Modelling Multiplicative Linear Logic via Deep Inference

Tomer Galor; Andrea Schalk

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arXiv · 2404.01026

Modelling Multiplicative Linear Logic via Deep Inference

Tomer Galor·Andrea Schalk

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Abstract

Multiplicative linear logic is a very well studied formal system, and most such studies are concerned with the one-sided sequent calculus. In this paper we look in detail at existing translations between a deep inference system and the standard sequent calculus one, provide a simplified translation, and provide a formal proof that a standard approach to modelling is indeed invariant to all these translations. En route we establish a necessary condition for provable sequents related to the number of pars and tensors in a formula that seems to be missing from the literature.

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BibTeX RIS

Tomer Galor, Andrea Schalk. 2024-04-01. Modelling Multiplicative Linear Logic via Deep Inference. https://arxiv.org/abs/2404.01026

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