Robustness, Scott continuity, and computability

Amin Farjudian, Eugenio Moggi

Research output: Journal PublicationArticlepeer-review


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 languageEnglish
JournalMathematical Structures in Computer Science
Publication statusAccepted/In press - 2023


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

ASJC Scopus subject areas

  • Mathematics (miscellaneous)
  • Computer Science Applications


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