Shadow Mining: Inferring Higher-Grade Structure from Lower-Grade Data
Every finite-dimensional approximation of a dynamical system loses information. The Shadow Principle (Nagy 2026a) establishes that this loss is structurally detectable but not exactly measurable: the projected system can know *that* something is missing, and approximately *how much*, but not *what*.
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