algorithm can be used to estimate size of directed acyclic graphs (DAGs) in a similar model. We then show two applications of this result: a) We show how to transform a classical backtracking search algorithm which exam…

FOS: Computer and information sciencesQuantum PhysicsSpeedupBacktrackingFOS: Physical sciences0102 computer and information sciences02 engineering and technologyComputational Complexity (cs.CC)Directed acyclic graph01 natural sciencesSearch treeCombinatoricsComputer Science - Computational Complexity010201 computation theory & mathematicsSearch algorithm020204 information systemsComputer Science - Data Structures and AlgorithmsTernary search tree0202 electrical engineering electronic engineering information engineeringData Structures and Algorithms (cs.DS)Quantum algorithmDepth-first searchQuantum Physics (quant-ph)MathematicsProceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing
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Supervised Quantum Learning without Measurements

2017

We propose a quantum machine learning algorithm for efficiently solving a class of problems encoded in quantum controlled unitary operations. The central physical mechanism of the protocol is the iteration of a quantum time-delayed equation that introduces feedback in the dynamics and eliminates the necessity of intermediate measurements. The performance of the quantum algorithm is analyzed by comparing the results obtained in numerical simulations with the outcome of classical machine learning methods for the same problem. The use of time-delayed equations enhances the toolbox of the field of quantum machine learning, which may enable unprecedented applications in quantum technologies. The…

FOS: Computer and information sciencesQuantum machine learningField (physics)Computer Science - Artificial IntelligenceComputer sciencelcsh:MedicineFOS: Physical sciencesMachine Learning (stat.ML)01 natural sciencesUnitary stateArticle010305 fluids & plasmasSuperconductivity (cond-mat.supr-con)Statistics - Machine Learning0103 physical sciencesMesoscale and Nanoscale Physics (cond-mat.mes-hall)lcsh:Science010306 general physicsQuantumProtocol (object-oriented programming)Quantum PhysicsClass (computer programming)MultidisciplinaryCondensed Matter - Mesoscale and Nanoscale PhysicsCondensed Matter - Superconductivitylcsh:RQuantum technologyArtificial Intelligence (cs.AI)ComputerSystemsOrganization_MISCELLANEOUSlcsh:QQuantum algorithmQuantum Physics (quant-ph)Algorithm
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Superlinear advantage for exact quantum algorithms

2012

A quantum algorithm is exact if, on any input data, it outputs the correct answer with certainty (probability 1). A key question is: how big is the advantage of exact quantum algorithms over their classical counterparts: deterministic algorithms. For total Boolean functions in the query model, the biggest known gap was just a factor of 2: PARITY of N inputs bits requires $N$ queries classically but can be computed with N/2 queries by an exact quantum algorithm. We present the first example of a Boolean function f(x_1, ..., x_N) for which exact quantum algorithms have superlinear advantage over the deterministic algorithms. Any deterministic algorithm that computes our function must use N qu…

FOS: Computer and information sciencesQuantum sortGeneral Computer ScienceDeterministic algorithmGeneral MathematicsFOS: Physical sciences0102 computer and information sciencesQuantum capacityComputational Complexity (cs.CC)01 natural sciences010305 fluids & plasmasCombinatorics0103 physical sciencesQuantum phase estimation algorithmQuantum informationBoolean function010306 general physicsComputer Science::DatabasesQuantum computerMathematicsDiscrete mathematicsQuantum PhysicsFunction (mathematics)Computer Science - Computational Complexity010201 computation theory & mathematicsQuantum Fourier transformNo-teleportation theoremQuantum algorithmQuantum Physics (quant-ph)Proceedings of the forty-fifth annual ACM symposium on Theory of Computing
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Quantum Computation With Devices Whose Contents Are Never Read

2010

In classical computation, a "write-only memory" (WOM) is little more than an oxymoron, and the addition of WOM to a (deterministic or probabilistic) classical computer brings no advantage. We prove that quantum computers that are augmented with WOM can solve problems that neither a classical computer with WOM nor a quantum computer without WOM can solve, when all other resource bounds are equal. We focus on realtime quantum finite automata, and examine the increase in their power effected by the addition of WOMs with different access modes and capacities. Some problems that are unsolvable by two-way probabilistic Turing machines using sublogarithmic amounts of read/write memory are shown to…

FOS: Computer and information sciencesQuantum sortQuantum PhysicsTheoretical computer scienceQuantum Turing machineComputer scienceFormal Languages and Automata Theory (cs.FL)ComputationQuantum simulatorFOS: Physical sciencesComputer Science - Formal Languages and Automata TheoryComputational Complexity (cs.CC)Computer Science - Computational ComplexityQuantum algorithmQuantum informationComputational problemQuantum Physics (quant-ph)Quantum computer
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Forrelation

2014

We achieve essentially the largest possible separation between quantum and classical query complexities. We do so using a property-testing problem called Forrelation, where one needs to decide whether one Boolean function is highly correlated with the Fourier transform of a second function. This problem can be solved using 1 quantum query, yet we show that any randomized algorithm needs Ω(√(N)log(N)) queries (improving an Ω(N[superscript 1/4]) lower bound of Aaronson). Conversely, we show that this 1 versus Ω(√(N)) separation is optimal: indeed, any t-query quantum algorithm whatsoever can be simulated by an O(N[superscript 1-1/2t])-query randomized algorithm. Thus, resolving an open questi…

FOS: Computer and information sciencesTheoretical computer scienceGeneral Computer ScienceComputational complexity theoryComputer scienceGeneralizationGeneral MathematicsSeparation (aeronautics)FOS: Physical sciences0102 computer and information sciencesComputational Complexity (cs.CC)01 natural sciencesUpper and lower boundsCombinatorics0103 physical sciences010306 general physicsBoolean functionQuantumComputer Science::DatabasesQuantum computerMathematicsDiscrete mathematicsQuantum PhysicsFunction (mathematics)Randomized algorithmComputer Science - Computational Complexity010201 computation theory & mathematicsQuantum algorithmQuantum Physics (quant-ph)Proceedings of the forty-seventh annual ACM symposium on Theory of Computing
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Time and space efficient quantum algorithms for detecting cycles and testing bipartiteness

2016

We study space and time efficient quantum algorithms for two graph problems -- deciding whether an $n$-vertex graph is a forest, and whether it is bipartite. Via a reduction to the s-t connectivity problem, we describe quantum algorithms for deciding both properties in $\tilde{O}(n^{3/2})$ time and using $O(\log n)$ classical and quantum bits of storage in the adjacency matrix model. We then present quantum algorithms for deciding the two properties in the adjacency array model, which run in time $\tilde{O}(n\sqrt{d_m})$ and also require $O(\log n)$ space, where $d_m$ is the maximum degree of any vertex in the input graph.

FOS: Computer and information sciencesVertex (graph theory)Quantum PhysicsNuclear and High Energy PhysicsReduction (recursion theory)Two-graphFOS: Physical sciencesGeneral Physics and AstronomyStatistical and Nonlinear PhysicsTheoretical Computer ScienceCombinatoricsComputational Theory and MathematicsComputer Science - Data Structures and AlgorithmsBipartite graphGraph (abstract data type)Adjacency listData Structures and Algorithms (cs.DS)Quantum algorithmAdjacency matrixQuantum Physics (quant-ph)Mathematical PhysicsMathematicsofComputing_DISCRETEMATHEMATICSMathematicsQuantum Information and Computation
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Molecular excited state calculations with adaptive wavefunctions on a quantum eigensolver emulation: reducing circuit depth and separating spin states

2021

Ab initio electronic excited state calculations are necessary for the quantitative study of photochemical reactions, but their accurate computation on classical computers is plagued by prohibitive resource scaling. The Variational Quantum Deflation (VQD) is an extension of the quantum-classical Variational Quantum Eigensolver (VQE) algorithm for calculating electronic excited state energies, and has the potential to address some of these scaling challenges using quantum computers. However, quantum computers available in the near term can only support a limited number of quantum circuit operations, so reducing the quantum computational cost in VQD methods is critical to their realisation. In…

FOS: Physical sciencesGeneral Physics and Astronomy02 engineering and technologyPhysics Atomic Molecular & Chemical7. Clean energy01 natural sciences09 EngineeringENERGYQuantum circuitquant-phQuantum mechanics0103 physical sciencesSinglet statePhysical and Theoretical Chemistry010306 general physicsWave functionQuantum computerSpin-½PhysicsQuantum PhysicsScience & Technology02 Physical SciencesChemical PhysicsChemistry PhysicalPhysics021001 nanoscience & nanotechnologyChemistryExcited statePhysical SciencesQuantum algorithm03 Chemical SciencesQuantum Physics (quant-ph)0210 nano-technologyGround stateFisicoquímicaPhysical Chemistry Chemical Physics
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Fundamental isomorphism theorems for quantum groups

2017

The lattice of subgroups of a group is the subject of numerous results revolving around the central theme of decomposing the group into "chunks" (subquotients) that can then be compared to one another in various ways. Examples of results in this class would be the Noether isomorphism theorems, Zassenhaus' butterfly lemma, the Schreier refinement theorem for subnormal series of subgroups, the Dedekind modularity law, and last but not least the Jordan-H\"older theorem. We discuss analogues of the above-mentioned results in the context of locally compact quantum groups and linearly reductive quantum groups. The nature of the two cases is different: the former is operator algebraic and the latt…

General MathematicsGroup Theory (math.GR)01 natural sciences0103 physical sciencesMathematics - Quantum AlgebraQuantum no-deleting theoremFOS: MathematicsQuantum Algebra (math.QA)Compact quantum groupLocally compact space0101 mathematicsOperator Algebras (math.OA)MathematicsZassenhaus lemmaLocally compact quantum group010102 general mathematicsMathematics - Operator AlgebrasFunctional Analysis (math.FA)AlgebraMathematics - Functional Analysis46L89 46L85 46L52 16T20 20G42Isomorphism theoremQuantum algorithmSchreier refinement theorem010307 mathematical physicsMathematics - Group Theory
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Quantum Algorithms for Some Strings Problems Based on Quantum String Comparator

2022

We study algorithms for solving three problems on strings. These are sorting of n strings of length k, “the Most Frequent String Search Problem”, and “searching intersection of two sequences of strings”. We construct quantum algorithms that are faster than classical (randomized or deterministic) counterparts for each of these problems. The quantum algorithms are based on the quantum procedure for comparing two strings of length k in O(k) queries. The first problem is sorting n strings of length k. We show that classical complexity of the problem is Θ(nk) for constant size alphabet, but our quantum algorithm has O˜(nk) complexity. The second one is searching the most frequent string among n …

High Energy Physics::Theoryquantum computation; quantum algorithms; string processing; sortingstring processingGeneral Mathematicsquantum computationComputer Science (miscellaneous)MathematicsofComputing_GENERALQA1-939Engineering (miscellaneous)quantum algorithmssortingMathematicsMathematics
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Lindblad equation approach for the full counting statistics of work and heat in driven quantum systems

2013

We formulate the general approach based on the Lindblad equation to calculate the full counting statistics of work and heat produced by driven quantum systems weakly coupled with a Markovian thermal bath. The approach can be applied to a wide class of dissipative quantum systems driven by an arbitrary force protocol. We show the validity of general fluctuation relations and consider several generic examples. The possibilities of using calorimetric measurements to test the presence of coherence and entanglement in the open quantum systems are discussed. QC 20141010

Hot TemperatureQuantum simulatorFOS: Physical sciencesresonance fluorescenceQuantum entanglementCalorimetry01 natural sciences010305 fluids & plasmasOpen quantum system0103 physical sciencesStatisticsFysikStatistical physicsequality010306 general physicsQuantum statistical mechanicsPhysicsQuantum discordQuantum Physicsta114Lindblad equationModels TheoreticalClassical mechanicsPhysical SciencesDissipative systemQuantum TheoryQuantum algorithmfluctuation theoremQuantum Physics (quant-ph)
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