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This theoretical framework analyzes measurement dynamics in quantum theory, suggesting a need for a fundamental measurement postulate.
Measurement is not taken to be a fundamental act, an observer intervention, or a separate kind of physics. It is an ordinary system-apparatus-environment process described with a retained physical record. If that record is discarded, the same coupling is represented only by a nonselective channel. Decoherence can suppress interference and stabilize preferred records, but the record-discarded channel does not contain an outcome label or a conditional state update. We make this data distinction exact in finite-dimensional quantum theory and then state its consequence for Modal Triplet Theory (MTT). For an orthogonal pointer resolution, the associated dephasing channel is completely positive and trace preserving, removes every off-diagonal pointer block, and preserves all pointer populations. We prove that the same nonselective channel is compatible with distinct outcome instruments having different probability laws. Hence the channel alone specifies neither records nor their probabilities. An MTT basin boundary or chart exit has the same logical limitation: it marks the failure of a supplied effective chart, but it does not choose a successor basin. A complete outcome-resolved model must additionally provide an outcome-indexed completely positive instrument or a normalized selection-completion kernel, together with its source and domain. This yields a rigorous conditional bridge between record-discarded intra-basin suppression and record-resolved inter-basin continuation. Both are ordinary physical dynamics; the distinction concerns which data the effective description retains. The current canonical q79 binary recorder supplies an exact stopped-output law on its declared finite domain, but general apparatus contexts, a universal Born-source theorem, and objective single-history actualization remain open. Projection, noninjectivity, admissibility loss, and chart exit alone specify none of those missing outcome-resolved data.
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Peter Nero (2026) studied this question.
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