Search results for "combinatoric"

showing 10 items of 1776 documents

Primitive sets of words

2020

Given a (finite or infinite) subset $X$ of the free monoid $A^*$ over a finite alphabet $A$, the rank of $X$ is the minimal cardinality of a set $F$ such that $X \subseteq F^*$. We say that a submonoid $M$ generated by $k$ elements of $A^*$ is {\em $k$-maximal} if there does not exist another submonoid generated by at most $k$ words containing $M$. We call a set $X \subseteq A^*$ {\em primitive} if it is the basis of a $|X|$-maximal submonoid. This definition encompasses the notion of primitive word -- in fact, $\{w\}$ is a primitive set if and only if $w$ is a primitive word. By definition, for any set $X$, there exists a primitive set $Y$ such that $X \subseteq Y^*$. We therefore call $Y$…

FOS: Computer and information sciencesPrimitive setDiscrete Mathematics (cs.DM)General Computer ScienceFormal Languages and Automata Theory (cs.FL)Pseudo-repetitionComputer Science - Formal Languages and Automata Theory0102 computer and information sciences02 engineering and technology01 natural sciencesTheoretical Computer ScienceCombinatoricsCardinalityFree monoidBi-rootFOS: Mathematics0202 electrical engineering electronic engineering information engineeringMathematics - CombinatoricsRank (graph theory)Primitive root modulo nMathematicsHidden repetitionSettore INF/01 - InformaticaIntersection (set theory)k-maximal monoidFunction (mathematics)Basis (universal algebra)010201 computation theory & mathematics020201 artificial intelligence & image processingCombinatorics (math.CO)Computer Science::Formal Languages and Automata TheoryWord (group theory)Computer Science - Discrete Mathematics
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Mahonian STAT on words

2016

In 2000, Babson and Steingrimsson introduced the notion of what is now known as a permutation vincular pattern, and based on it they re-defined known Mahonian statistics and introduced new ones, proving or conjecturing their Mahonity. These conjectures were proved by Foata and Zeilberger in 2001, and by Foata and Randrianarivony in 2006.In 2010, Burstein refined some of these results by giving a bijection between permutations with a fixed value for the major index and those with the same value for STAT , where STAT is one of the statistics defined and proved to be Mahonian in the 2000 Babson and Steingrimsson's paper. Several other statistics are preserved as well by Burstein's bijection.At…

FOS: Computer and information sciencesQA75[ INFO ] Computer Science [cs]Discrete Mathematics (cs.DM)Major index0102 computer and information sciencesMathematical Analysis01 natural sciencesWords and PermutationsCombinatorial problemsEquidistributionTheoretical Computer ScienceCombinatoricssymbols.namesakePermutationBijectionsFOS: MathematicsMathematics - CombinatoricsMathematical proofs[INFO]Computer Science [cs]0101 mathematicsStatisticMathematicsStatisticZ665Algebraic combinatoricsMathematics::CombinatoricsFormal power seriesPatternPermutationsEulerian path16. Peace & justiceComputer Science Applications010101 applied mathematics010201 computation theory & mathematicsCombinatoricsSignal ProcessingsymbolsBijectionCombinatorics (math.CO)Information SystemsComputer Science - Discrete Mathematics
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Quadratic speedup for finding marked vertices by quantum walks

2020

A quantum walk algorithm can detect the presence of a marked vertex on a graph quadratically faster than the corresponding random walk algorithm (Szegedy, FOCS 2004). However, quantum algorithms that actually find a marked element quadratically faster than a classical random walk were only known for the special case when the marked set consists of just a single vertex, or in the case of some specific graphs. We present a new quantum algorithm for finding a marked vertex in any graph, with any set of marked vertices, that is (up to a log factor) quadratically faster than the corresponding classical random walk.

FOS: Computer and information sciencesQuadratic growthQuantum PhysicsQuantum algorithmsSpeedupMarkov chainMarkov chainsProbability (math.PR)FOS: Physical sciencesRandom walkVertex (geometry)CombinatoricsQuadratic equationSearch by random walkQuantum searchComputer Science - Data Structures and AlgorithmsFOS: MathematicsData Structures and Algorithms (cs.DS)Quantum walkQuantum algorithmQuantum Physics (quant-ph)Mathematics - ProbabilityMathematicsQuantum walks
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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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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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A Quantum Lovasz Local Lemma

2012

The Lovasz Local Lemma (LLL) is a powerful tool in probability theory to show the existence of combinatorial objects meeting a prescribed collection of "weakly dependent" criteria. We show that the LLL extends to a much more general geometric setting, where events are replaced with subspaces and probability is replaced with relative dimension, which allows to lower bound the dimension of the intersection of vector spaces under certain independence conditions. Our result immediately applies to the k-QSAT problem: For instance we show that any collection of rank 1 projectors with the property that each qubit appears in at most $2^k/(e \cdot k)$ of them, has a joint satisfiable state. We then …

FOS: Computer and information sciencesRank (linear algebra)FOS: Physical sciences0102 computer and information sciencesComputational Complexity (cs.CC)01 natural sciencesUpper and lower boundsCombinatoricsIntersectionProbability theoryArtificial Intelligence0103 physical sciences010306 general physicsLovász local lemmaIndependence (probability theory)Quantum computerMathematicsDiscrete mathematicsQuantum PhysicsComputer Science - Computational ComplexityHardware and ArchitectureControl and Systems Engineering010201 computation theory & mathematicsQubitQuantum Physics (quant-ph)SoftwareInformation SystemsVector space
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Sensitivity versus block sensitivity of Boolean functions

2010

Determining the maximal separation between sensitivity and block sensitivity of Boolean functions is of interest for computational complexity theory. We construct a sequence of Boolean functions with bs(f) = 1/2 s(f)^2 + 1/2 s(f). The best known separation previously was bs(f) = 1/2 s(f)^2 due to Rubinstein. We also report results of computer search for functions with at most 12 variables.

FOS: Computer and information sciencesSequenceComputational complexity theoryBlock (permutation group theory)Computational Complexity (cs.CC)Computer Science ApplicationsTheoretical Computer ScienceCombinatoricsComputer Science - Computational ComplexitySignal ProcessingTheory of computationSensitivity (control systems)Boolean functionAlgorithmComputer searchInformation SystemsMathematics
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Open and Closed Prefixes of Sturmian Words

2013

A word is closed if it contains a proper factor that occurs both as a prefix and as a suffix but does not have internal occurrences, otherwise it is open. We deal with the sequence of open and closed prefixes of Sturmian words and prove that this sequence characterizes every finite or infinite Sturmian word up to isomorphisms of the alphabet. We then characterize the combinatorial structure of the sequence of open and closed prefixes of standard Sturmian words. We prove that every standard Sturmian word, after swapping its first letter, can be written as an infinite product of squares of reversed standard words.

FOS: Computer and information sciencesSequenceFibonacci numberDiscrete Mathematics (cs.DM)Formal Languages and Automata Theory (cs.FL)Sturmian wordStructure (category theory)Sturmian wordInfinite productComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Computer Science - Formal Languages and Automata Theory68R15CombinatoricsPrefixComputer Science::Discrete MathematicsCombinatorics on words Sturmian wordFOS: MathematicsMathematics - CombinatoricsClosed wordsCombinatorics (math.CO)SuffixWord (group theory)Computer Science::Formal Languages and Automata TheoryMathematicsComputer Science - Discrete Mathematics
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Constructing Antidictionaries in Output-Sensitive Space

2021

A word $x$ that is absent from a word $y$ is called minimal if all its proper factors occur in $y$. Given a collection of $k$ words $y_1,y_2,\ldots,y_k$ over an alphabet $\Sigma$, we are asked to compute the set $\mathrm{M}^{\ell}_{y_{1}\#\ldots\#y_{k}}$ of minimal absent words of length at most $\ell$ of word $y=y_1\#y_2\#\ldots\#y_k$, $\#\notin\Sigma$. In data compression, this corresponds to computing the antidictionary of $k$ documents. In bioinformatics, it corresponds to computing words that are absent from a genome of $k$ chromosomes. This computation generally requires $\Omega(n)$ space for $n=|y|$ using any of the plenty available $\mathcal{O}(n)$-time algorithms. This is because a…

FOS: Computer and information sciencesSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniOutput sensitive algorithmsString algorithmsPhysicsAntidictionarieSettore INF/01 - InformaticaOutput sensitive algorithm0102 computer and information sciencesAbsent wordsSpace (mathematics)01 natural sciencesAntidictionariesCombinatorics010201 computation theory & mathematicsTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYData compressionComputer Science - Data Structures and AlgorithmsData Structures and Algorithms (cs.DS)Computer Science::Symbolic Computation[INFO]Computer Science [cs]Absent wordAlphabetWord (group theory)2019 Data Compression Conference (DCC)
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Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions

2021

We develop a Bayesian inference method for diffusions observed discretely and with noise, which is free of discretisation bias. Unlike existing unbiased inference methods, our method does not rely on exact simulation techniques. Instead, our method uses standard time-discretised approximations of diffusions, such as the Euler--Maruyama scheme. Our approach is based on particle marginal Metropolis--Hastings, a particle filter, randomised multilevel Monte Carlo, and importance sampling type correction of approximate Markov chain Monte Carlo. The resulting estimator leads to inference without a bias from the time-discretisation as the number of Markov chain iterations increases. We give conver…

FOS: Computer and information sciencesStatistics and ProbabilityDiscretizationComputer scienceMarkovin ketjutInference010103 numerical & computational mathematicssequential Monte CarloBayesian inferenceStatistics - Computation01 natural sciencesMethodology (stat.ME)010104 statistics & probabilitysymbols.namesakediffuusio (fysikaaliset ilmiöt)FOS: MathematicsDiscrete Mathematics and Combinatorics0101 mathematicsHidden Markov modelComputation (stat.CO)Statistics - Methodologymatematiikkabayesilainen menetelmäApplied MathematicsProbability (math.PR)diffusionmatemaattiset menetelmätMarkov chain Monte CarloMarkov chain Monte CarloMonte Carlo -menetelmätNoiseimportance sampling65C05 (primary) 60H35 65C35 65C40 (secondary)Modeling and Simulationsymbolsmatemaattiset mallitStatistics Probability and Uncertaintymultilevel Monte CarloParticle filterAlgorithmMathematics - ProbabilityImportance samplingSIAM/ASA Journal on Uncertainty Quantification
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