Efficient data structures for masks on 2D grids

TL;DR

This paper explores efficient data structures for representing and manipulating 2D coverage masks, optimizing space and time for storage, processing, and transmission, with applications in astronomy and beyond.

Contribution

It introduces novel methods for space- and time-efficient representation of 2D coverage masks applicable across various fields.

Findings

Proposes new data structures for 2D masks

Demonstrates improved efficiency in storage and processing

Applicable to astronomical and other spatial data tasks

Abstract

This article discusses various methods of representing and manipulating arbitrary coverage information in two dimensions, with a focus on space- and time-efficiency when processing such coverages, storing them on disk, and transmitting them between computers. While these considerations were originally motivated by the specific tasks of representing sky coverage and cross-matching catalogues of astronomical surveys, they can be profitably applied in many other situations as well.