Monoidal computer III: A coalgebraic view of computability and complexity

TL;DR

This paper presents a coalgebraic framework for monoidal computers, offering a high-level, diagrammatic approach to understanding computability and complexity through state machines and categorical models.

Contribution

It introduces a coalgebraic characterization of monoidal computers, linking interpreters and specializers to universal state spaces and state machines.

Findings

Provides a coalgebraic view of monoidal computers

Shows how to represent Turing machines and their execution

Offers a diagrammatic language for computability and complexity

Abstract

Monoidal computer is a categorical model of intensional computation, where many different programs correspond to the same input-output behavior. The upshot of yet another model of computation is that a categorical formalism should provide a much needed high level language for theory of computation, flexible enough to allow abstracting away the low level implementation details when they are irrelevant, or taking them into account when they are genuinely needed. A salient feature of the approach through monoidal categories is the formal graphical language of string diagrams, which supports visual reasoning about programs and computations. In the present paper, we provide a coalgebraic characterization of monoidal computer. It turns out that the availability of interpreters and specializers, that make a monoidal category into a monoidal computer, is equivalent with the existence of a *universal state space*, that carries a weakly final state machine for any pair of input and output types. Being able to program state machines in monoidal computers allows us to represent Turing machines, to capture their execution, count their steps, as well as, e.g., the memory cells that they use. The coalgebraic view of monoidal computer thus provides a convenient diagrammatic language for studying computability and complexity.