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Architecture and Extensions of the Shadow Function in the Prescriptive Mathematics Paradigm: From Quantum Collapse to Ontological Engineering of Macro-Systems

Vlasie Catalin Mircea

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.13140/rg.2.2.21529.58725

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Paradoxes and Primitive Ontology in Collapse Theories of Quantum Mechanics

Roderich Tumulka

Collapse theories are versions of quantum mechanics according to which the collapse of the wave function is a real physical process. They propose precise mathematical laws to govern this process and to replace the vague conventional prescription that a collapse occurs whenever an "observer" makes a "measurement." The "primitive ontology" of a theory (more or less what Bell called the "local beables") are the variables in the theory that represent matter in space-time. There is no consensus about whether collapse theories need to introduce a primitive ontology as part of their definition. I make some remarks on this question and point out that certain paradoxes about collapse theories are absent if a primitive ontology is introduced.

arXiv:1102.5767•Feb 28, 2011•35 citations

The Two-Phase Universe: Quantum Ontology for Biology, AI, Cognition and Computation

John Carew

Quantum biology has emerged as a transformative field, demonstrating that non-classical quantum effects—such as coherence, tunneling, entanglement, and spin-dependent dynamics—play functional roles in living systems under physiological conditions that were previously assumed to be exclusively classical. This revelation challenges long-held assumptions about the boundaries between quantum and classical regimes in complex, warm, and noisy environments. However, despite significant empirical and theoretical advances, quantum biology lacks a comprehensive ontological framework that explains not only how these effects persist but why biological evolution has repeatedly converged on structures that exploit them for adaptive advantages. This paper advances the Two-Phase Universe (TPU) [1] as such a foundational ontology, extending its application to quantum biology, cognitive architecture, and artificial intelligence (AI) design.TPU posits a dual-substrate reality consisting of a timeless, nonlocal Cold-Phase (an informational substrate devoid of geometry or causality) and an emergent Warm-Phase (the dynamical domain of spacetime, fields, and classical interactions). Within this framework, quantum phenomena are reinterpreted as statistical manifestations of sampling interactions between the phases, modulated by biological structures to achieve functional optimality. We develop detailed mathematical formalisms for sampling density, bonded mechanisms, and effective dynamics, providing a rigorous basis for analysis.The Bonded Warm-Phase Hypothesis is introduced, proposing that biological micro-elements (e.g., spins, tunneling protons, excitons) form "tight bonds" to the Cold-Phase, inheriting its timeless and nonlocal properties for hyper-efficient information processing, while remaining anchored in Warm-Phase macro-structures to maintain stability and prevent gravitational collapse. Through in-depth reanalysis of key experimental data and case studies from photosynthesis [2,12], magnetoreception [4-6], DNA proton tunneling [7,8], and enzyme catalysis [9], we demonstrate that biology operates as a sophisticated technology of Sampling Modulation.Extensions to cognitive architecture explain phenomena like intuitive decision-making and "Aha!" moments as non-causal path exploration in neural low-sampling windows [13,16]. For AI, TPU suggests substrate-aware architectures that mimic bonded computation, potentially enabling energy-efficient, intuitive systems far beyond current bit-based paradigms. This unified framework reveals life and mind as interfaces between timeless substrate and temporal dynamics, opening new research avenues in biology, neuroscience, and computation. Testable predictions include correlations between structural features and coherence lifetimes, mutation hotspots linked to sampling minima, and enhanced performance in engineered biomolecules with modulated sampling density.

•Jan 22, 2026•0 citations
Collapse theories are versions of quantum mechanics according to which the collapse of the wave function is a real physical process. They propose precise mathematical laws to govern this process and to replace the vague conventional prescription that a collapse occurs whenever an "observer" makes a "measurement." The "primitive ontology" of a theory (more or less what Bell called the "local beables") are the variables in the theory that represent matter in space-time. There is no consensus about whether collapse theories need to introduce a primitive ontology as part of their definition. I make some remarks on this question and point out that certain paradoxes about collapse theories are absent if a primitive ontology is introduced.
Quantum biology has emerged as a transformative field, demonstrating that non-classical quantum effects—such as coherence, tunneling, entanglement, and spin-dependent dynamics—play functional roles in living systems under physiological conditions that were previously assumed to be exclusively classical. This revelation challenges long-held assumptions about the boundaries between quantum and classical regimes in complex, warm, and noisy environments. However, despite significant empirical and theoretical advances, quantum biology lacks a comprehensive ontological framework that explains not only how these effects persist but why biological evolution has repeatedly converged on structures that exploit them for adaptive advantages. This paper advances the Two-Phase Universe (TPU) [1] as such a foundational ontology, extending its application to quantum biology, cognitive architecture, and artificial intelligence (AI) design.TPU posits a dual-substrate reality consisting of a timeless, nonlocal Cold-Phase (an informational substrate devoid of geometry or causality) and an emergent Warm-Phase (the dynamical domain of spacetime, fields, and classical interactions). Within this framework, quantum phenomena are reinterpreted as statistical manifestations of sampling interactions between the phases, modulated by biological structures to achieve functional optimality. We develop detailed mathematical formalisms for sampling density, bonded mechanisms, and effective dynamics, providing a rigorous basis for analysis.The Bonded Warm-Phase Hypothesis is introduced, proposing that biological micro-elements (e.g., spins, tunneling protons, excitons) form "tight bonds" to the Cold-Phase, inheriting its timeless and nonlocal properties for hyper-efficient information processing, while remaining anchored in Warm-Phase macro-structures to maintain stability and prevent gravitational collapse. Through in-depth reanalysis of key experimental data and case studies from photosynthesis [2,12], magnetoreception [4-6], DNA proton tunneling [7,8], and enzyme catalysis [9], we demonstrate that biology operates as a sophisticated technology of Sampling Modulation.Extensions to cognitive architecture explain phenomena like intuitive decision-making and "Aha!" moments as non-causal path exploration in neural low-sampling windows [13,16]. For AI, TPU suggests substrate-aware architectures that mimic bonded computation, potentially enabling energy-efficient, intuitive systems far beyond current bit-based paradigms. This unified framework reveals life and mind as interfaces between timeless substrate and temporal dynamics, opening new research avenues in biology, neuroscience, and computation. Testable predictions include correlations between structural features and coherence lifetimes, mutation hotspots linked to sampling minima, and enhanced performance in engineered biomolecules with modulated sampling density.