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Born Statistics from Decoherence and Contraction Dynamics on Projective Hilbert Space

Elythian

Published Jan 1, 2026• 0 citations
Publisher

Abstract

We derive the Born rule as a consequence of two physical processes: environment-induced decoherence, which selects the pointer-basis decomposition of the density matrix, and a contraction map on projective Hilbert space, which assigns each pointer state to a definite outcome basin. The contraction map partitions projective space into basins of attraction whose boundaries are determined by the measurement projectors. We prove that the decoherence-selected decomposition of the reduced density matrix, combined with the basin assignment, reproduces the Born probabilities p_i = ⟨ψ|Π_i|ψ⟩ exactly for projective measurements in any finite dimension, including dimension 2 where Gleason's theorem does not apply. For generalized measurements (POVMs), the result extends via Naimark dilation. The derivation resolves the "probability problem" of decoherence-based approaches: standard decoherence produces the correct diagonal density matrix but leaves open why diagonal entries should be interpreted as outcome probabilities. Our answer is geometric — each diagonal component corresponds to a pointer state lying deep inside a definite basin of the contraction map, and the mixture weights become outcome probabilities through the basin assignment. The derivation is geometric rather than decision-theoretic, does not assume the probability interpretation of the density matrix, requires no ensemble averaging, and applies to single systems. Perturbations to the contraction map produce bounded corrections to the Born probabilities, providing a falsifiable prediction: any measured deviation from Born statistics constrains the perturbation strength. This work connects quantum measurement theory to the geometry of projective Hilbert space and contraction dynamics, offering a new perspective on the origin of quantum probabilities that complements existing approaches by Gleason, Zurek, and Deutsch-Wallace.

DOI
10.17605/osf.io/9p46n

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We derive the Born rule as a consequence of two physical processes: environment-induced decoherence, which selects the pointer-basis decomposition of the density matrix, and a contraction map on projective Hilbert space, which assigns each pointer state to a definite outcome basin. The contraction map partitions projective space into basins of attraction whose boundaries are determined by the measurement projectors. We prove that the decoherence-selected decomposition of the reduced density matrix, combined with the basin assignment, reproduces the Born probabilities p_i = ⟨ψ|Π_i|ψ⟩ exactly for projective measurements in any finite dimension, including dimension 2 where Gleason's theorem does not apply. For generalized measurements (POVMs), the result extends via Naimark dilation. The derivation resolves the "probability problem" of decoherence-based approaches: standard decoherence produces the correct diagonal density matrix but leaves open why diagonal entries should be interpreted as outcome probabilities. Our answer is geometric — each diagonal component corresponds to a pointer state lying deep inside a definite basin of the contraction map, and the mixture weights become outcome probabilities through the basin assignment. The derivation is geometric rather than decision-theoretic, does not assume the probability interpretation of the density matrix, requires no ensemble averaging, and applies to single systems. Perturbations to the contraction map produce bounded corrections to the Born probabilities, providing a falsifiable prediction: any measured deviation from Born statistics constrains the perturbation strength. This work connects quantum measurement theory to the geometry of projective Hilbert space and contraction dynamics, offering a new perspective on the origin of quantum probabilities that complements existing approaches by Gleason, Zurek, and Deutsch-Wallace.
We derive the Born rule as a consequence of two physical processes: environment-induced decoherence, which selects the pointer-basis decomposition of the density matrix, and a contraction map on projective Hilbert space, which assigns each pointer state to a definite outcome basin. The contraction map partitions projective space into basins of attraction whose boundaries are determined by the measurement projectors. We prove that the decoherence-selected decomposition of the reduced density matrix, combined with the basin assignment, reproduces the Born probabilities p_i = ⟨ψ|Π_i|ψ⟩ exactly for projective measurements in any finite dimension, including dimension 2 where Gleason's theorem does not apply. For generalized measurements (POVMs), the result extends via Naimark dilation. The derivation resolves the "probability problem" of decoherence-based approaches: standard decoherence produces the correct diagonal density matrix but leaves open why diagonal entries should be interpreted as outcome probabilities. Our answer is geometric — each diagonal component corresponds to a pointer state lying deep inside a definite basin of the contraction map, and the mixture weights become outcome probabilities through the basin assignment. The derivation is geometric rather than decision-theoretic, does not assume the probability interpretation of the density matrix, requires no ensemble averaging, and applies to single systems. Perturbations to the contraction map produce bounded corrections to the Born probabilities, providing a falsifiable prediction: any measured deviation from Born statistics constrains the perturbation strength. This work connects quantum measurement theory to the geometry of projective Hilbert space and contraction dynamics, offering a new perspective on the origin of quantum probabilities that complements existing approaches by Gleason, Zurek, and Deutsch-Wallace.
We derive the Born rule as a consequence of two physical processes: environment-induced decoherence, which selects the pointer-basis decomposition of the density matrix, and a contraction map on projective Hilbert space, which assigns each pointer state to a definite outcome basin. The contraction map partitions projective space into basins of attraction whose boundaries are determined by the measurement projectors. We prove that the decoherence-selected decomposition of the reduced density matrix, combined with the basin assignment, reproduces the Born probabilities p_i = ⟨ψ|Π_i|ψ⟩ exactly for projective measurements in any finite dimension, including dimension 2 where Gleason's theorem does not apply. For generalized measurements (POVMs), the result extends via Naimark dilation. The derivation resolves the "probability problem" of decoherence-based approaches: standard decoherence produces the correct diagonal density matrix but leaves open why diagonal entries should be interpreted as outcome probabilities. Our answer is geometric — each diagonal component corresponds to a pointer state lying deep inside a definite basin of the contraction map, and the mixture weights become outcome probabilities through the basin assignment. The derivation is geometric rather than decision-theoretic, does not assume the probability interpretation of the density matrix, requires no ensemble averaging, and applies to single systems. Perturbations to the contraction map produce bounded corrections to the Born probabilities, providing a falsifiable prediction: any measured deviation from Born statistics constrains the perturbation strength. This work connects quantum measurement theory to the geometry of projective Hilbert space and contraction dynamics, offering a new perspective on the origin of quantum probabilities that complements existing approaches by Gleason, Zurek, and Deutsch-Wallace.
We derive the Born rule as a consequence of two physical processes: environment-induced decoherence, which selects the pointer-basis decomposition of the density matrix, and a contraction map on projective Hilbert space, which assigns each pointer state to a definite outcome basin. The contraction map partitions projective space into basins of attraction whose boundaries are determined by the measurement projectors. We prove that the decoherence-selected decomposition of the reduced density matrix, combined with the basin assignment, reproduces the Born probabilities p_i = ⟨ψ|Π_i|ψ⟩ exactly for projective measurements in any finite dimension. For generalized measurements (POVMs), the result extends via Naimark dilation. Perturbations to the contraction map (modeling external bias) shift the basin boundaries, producing corrections bounded by the perturbation strength. The derivation is geometric rather than decision-theoretic, does not assume the probability interpretation of the density matrix, and applies to single systems without ensemble averaging.
We derive the Born probability rule as a theorem within the Time–Scalar Field Theory (TSFT) spectral-geometry program. Assuming only that measurement outcomes correspond to orthogonal spectral projectors on the TSFT Hilbert space and that probability assignments are additive on exclusive outcomes and noncontextual with respect to commuting decompositions, we obtain a unique projector measure. By Gleason-type arguments (with a qubit patch via ancilla embedding or POVM extension), the probability of an outcome projector P must take the trace form μ(P) = Tr(ρP) for some density operator ρ. For pure states this reduces to μ(P) = ⟨ψ|P|ψ⟩, yielding the Born rule without invoking external quantum axioms.