Relating toy models of quantum computation: comprehension, complementarity and dagger mix autonomous categories
Dusko Pavlovic

TL;DR
This paper combines category theory and toy models of quantum computation to develop a new categorical framework called dagger mix autonomous categories, capturing quantum features like complementarity and propositions.
Contribution
It introduces the comprehension construction to extend toy models, resulting in a novel categorical structure that unifies quantum features within a broad mathematical framework.
Findings
Models share the same categorical structure.
Extension of test space models with comprehension construction.
Dagger mix autonomous categories naturally arise in quantum computation.
Abstract
Toy models have been used to separate important features of quantum computation from the rich background of the standard Hilbert space model. Category theory, on the other hand, is a general tool to separate components of mathematical structures, and analyze one layer at a time. It seems natural to combine the two approaches, and several authors have already pursued this idea. We explore *categorical comprehension construction* as a tool for adding features to toy models. We use it to comprehend quantum propositions and probabilities within the basic model of finite-dimensional Hilbert spaces. We also analyze complementary quantum observables over the category of sets and relations. This leads into the realm of *test spaces*, a well-studied model. We present one of many possible extensions of this model, enabled by the comprehension construction. Conspicuously, all models obtained in…
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Taxonomy
TopicsQuantum Mechanics and Applications · Computability, Logic, AI Algorithms · Quantum Computing Algorithms and Architecture
