In high-dimensional Hilbert spaces, near-orthogonality of almost all vectors supplies an exponentially large reservoir of mutually quasi-orthogonal environmental records that makes decoherence overwhelmingly effective for macroscopic systems.
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No universal trading strategy exists that generates strict profits in all market trajectories, as such strategies are precluded by no-arbitrage conditions, no-free-lunch theorems, and adversarial constructions that defeat computable rules.
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The Geometric Part of Decoherence: Quasi-Orthogonality in High-Dimensional Hilbert Spaces
In high-dimensional Hilbert spaces, near-orthogonality of almost all vectors supplies an exponentially large reservoir of mutually quasi-orthogonal environmental records that makes decoherence overwhelmingly effective for macroscopic systems.
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Against a Universal Trading Strategy: No-Arbitrage, No-Free-Lunch, and Adversarial Cantor Diagonalization
No universal trading strategy exists that generates strict profits in all market trajectories, as such strategies are precluded by no-arbitrage conditions, no-free-lunch theorems, and adversarial constructions that defeat computable rules.