Orbit Computation for Atomically Generated Subgroups of Isometries of Zn\mathbb{Z}^n

preprint2020arXivOpen access

Abstract

Isometries are ubiquitous in nature; isometries of discrete (quantized) objects---abstracted as the group of isometries of Zn\mathbb{Z}^n denoted by ISO(Zn)\mathsf{ISO}(\mathbb{Z}^n)---are important concepts in the computational world. In this paper, we compute various isometric invariances which mathematically are orbit-computation problems under various isometry-subgroup actions H↷Zn,H≤ISO(Zn)H \curvearrowright \mathbb{Z}^n, H \leq \mathsf{ISO}(\mathbb{Z}^n). One computational challenge here is about the \emph{infinite}: in general, we can have an infinite subgroup acting on Zn\mathbb{Z}^n, resulting in possibly an infinite number of orbits of possibly infinite size. In practice, we restrict the set of orbits (a partition of Zn\mathbb{Z}^n) to a finite subset Z⊆ZnZ \subseteq \mathbb{Z}^n (a partition of ZZ), where ZZ is specified a priori by an application domain or a data set. Our main contribution is an efficient algorithm to solve this \emph{restricted} orbit-computation problem in the special case of \emph{atomically generated subgroups}---a new notion partially motivated from interpretable AI. The atomic property is key to preserving the \emph{semidirect-product structure}---the core structure we leverage to make our algorithm outperform generic approaches. Besides algorithmic merit, our approach enables \emph{parallel-computing} implementations in many subroutines, which can further benefit from hardware boosts. Moreover, our algorithm works efficiently for \emph{any} finite subset (ZZ) regardless of the shape (continuous/discrete, (non)convex) or location; so it is application-independent.

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