Search results for "complex"

showing 10 items of 5889 documents

On a Conjecture on Bidimensional Words

2003

We prove that, given a double sequence w over the alphabet A (i.e. a mapping from Z2 to A), if there exists a pair (n0, m0) ∈ Z2 such that pw(n0, m0) < 1/100n0m0, then w has a periodicity vector, where pw is the complexity function in rectangles of w.

Discrete mathematicsConjectureGeneral Computer ScienceExistential quantificationTheoretical Computer ScienceCombinatoricsCombinatorics on wordsFormal languageComplexity functionPattern matchingAlphabetDouble sequenceComputer Science(all)Mathematics
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The branch set of a quasiregular mapping between metric manifolds

2016

Abstract In this note, we announce some new results on quantitative countable porosity of the branch set of a quasiregular mapping in very general metric spaces. As applications, we solve a recent conjecture of Fassler et al., an open problem of Heinonen–Rickman, and an open question of Heinonen–Semmes.

Discrete mathematicsConjectureMathematics::Complex VariablesOpen problem010102 general mathematicsMathematical analysisGeneral Medicine01 natural sciences010101 applied mathematicsSet (abstract data type)Metric spaceMetric (mathematics)Mathematics::Metric GeometryCountable set0101 mathematicsMathematicsComptes Rendus Mathematique
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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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Dichotomies properties on computational complexity of S-packing coloring problems

2015

This work establishes the complexity class of several instances of the S -packing coloring problem: for a graph G , a positive integer k and a nondecreasing list of integers S = ( s 1 , ? , s k ) , G is S -colorable if its vertices can be partitioned into sets S i , i = 1 , ? , k , where each S i is an s i -packing (a set of vertices at pairwise distance greater than s i ). In particular we prove a dichotomy between NP-complete problems and polynomial-time solvable problems for lists of at most four integers.

Discrete mathematicsDichotomyComputational complexity theory010102 general mathematics0102 computer and information sciences01 natural sciencesGraphTheoretical Computer ScienceCombinatoricsIntegerSet packing010201 computation theory & mathematicsComplexity classDiscrete Mathematics and CombinatoricsPairwise comparison0101 mathematicsColoring problemMathematicsDiscrete Mathematics
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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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On Physical Problems that are Slightly More Difficult than QMA

2013

We study the complexity of computational problems from quantum physics. Typically, they are studied using the complexity class QMA (quantum counterpart of NP) but some natural computational problems appear to be slightly harder than QMA. We introduce new complexity classes consisting of problems that are solvable with a small number of queries to a QMA oracle and use these complexity classes to quantify the complexity of several natural computational problems (for example, the complexity of estimating the spectral gap of a Hamiltonian).

Discrete mathematicsFOS: Computer and information sciencesQuantum PhysicsTheoretical computer scienceCompleteNP-easyFOS: Physical sciences0102 computer and information sciencesComputer Science::Computational ComplexityComputational Complexity (cs.CC)01 natural sciencesPHStructural complexity theoryComputer Science - Computational Complexity010201 computation theory & mathematics0103 physical sciencesAsymptotic computational complexityComplexity classF.1.2Low010306 general physicsQuantum Physics (quant-ph)Quantum complexity theoryMathematics2014 IEEE 29th Conference on Computational Complexity (CCC)
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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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Finite State Verifiers with Constant Randomness

2012

We give a new characterization of NL as the class of languages whose members have certificates that can be verified with small error in polynomial time by finite state machines that use a constant number of random bits, as opposed to its conventional description in terms of deterministic logarithmic-space verifiers. It turns out that allowing two-way interaction with the prover does not change the class of verifiable languages, and that no polynomially bounded amount of randomness is useful for constant-memory computers when used as language recognizers, or public-coin verifiers.

Discrete mathematicsFinite-state machine010102 general mathematics0102 computer and information sciencesGas meter prover01 natural sciencesRegular language010201 computation theory & mathematicsBounded functionProbabilistic automaton0101 mathematicsConstant (mathematics)Time complexityRandomnessMathematics
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Team learning as a game

1997

A machine FIN-learning machine M receives successive values of the function f it is learning; at some point M outputs conjecture which should be a correct index of f. When n machines simultaneously learn the same function f and at least k of these machines outut correct indices of f, we have team learning [k,n]FIN. Papers [DKV92, DK96] show that sometimes a team or a robabilistic learner can simulate another one, if its probability p (or team success ratio k/n) is close enough. On the other hand, there are critical ratios which mae simulation o FIN(p2) by FIN(p1) imossible whenever p2 _< r < p1 or some critical ratio r. Accordingly to [DKV92] the critical ratio closest to 1/2 rom the let is…

Discrete mathematicsFinite-state machineConjectureTeam learningAlgorithm complexityFunction (mathematics)Critical ratioAlgorithmMathematics
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