Novel framework encodes abstract categories into vector spaces, preserving structural integrity and details.
We introduce a novel structural framework for encoding arbitrary abstract categories into the category of vector spaces. While the category of vector spaces isstructurally rich, classical representation methods that utilize direct functors oftenlead to a loss of fine logical and structural details of the source category. To resolvethis, we propose an intermediate scalar encoding mechanism. We define a generative functor that maps objects to field-valued functions, which subsequently act asscaling endomorphisms on vector spaces. This construction preserves the structuralintegrity of the abstract category without succumbing to the dimensional complexities of direct matrix representations, providing a rigorous translation of abstractmorphisms into localized linear transformation menariomar6@gmail.com
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Omar. M'NARI (2026) studied this question.
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