This paper is an overview of existing applications of Linear Logic (LL) to issues of computation. After a substantial introduction to LL, it discusses the implications of LL to functional programming, logic programming, concurrent and object-oriented programming and some other applications of LL, like semantics of negation in LP, non-monotonic issues in AI planning, etc. Although the overview covers pretty much the state-of-the-art in this area, by necessity many of the works are only mentioned and referenced, but not discussed in any considerable detail. The paper does not presuppose any previous exposition to LL, and is addressed more to computer scientists (probably with a theoretical inclination) than to logicians. The paper contains over 140 references, of which some 80 are about applications of LL. 1 Linear Logic Linear Logic (LL) was introduced in 1987 by Girard [62]. From the very beginning it was recognized as relevant to issues of computation (especially concurrency and stat...

this paper was quite di#erent, stemming from the axiomatics of categories of tangles (although the authors were aware of possible connections to iteration theories. In fact, similar axiomatics in the symmetric case, motivated by flowcharts and "flownomials" had been developed some years earlier by Stefanescu (Stefanescu 2000).) However, the first author realized, following a stimulating discussion with Gordon Plotkin, that traced monoidal categories provided a common denominator for the axiomatics of both the Girard-style and Abramsky-Jagadeesan-style versions of the Geometry of Interaction, at the basic level of the multiplicatives. This insight was presented in (Abramsky 1996), in which Girard-style GoI was dubbed "particle-style", since it concerns information particles or tokens flowing around a network, while the Abramsky-Jagadeesan style GoI was dubbed "wave-style", since it concerns the evolution of a global information state or "wave". Formally, this distinction is based on whether the tensor product (i.e. the symmetric monoidal structure) in the underlying category is interpreted as a coproduct (particle style) or as a product (wave style). This computational distinction between coproduct and product interpretations of the same underlying network geometry turned out to have been partially anticipated, in a rather di#erent context, in a pioneering paper by E. S. Bainbridge (Bainbridge 1976), as observed by Dusko Pavlovic. These two forms of interpretation, and ways of combining them, have also been studied recently in (Stefanescu 2000). He uses the terminology "additive" for coproduct-based (i.e. our "particle-style") and "multiplicative" for product-based (i.e. our "wave-style"); this is not suitable for our purposes, because of the clash with Linear Logic term...

The classical lambda calculus may be regarded both as a programming language and as a formal algebraic system for reasoning about computation. It provides a computational model equivalent to the Turing machine, and continues to be of enormous benefit in the classical theory of computation. We propose that quantum computation, like its classical counterpart, may benefit from a version of the lambda calculus suitable for expressing and reasoning about quantum algorithms. In this paper we develop a quantum lambda calculus as an alternative model of quantum computation, which combines some of the benefits of both the quantum Turing machine and the quantum circuit models. The calculus turns out to be closely related to the linear lambda calculi used in the study of Linear Logic. We set up a computational model and an equational proof system for this calculus, and we argue that it is equivalent to the quantum Turing machine.

Linear logic is a resource-aware logic that is based on an analysis of the classical proof rules of contraction (copying) and weakening (throwing away). In this paper we study the decision problem for the multiplicative fragment of linear logic without quantifiers or propositions: the constant-only case. We show that this fragment is np-complete. Earlier work by Max Kanovich showed that propositional multiplicative linear logic is np-complete. With Natarajan Shankar, the first author developed a simplified proof for the propositional case. The structure of this simplified proof is utilized here with a new encoding which uses only constants. The end product is the somewhat surprising result that simply evaluating expressions in true, false, and, and or in multiplicative linear logic (\Omega , , 1, and ?) is np-complete. By conservativity results not proven here, the np-hardness of larger fragments of linear logic follows. 1 Introduction When Girard introduced linear logic [7], he bro...

Models of intuitionistic linear logic also provide models of Moggi's computational metalanguage. We use the adjoint presentation of these models and the associated adjoint calculus to show that three translations, due mainly to Moggi, of the lambda calculus into the computational metalanguage (direct, call-by-name and call-by-value) correspond exactly to three translations, due mainly to Girard, of intuitionistic logic into intuitionistic linear logic. We also consider extending these results to languages with recursion. 1. Introduction Two of the most significant developments in semantics during the last decade are Girard's linear logic [10] and Moggi's computational metalanguage [14]. Any student of these formalisms will suspect that there are significant connections between the two, despite their apparent differences. The intuitionistic fragment of linear logic (ILL) may be modelled in a linear model -- a symmetric monoidal closed category with a comonad ! which satisfies some extr...

Girard described two translations of intuitionistic logic into linear logic, one where A -> B maps to (!A) -o B, and another where it maps to !(A -o B). We detail the action of these translations on terms, and show that the first corresponds to a call-by-name calculus, while the second corresponds to call-by-value. We further show that if the target of the translation is taken to be an affine calculus, where ! controls contraction but weakening is allowed everywhere, then the second translation corresponds to a call-by-need calculus, as recently defined by Ariola, Felleisen, Maraist, Odersky, and Wadler. Thus the different calling mechanisms can be explained in terms of logical translations, bringing them into the scope of the Curry-Howard isomorphism.

Surprisingly, there is not a good fit between a syntax for linear logic in the style of Abramsky, and a semantics in the style of Seely. Notably, the Substitution Lemma is valid if and only if !A and !!A are isomorphic in a canonical way. An alternative syntax is proposed, that has striking parallels to Moggi's language for monads. In the old syntax, some terms look like the identity that should not, and vice versa; the new syntax eliminates this awkwardness. 1 Introduction This paper has two purposes: to show that linear logic has no substitute, and to propose one. The first part presents a standard syntax and semantics for linear logic, and notes some resulting difficulties. The linear logic is that of Girard [Gir87]. The syntax is based on lambda terms, following in the footsteps of Abramsky [Abr90]: the four rules associated with the `of course' type, Weakening, Contraction, Dereliction, and Promotion, are each represented by a separate term form. The semantics is based on categor...

Abstract not found

Concurrent computation can be given an abstract mathematical treatment very similar to that provided for sequential computation by domain theory and denotational semantics of Scott and Strachey.

Vol. 2 (4:3) 2006, pp. 1–44 www.lmcs-online.org