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Searching spatial data is an important operation for scientific simulationswhich are performed mostly with periodic boundary conditions. An R-Tree is awell known tree data structure used to contain spatial objects and it iscapable of answering to spatial searching queries in an efficient way. In thispaper, a novel method to construct an R-Tree considering periodic boundaryconditions is presented. Unlike existing methods, the proposed method workswithout any kind of extra objects or queries. Moreover, because this methodreduces the volume of bounding box for each node under the periodic boundaryconditions, it is expected to increase the overall efficiency. While theextension of an R-Tree is presented in this work, this method is not onlyapplicable to an R-Tree but also to other data structures that use axis-alignedbounding boxes with periodic boundary conditions. The implementation isavailable on GitHub.

Periortree: An Extention of R-Tree for Periodic Boundary Conditions