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Constraint search trees are a generic approach to search trees where all operations are defined in terms of constraints. This abstract viewpoint makes clear the fundamental operations of search trees and immediately points to new possibilities for search trees. In this paper we present height-balanced constraint search trees (HCSTs), a general approach to building height-balanced index structur...
Spatial databases have been increasingly and widely used in recent years. The R-tree proposed by Guttman is probably the most popular dynamic index structure for eciently retrieving objects from a spatial database according to their spatial locations. However, experiments show that only about 70% storage utilization can be achieved in Guttman's R-tree and its variants. In this paper, we propos...
Given a group G, RF-theory constructs a new group RF(G) and an action RF(G) → Isom(XG) by isometries of RF(G) on a canonically associated R-tree XG. We give an overview mostly focusing on the more basic aspects of this theory, up to and including the universal property of RF-groups and their associated R-trees.
Recently there has been an increasing interest in supporting bulk operations on multidimensional index structures. Bulk loading refers to the process of creating an initial index structure for a presumably very large data set. In this paper, we present a generic algorithm for bulk loading which is applicable to a broad class of index structures. Our approach differs completely from previous one...
R-trees arise naturally in the study of groups of isometries of hyperbolic space. An R-tree is a uniquely arcwise connected metric space in which each arc is isometric to a subarc of the reals. It follows that an R-tree is locally arcwise connected, contractible, and one-dimensional. Unique and local arcwise connectivity characterize R-trees among metric spaces. A universal R-tree would be of i...
In this paper, we describe a cost model for an adaptive cellbased index structure which aims at efficient management of immense amounts of spatio-temporal data. We first survey various methods to estimate the performance of R-tree variants. Then, we present our cost model which accurately estimates the number of disk accesses for the adaptive cell-based index structure. To show the accuracy of ...
We propose a scalable technique called Seeded Clustering that allows us to maintain R-tree indices by bulk insertion while keeping pace with high data arrival rates. Our approach uses a seed tree, which is copied from the top k levels of a target R-tree, to classify input data objects into clusters. We then build an Rtree for each of the clusters and insert the input R-trees into the target R-t...
and it is easy to see that this is constant on conjugacy classes. In this setting, it can be shown that η(s) and ζ(s) have extensions as meromorphic functions to the entire complex plane. The proof relies on non-commutative harmonic analysis and the functions are studied via the spectral properties of the Laplace-Beltrami operator. In this note we shall consider an analogous situation where we ...
In this work an R-tree variant, which uses minimum volume covering ellipsoids instead of usual minimum bounding rectangles, is presented. The most significant aspects, which determine R-tree index structure performance, is an amount of dead space coverage and overlaps among the covering regions. Intuitively, ellipsoid as a quadratic surface should cover data more tightly, leading to less dead s...
Improving two-qubit gate performance and suppressing crosstalk are major, but often competing, challenges to achieving scalable quantum computation. In particular, increasing the coupling realize faster gates has been intrinsically linked enhanced due unwanted terms in Hamiltonian. Here, we demonstrate a novel architecture for transmon qubits that circumvents standard relationship between desir...
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