Search results for "MathematicsofComputing_DISCRETEMATHEMATICS"

showing 10 items of 123 documents

Three-page encoding and complexity theory for spatial graphs

2004

We construct a series of finitely presented semigroups. The centers of these semigroups encode uniquely up to rigid ambient isotopy in 3-space all non-oriented spatial graphs. This encoding is obtained by using three-page embeddings of graphs into the product of the line with the cone on three points. By exploiting three-page embeddings we introduce the notion of the three-page complexity for spatial graphs. This complexity satisfies the properties of finiteness and additivity under natural operations.

Discrete mathematics[ MATH.MATH-GT ] Mathematics [math]/Geometric Topology [math.GT]Algebra and Number TheoryDegree (graph theory)Semigroup010102 general mathematicsGeometric topologyGeometric Topology (math.GT)01 natural sciences57M25 57M15 57M05Combinatorics010104 statistics & probabilityMathematics - Geometric TopologyCone (topology)Additive functionEncoding (memory)[MATH.MATH-GT]Mathematics [math]/Geometric Topology [math.GT]FOS: Mathematics0101 mathematicsUnit (ring theory)Ambient isotopyMathematics[MATH.MATH-GT] Mathematics [math]/Geometric Topology [math.GT]MathematicsofComputing_DISCRETEMATHEMATICS
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About Graph Unions and Intersections

2020

Summary In this article the union and intersection of a set of graphs are formalized in the Mizar system [5], based on the formalization of graphs in [7].

Discrete mathematicsgraph theoryApplied Mathematics020207 software engineeringgraph intersection0102 computer and information sciences02 engineering and technology68v20Computer Science::Digital Libraries01 natural sciencesComputational Mathematicsgraph union010201 computation theory & mathematicsComputer Science::Mathematical SoftwareQA1-9390202 electrical engineering electronic engineering information engineering05c76Graph (abstract data type)MathematicsMathematicsofComputing_DISCRETEMATHEMATICSMathematicsFormalized Mathematics
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The Spanning Tree based Approach for Solving the Shortest Path Problem in Social Graphs

2016

Nowadays there are many social media sites with a very large number of users. Users of social media sites and relationships between them can be modelled as a graph. Such graphs can be analysed using methods from social network analysis (SNA). Many measures used in SNA rely on computation of shortest paths between nodes of a graph. There are many shortest path algorithms, but the majority of them suits only for small graphs, or work only with road network graphs that are fundamentally different from social graphs. This paper describes an efficient shortest path searching algorithm suitable for large social graphs. The described algorithm extends the Atlas algorithm. The proposed algorithm so…

Discrete mathematicsta113Mathematical optimizationSpanning treesocial network analysisComputer scienceAtlas algorithm020206 networking & telecommunications02 engineering and technologyLongest path problemverkostoanalyysiWidest path problemOdnoklassnikiEuclidean shortest pathShortest Path Faster Algorithmsocial graph020204 information systemsShortest path problem0202 electrical engineering electronic engineering information engineeringK shortest path routingCanadian traveller problemshortest path problemMathematicsofComputing_DISCRETEMATHEMATICS
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Algorithms for the Maximum Weight Connected $$k$$-Induced Subgraph Problem

2014

Finding differentially regulated subgraphs in a biochemical network is an important problem in bioinformatics. We present a new model for finding such subgraphs which takes the polarity of the edges (activating or inhibiting) into account, leading to the problem of finding a connected subgraph induced by \(k\) vertices with maximum weight. We present several algorithms for this problem, including dynamic programming on tree decompositions and integer linear programming. We compare the strength of our integer linear program to previous formulations of the \(k\)-cardinality tree problem. Finally, we compare the performance of the algorithms and the quality of the results to a previous approac…

Dynamic programmingDiscrete mathematicsCombinatoricsLinear programmingInduced subgraphHeuristicsInteger programmingAlgorithmTree (graph theory)Tree decompositionMathematicsofComputing_DISCRETEMATHEMATICSMathematicsInteger (computer science)
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A Constructive Arboricity Approximation Scheme

2018

The arboricity $\Gamma$ of a graph is the minimum number of forests its edge set can be partitioned into. Previous approximation schemes were nonconstructive, i.e., they only approximated the arboricity as a value without computing a corresponding forest partition. This is because they operate on the related pseudoforest partitions or the dual problem of finding dense subgraphs. We propose an algorithm for converting a partition of $k$ pseudoforests into a partition of $k+1$ forests in $O(mk\log k + m \log n)$ time with a data structure by Brodal and Fagerberg that stores graphs of arboricity $k$. A slightly better bound can be given when perfect hashing is used. When applied to a pseudofor…

FOS: Computer and information sciencesComputer Science - Data Structures and AlgorithmsData Structures and Algorithms (cs.DS)MathematicsofComputing_DISCRETEMATHEMATICS
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Self-stabilizing Balls & Bins in Batches

2016

A fundamental problem in distributed computing is the distribution of requests to a set of uniform servers without a centralized controller. Classically, such problems are modeled as static balls into bins processes, where $m$ balls (tasks) are to be distributed to $n$ bins (servers). In a seminal work, Azar et al. proposed the sequential strategy \greedy{d} for $n=m$. When thrown, a ball queries the load of $d$ random bins and is allocated to a least loaded of these. Azar et al. showed that $d=2$ yields an exponential improvement compared to $d=1$. Berenbrink et al. extended this to $m\gg n$, showing that the maximal load difference is independent of $m$ for $d=2$ (in contrast to $d=1$). W…

FOS: Computer and information sciencesComputer Science - Distributed Parallel and Cluster ComputingTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYDistributed Parallel and Cluster Computing (cs.DC)MathematicsofComputing_DISCRETEMATHEMATICS
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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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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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Quantum Algorithm for Dynamic Programming Approach for DAGs. Applications for Zhegalkin Polynomial Evaluation and Some Problems on DAGs

2018

In this paper, we present a quantum algorithm for dynamic programming approach for problems on directed acyclic graphs (DAGs). The running time of the algorithm is $O(\sqrt{\hat{n}m}\log \hat{n})$, and the running time of the best known deterministic algorithm is $O(n+m)$, where $n$ is the number of vertices, $\hat{n}$ is the number of vertices with at least one outgoing edge; $m$ is the number of edges. We show that we can solve problems that use OR, AND, NAND, MAX and MIN functions as the main transition steps. The approach is useful for a couple of problems. One of them is computing a Boolean formula that is represented by Zhegalkin polynomial, a Boolean circuit with shared input and non…

FOS: Computer and information sciencesQuantum PhysicsTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYComputer Science - Data Structures and AlgorithmsFOS: Physical sciencesData Structures and Algorithms (cs.DS)Quantum Physics (quant-ph)MathematicsofComputing_DISCRETEMATHEMATICS
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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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