Valentin Maestracci

dblp:283/4552 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2025
—ORCID · none

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Theory of computation · 2 · 1 first-author · 2 since 2021
YearPublicationVenuePosition
2025 The Lambda Calculus Is Quantifiable
abstract
In this paper we introduce several quantitative methods for the lambda-calculus based on partial metrics, a well-studied variant of standard metric spaces that have been used to metrize non-Hausdorff topologies, like those arising from Scott domains. First, we study quantitative variants, based on program distances, of sensible equational theories for the λ-calculus, like those arising from Böhm trees and from the contextual preorder. Then, we introduce applicative distances capturing higher-order Scott topologies, including reflexive objects like the D_∞ model. Finally, we provide a quantitative insight on the well-known connection between the Böhm tree of a λ-term and its Taylor expansion, by showing that the latter can be presented as an isometric transformation.
Valentin Maestracci, Paolo Pistone
CSL1
2025 Functorial Models of Differential Linear Logic
abstract
Differentiation in logic has several sources of inspiration. The most recent is differentiable programming, models of which demand functoriality and good typing properties. More historical is reverse denotational semantics, taking inspiration from models of Linear Logic to differentiate proofs and λ-terms. In this paper, we take advantage of the rich structure of categorical models of Linear Logic to give a new functorial presentation of differentiation. We define differentiation as a functor from a coslice of the category of smooth maps to the category of linear maps. Extending linear-non-linear adjunction models of Linear Logic, this produces models of Differential Linear Logic. We use these functorial presentations to shed new light on integration in differential categories.
Marie Kerjean, Valentin Maestracci, Morgan Rogers
FSCD2