3,387 research outputs found

    Inapproximability of the Standard Pebble Game and Hard to Pebble Graphs

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    Pebble games are single-player games on DAGs involving placing and moving pebbles on nodes of the graph according to a certain set of rules. The goal is to pebble a set of target nodes using a minimum number of pebbles. In this paper, we present a possibly simpler proof of the result in [CLNV15] and strengthen the result to show that it is PSPACE-hard to determine the minimum number of pebbles to an additive n1/3−ϔn^{1/3-\epsilon} term for all Ï”>0\epsilon > 0, which improves upon the currently known additive constant hardness of approximation [CLNV15] in the standard pebble game. We also introduce a family of explicit, constant indegree graphs with nn nodes where there exists a graph in the family such that using constant kk pebbles requires Ω(nk)\Omega(n^k) moves to pebble in both the standard and black-white pebble games. This independently answers an open question summarized in [Nor15] of whether a family of DAGs exists that meets the upper bound of O(nk)O(n^k) moves using constant kk pebbles with a different construction than that presented in [AdRNV17].Comment: Preliminary version in WADS 201

    General Connectivity Distribution Functions for Growing Networks with Preferential Attachment of Fractional Power

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    We study the general connectivity distribution functions for growing networks with preferential attachment of fractional power, Πi∝kα\Pi_{i} \propto k^{\alpha}, using the Simon's method. We first show that the heart of the previously known methods of the rate equations for the connectivity distribution functions is nothing but the Simon's method for word problem. Secondly, we show that the case of fractional α\alpha the ZZ-transformation of the rate equation provides a fractional differential equation of new type, which coincides with that for PA with linear power, when α=1\alpha = 1. We show that to solve such a fractional differential equation we need define a transidental function ΄(a,s,c;z)\Upsilon (a,s,c;z) that we call {\it upsilon function}. Most of all previously known results are obtained consistently in the frame work of a unified theory.Comment: 10 page

    Border trees of complex networks

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    The comprehensive characterization of the structure of complex networks is essential to understand the dynamical processes which guide their evolution. The discovery of the scale-free distribution and the small world property of real networks were fundamental to stimulate more realistic models and to understand some dynamical processes such as network growth. However, properties related to the network borders (nodes with degree equal to one), one of its most fragile parts, remain little investigated and understood. The border nodes may be involved in the evolution of structures such as geographical networks. Here we analyze complex networks by looking for border trees, which are defined as the subgraphs without cycles connected to the remainder of the network (containing cycles) and terminating into border nodes. In addition to describing an algorithm for identification of such tree subgraphs, we also consider a series of their measurements, including their number of vertices, number of leaves, and depth. We investigate the properties of border trees for several theoretical models as well as real-world networks.Comment: 5 pages, 1 figure, 2 tables. A working manuscript, comments and suggestions welcome
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