This approach reminds me of RedisGraph[1] (which is now unfortunately EoL).
"RedisGraph is the first queryable Property Graph database to use sparse matrices to represent the adjacency matrix in graphs and linear algebra to query the graph."
"RedisGraph is the first queryable Property Graph database to use sparse matrices to represent the adjacency matrix in graphs and linear algebra to query the graph."
Justify Linked Data; https://5stardata.info/
W3C RDF-star and SPARQL-star > 2.2 RDF-star Graph Examples: https://w3c.github.io/rdf-star/cg-spec/editors_draft.html#rd...
def to_matrices(g: rdflib.MultiDiGraph) -> Union[Matrix, Tensor]
Multigraph: https://en.wikipedia.org/wiki/Multigraph :
> In mathematics, and more specifically in graph theory, a multigraph is a graph which is permitted to have multiple edges (also called parallel edges[1]), that is, edges that have the same end nodes. Thus two vertices may be connected by more than one edge ... [which requires multidimensional matrices, netcdf (pydata/xarray,), tensors, or a better implementation of a representation; and edge reification in RDF]
From "Why tensors? A beginner's perspective" https://news.ycombinator.com/item?id=30629931 :
> https://en.wikipedia.org/wiki/Tensor
... Tensor product of graphs: https://en.wikipedia.org/wiki/Tensor_product_of_graphs
Hilbert space: https://en.wikipedia.org/wiki/Hilbert_space :
> The inner product between two state vectors is a complex number known as a probability amplitude.