Over on Shtetl-Optimized, you mention "I'm not answering all things people toss out as I don't want to spam the thread." I expect you're not even referring to me, but FWIW I'll repeat my comment there (which reels in a little my comment above that I wouldn't go to the wall over the choice of mapping),
«Hoel works with Markov processes, but specializes to systems that have an exact macro-state separation: that is, having a diagonal block-matrix presentation. Physical systems, however, are only separable in this way for limited lengths of time. There are small probabilities, for example, of interactions between my fingers, subsystems of my body, and my toes; infrequently, I have to cut my toenails. In general, every entry in a Markov matrix is likely to be non-zero and different from other entries.
To identify how to coarse-grain in the general case, we have to consider either the matrix entries or we have to consider whatever information is not encoded in the Markov matrix (physical adjacency, for example). If the former, an algorithm might, for example, compute an eigenvector basis (over the complex numbers) and compute which to discard (but there's likely a better algorithm!); the algorithm is clearly a source of extra information. If the latter, there's an even clearer source of extra information. In both cases, the Markov process is embedded in a larger system of other degrees of freedom, but we can't just move Hoel's argument to that larger system, because the same problem applies to it (perhaps more so, because now either the matrix or the external information is more complex).»
Perhaps even this doesn't engage with or misunderstands your approach too much for it to be fruitful to engage with it? I always thought my reach into Axiomatic QFT (or more generally, any algebra of observables approach) would likely be too much in my own way of thinking for you, but I'm curious whether you think this later thought illuminates your formalism.