Dimensional Convergence as a Universal Coherence Metric: From Quantum Physics to Cancer Field Organization

Cancer disrupts tissue organization through the loss of coherent bioelectric–morphological coupling, yet existing biomarkers capture molecular rather than field-scale coherence. We apply Dual Boundary Condition Inference (DBCI), a time-symmetric framework that quantifies dimensional collapse—the joint minimization of field gradients and morphological entropy—as a measurable indicator of pathological field disruption. Validation across seven experimental tiers establishes DBCI coherence as a scale-invariant principle. Molecular simulations (H₂, CH₂, NADH, p53) show entropy reduction ΔH ≈ 0.1–0.2 bits under dual-boundary (ABL) reweighting. Clinical inference (breast cancer classification and breath metabolomics; N = 115–569) demonstrates improved discrimination (AUROC = 0.994–0.995) with identical entropy signatures. Cellular validation (N = 4,969 fluorescence micrographs) reveals strong global anticorrelation between bioelectric potential gradients and morphological entropy (ρ = −0.676, p < 10⁻⁵⁰⁰), and tissue-level coherence (ρ_image = −0.633, p < 10⁻¹⁶²). Local (per-ring) measurements yield null correlations (ρ ≈ 0), whereas global (whole-cell) integration produces robust coupling—confirming that dimensional collapse is an emergent, top-down property consistent with the Aharonov–Cohen theorem in quantum foundations [1]. This cross-scale coherence defines a quantitative metric for pathological field organization, offering direct applications in cancer detection and therapy monitoring.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-11
DOI
https://doi.org/10.5281/zenodo.17584132
Primary Topic
Microbial Inactivation Methods
Type
article
Field-Weighted Citation Impact
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article

Dimensional Convergence as a Universal Coherence Metric: From Quantum Physics to Cancer Field Organization

Zenodo (CERN European Organization for Nuclear Research)
Microbial Inactivation Methods
article

Dimensional Convergence as a Universal Coherence Metric: From Quantum Physics to Cancer Field Organization

article en

Abstract

Cancer disrupts tissue organization through the loss of coherent bioelectric–morphological coupling, yet existing biomarkers capture molecular rather than field-scale coherence. We apply Dual Boundary Condition Inference (DBCI), a time-symmetric framework that quantifies dimensional collapse—the joint minimization of field gradients and morphological entropy—as a measurable indicator of pathological field disruption. Validation across seven experimental tiers establishes DBCI coherence as a scale-invariant principle. Molecular simulations (H₂, CH₂, NADH, p53) show entropy reduction ΔH ≈ 0.1–0.2 bits under dual-boundary (ABL) reweighting. Clinical inference (breast cancer classification and breath metabolomics; N = 115–569) demonstrates improved discrimination (AUROC = 0.994–0.995) with identical entropy signatures. Cellular validation (N = 4,969 fluorescence micrographs) reveals strong global anticorrelation between bioelectric potential gradients and morphological entropy (ρ = −0.676, p < 10⁻⁵⁰⁰), and tissue-level coherence (ρ_image = −0.633, p < 10⁻¹⁶²). Local (per-ring) measurements yield null correlations (ρ ≈ 0), whereas global (whole-cell) integration produces robust coupling—confirming that dimensional collapse is an emergent, top-down property consistent with the Aharonov–Cohen theorem in quantum foundations [1]. This cross-scale coherence defines a quantitative metric for pathological field organization, offering direct applications in cancer detection and therapy monitoring.

Zenodo (CERN European Organization for Nuclear Research)
Bar-Ilan University (IL), European Institute for Advanced Studies in Management (BE), Institut de Recerca Biomèdica Catalunya Sud (ES)
Reduced inequalities
Openalex Percentile: Top 38%
Microbial Inactivation Methods
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