Search results for " algorithm"

showing 10 items of 2538 documents

Span-Program-Based Quantum Algorithms for Graph Bipartiteness and Connectivity

2016

Span program is a linear-algebraic model of computation which can be used to design quantum algorithms. For any Boolean function there exists a span program that leads to a quantum algorithm with optimal quantum query complexity. In general, finding such span programs is not an easy task. In this work, given a query access to the adjacency matrix of a simple graph G with n vertices, we provide two new span-program-based quantum algorithms:an algorithm for testing if the graph is bipartite that uses $$On\sqrt{n}$$ quantum queries;an algorithm for testing if the graph is connected that uses $$On\sqrt{n}$$ quantum queries.

Discrete mathematicsComputer scienceExistential quantificationModel of computationTheoryofComputation_GENERALComputerSystemsOrganization_MISCELLANEOUSBipartite graphGraph (abstract data type)Quantum algorithmAdjacency matrixBoolean functionQuantumComputer Science::DatabasesMathematicsofComputing_DISCRETEMATHEMATICS
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Using Search Algorithms for Modeling Economic Processes

2013

Abstract Economic issues are placed in formal practice, when is desired a modelling of the economic process, a manufacturing process, a device, etc. Each share of that economic process is denoted by a, b, c, d, these actions with defined time periods and action pairs are formed strings of the form, ab * cab * bc ., ab, bb, bc. so for them there are no other restrictions. If the graph is viewed as a system image, nodes representing components, then an immediate interpretation of an arc (xi, xj) are the component xi that is said to directly influence component xj. If nodes have the significance of possible states of a system when a spring (xi.xj) means that, the system can jump from state xi …

Discrete mathematicsComputer scienceGeneral EngineeringEnergy Engineering and Power TechnologyState (functional analysis)Directed graphGraphInterpretation (model theory)AlgorithmSearch algorithmComponent (UML)Economic Process.System imageGraph (abstract data type)Operations managementFinite setModelProcedia Economics and Finance
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Witness computation for solving geometric constraint systems

2014

International audience; In geometric constraint solving, the constraints are represented with an equation system F(U, X) = 0, where X denotes the unknowns and U denotes a set of parameters. The target solution for X is noted XT. A witness is a couple (U_W, X_W) such that F(U_W, X_W) = 0. The witness is not the target solution, but they share the same combinatorial features, even when the witness and the target lie on two distinct connected components of the solution set of F(U, X) = 0. Thus a witness enables the qualitative study of the system: the detection of over- and under-constrained systems, the decomposition into irreducible subsystems, the computation of subsystems boundaries. This …

Discrete mathematicsConnected componentMathematical optimization[ INFO ] Computer Science [cs]Numerical algorithmsComputer scienceComputationNumerical analysisSystem FSolution setBinary constraint[INFO] Computer Science [cs]16. Peace & justiceGeometric constraint solvingWitnessSimplex algorithmWitness computation[INFO]Computer Science [cs]
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Approximate convex hull of affine iterated function system attractors

2012

International audience; In this paper, we present an algorithm to construct an approximate convex hull of the attractors of an affine iterated function system (IFS). We construct a sequence of convex hull approximations for any required precision using the self-similarity property of the attractor in order to optimize calculations. Due to the affine properties of IFS transformations, the number of points considered in the construction is reduced. The time complexity of our algorithm is a linear function of the number of iterations and the number of points in the output convex hull. The number of iterations and the execution time increases logarithmically with increasing accuracy. In additio…

Discrete mathematicsConvex hull0209 industrial biotechnologyGeneral MathematicsApplied Mathematics010102 general mathematicsProper convex functionConvex setMathematicsofComputing_GENERALGeneral Physics and AstronomyStatistical and Nonlinear Physics02 engineering and technology[ INFO.INFO-GR ] Computer Science [cs]/Graphics [cs.GR]01 natural sciences[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]020901 industrial engineering & automationAffine hullTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYConvex polytopeOutput-sensitive algorithmConvex combination0101 mathematicsConvex conjugateMathematics
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Complete, Exact and Efficient Implementation for Computing the Adjacency Graph of an Arrangement of Quadrics

2007

The original publication is available at www.springerlink.com ; ISBN 978-3-540-75519-7 ; ISSN 0302-9743 (Print) 1611-3349 (Online); International audience; We present a complete, exact and efficient implementation to compute the adjacency graph of an arrangement of quadrics, \ie surfaces of algebraic degree~2. This is a major step towards the computation of the full 3D arrangement. We enhanced an implementation for an exact parameterization of the intersection curves of two quadrics, such that we can compute the exact parameter value for intersection points and from that the adjacency graph of the arrangement. Our implementation is {\em complete} in the sense that it can handle all kinds of…

Discrete mathematicsDegree (graph theory)ComputationDegenerate energy levelsACM: I.: Computing Methodologies/I.1: SYMBOLIC AND ALGEBRAIC MANIPULATION/I.1.2: Algorithms/I.1.2.0: Algebraic algorithms020207 software engineering010103 numerical & computational mathematics02 engineering and technology[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]01 natural sciencesACM: G.: Mathematics of Computing/G.4: MATHEMATICAL SOFTWARE/G.4.3: EfficiencyCombinatoricsIntersection0202 electrical engineering electronic engineering information engineeringGraph (abstract data type)Adjacency listGravitational singularity0101 mathematicsAlgebraic numberACM: G.: Mathematics of Computing/G.4: MATHEMATICAL SOFTWARE/G.4.0: Algorithm design and analysisMathematics
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Grover’s Algorithm with Errors

2013

Grover’s algorithm is a quantum search algorithm solving the unstructured search problem of size n in \(O(\sqrt{n})\) queries, while any classical algorithm needs O(n) queries [3].

Discrete mathematicsDensity matrixComputer Science::Information RetrievalProbability of errorGrover's algorithmMatrix normSearch problemQuantum algorithmQuantum search algorithmComputer Science::DatabasesMathematics
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A formal proof of the ε-optimality of absorbing continuous pursuit algorithms using the theory of regular functions

2014

Published version of an article from the journal: Applied Intelligence. Also available on Springerlink: http://dx.doi.org/10.1007/s10489-014-0541-1 The most difficult part in the design and analysis of Learning Automata (LA) consists of the formal proofs of their convergence accuracies. The mathematical techniques used for the different families (Fixed Structure, Variable Structure, Discretized etc.) are quite distinct. Among the families of LA, Estimator Algorithms (EAs) are certainly the fastest, and within this family, the set of Pursuit algorithms have been considered to be the pioneering schemes. Informally, if the environment is stationary, their ε-optimality is defined as their abili…

Discrete mathematicsDiscretizationLearning automataAbsorbing CPAComputer scienceEstimatorMonotonic functionVDP::Technology: 500::Information and communication technology: 550Mathematical proofFormal proofCPAArbitrarily largeArtificial Intelligenceε-optimalityMartingale (probability theory)Pursuit algorithmsAlgorithm
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Understanding Quantum Algorithms via Query Complexity

2017

Query complexity is a model of computation in which we have to compute a function $f(x_1, \ldots, x_N)$ of variables $x_i$ which can be accessed via queries. The complexity of an algorithm is measured by the number of queries that it makes. Query complexity is widely used for studying quantum algorithms, for two reasons. First, it includes many of the known quantum algorithms (including Grover's quantum search and a key subroutine of Shor's factoring algorithm). Second, one can prove lower bounds on the query complexity, bounding the possible quantum advantage. In the last few years, there have been major advances on several longstanding problems in the query complexity. In this talk, we su…

Discrete mathematicsFOS: Computer and information sciencesQuantum PhysicsComputer scienceModel of computationSubroutineComputer Science::Information RetrievalFOS: Physical sciencesFunction (mathematics)Computational Complexity (cs.CC)Symmetric functionComputer Science - Computational ComplexityBounding overwatchPartial functionKey (cryptography)Quantum algorithmQuantum Physics (quant-ph)Computer Science::Databases
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The Alternating BWT: an algorithmic perspective

2020

Abstract The Burrows-Wheeler Transform (BWT) is a word transformation introduced in 1994 for Data Compression. It has become a fundamental tool for designing self-indexing data structures, with important applications in several areas in science and engineering. The Alternating Burrows-Wheeler Transform (ABWT) is another transformation recently introduced in Gessel et al. (2012) [21] and studied in the field of Combinatorics on Words. It is analogous to the BWT, except that it uses an alternating lexicographical order instead of the usual one. Building on results in Giancarlo et al. (2018) [23] , where we have shown that BWT and ABWT are part of a larger class of reversible transformations, …

Discrete mathematicsFOS: Computer and information sciencesSettore INF/01 - InformaticaGeneral Computer ScienceBasis (linear algebra)Computer scienceAlternating Burrows-Wheeler TransformGalois wordRank-invertibilityField (mathematics)Data structureTheoretical Computer ScienceTransformation (function)Difference cover algorithmComputer Science - Data Structures and AlgorithmsData Structures and Algorithms (cs.DS)Time complexityAlternating Burrows-Wheeler Transform; Difference cover algorithm; Galois word; Rank-invertibilityWord (computer architecture)Data compression
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Minimal forbidden words and symbolic dynamics

1996

We introduce a new complexity measure of a factorial formal language L: the growth rate of the set of minimal forbidden words. We prove some combinatorial properties of minimal forbidden words. As main result we prove that the growth rate of the set of minimal forbidden words for L is a topological invariant of the dynamical system defined by L.

Discrete mathematicsFactorial010102 general mathematics[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Symbolic dynamicsComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)[INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]0102 computer and information sciencesInvariant (physics)16. Peace & justice01 natural sciencesCombinatorics010201 computation theory & mathematicsTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMSInformation complexityFormal language0101 mathematicsComputer Science::Formal Languages and Automata TheoryComputingMilieux_MISCELLANEOUSMathematicsofComputing_DISCRETEMATHEMATICSMathematics
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