## Abstract

Robustness is a property of system analyses, namely monotonic maps from the complete lattice of subsets of a (system's state) space to the two-point lattice. The definition of robustness requires the space to be a metric space. Robust analyses cannot discriminate between a subset of the metric space and its closure; therefore, one can restrict to the complete lattice of closed subsets. When the metric space is compact, the complete lattice of closed subsets ordered by reverse inclusion is <![CDATA[ $\omega$ ]]> -continuous, and robust analyses are exactly the Scott-continuous maps. Thus, one can also ask whether a robust analysis is computable (with respect to a countable base). The main result of this paper establishes a relation between robustness and Scott continuity when the metric space is not compact. The key idea is to replace the metric space with a compact Hausdorff space, and relate robustness and Scott continuity by an adjunction between the complete lattice of closed subsets of the metric space and the <![CDATA[ $\omega$ ]]> -continuous lattice of closed subsets of the compact Hausdorff space. We demonstrate the applicability of this result with several examples involving Banach spaces.

Original language | English |
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Journal | Mathematical Structures in Computer Science |

DOIs | |

Publication status | Accepted/In press - 2023 |

## Keywords

- category theory
- continuous lattices
- Keywords:
- Robustness
- topology

## ASJC Scopus subject areas

- Mathematics (miscellaneous)
- Computer Science Applications