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Unitary-orbit classification and a refinement theorem for context-independent projective probabilities

arXiv
Authors: Michael P. Rubin

Year

2026

Paper ID

75793

Status

Preprint

Abstract Read

~2 min

Abstract Words

259

Citations

N/A

Abstract

Let mathcal H be a finite-dimensional complex Hilbert space, and let w\(P,mathsf M\) be a normalized probability weight assigned to an outcome projection P as it occurs in a projective measurement mathsf M. For fixed P, let GPcongmathcal U\(Pperp\) be the group of unitaries acting identically on operatorname{ran}P and arbitrarily on Pperp. We classify the GP-orbits of projective measurements containing P: two measurements lie in the same orbit exactly when the multisets of ranks of their complementary outcomes agree. The orbit with profile λ=\(r1,ldots,rk\) is a compact homogeneous space of real dimension \(d-operatorname{rank}P\)2-sumj rj2. On maximal rank-one measurements there is one orbit, so context independence is equivalent to GP-invariance, with equality of the corresponding uniform defects; invariance under two-level complementary unitaries already suffices. For arbitrary projective measurements, every context containing an outcome Pneq I coarsens to the unique binary context \{P,I-P\}. Consequently, refinement consistency alone is equivalent to context independence. The finite orbit space carries a natural rank-profile refinement graph, whose diameter is d-operatorname{rank}P-1 when Pneq I. We prove a stability theorem that compares the binary-coarsening path with a shortest path in this graph followed by one complementary unitary. In dimension at least three, Gleason's theorem converts the maximal-context invariance condition and the all-context refinement condition, on their respective domains, into the Born form operatorname{Tr}(ρP). The results are structural characterizations, not independent physical derivations of context independence.

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  • Let mathcal H be a finite-dimensional complex Hilbert space, and let w(P,mathsf M) be a normalized probability weight assigned to an outcome projection P as it occurs in a...

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