A Dissipative Quantum Field Model of Whole-Organism Coherence: A Multi-Field Framework for Biological Integration Across Scales

1. Introduction

Biological systems maintain coherent organization across spatial and temporal scales ranging from nanometers to the scale of the whole organism. Mitochondrial electron and proton transport exhibit signatures of excitonic and collective behavior (Nicholls & Ferguson, 2013; Wallace, 2010), intracellular water forms dipolar ordering domains (Del Giudice, Doglia, Milani & Vitiello, 1985; Pollack, 2013), microtubules support dipole oscillations and collective vibrational modes (Jibu & Yasue, 1995; Hameroff & Penrose, 2014), and large-scale neural and physiological oscillations show long-range phase coherence (Singer, 1999; Freeman, 2000; Goldberger et al., 2002). These phenomena are difficult to reconcile with classical biochemical or electrophysiological frameworks, which rely on local interactions, diffusion, and short-range signaling.

A deeper theoretical issue emerges: How do living systems preserve extended, robust coherence under permanently dissipative conditions? Traditional models of biochemical regulation do not explain long-range correlations, abrupt transitions between coherent states, or the integration of cellular, physiological, cognitive, and emotional processes into unified organismic dynamics.

Dissipative quantum field theory (DQFT), developed by Celeghini, Rasetti, and Vitiello (1992), offers a mathematically rigorous Framework for addressing such questions. DQFT extends standard quantum field theory by doubling degrees of freedom to represent environmental coupling (Umezawa, 1993; Breuer & Petruccione, 2002), introducing Bogoliubov transformations that generate coherent excitations with condensation amplitudes θₖ (Celeghini, Rasetti & Vitiello, 1992), and yielding unitarily inequivalent vacuum states associated with distinct macroscopic orderings (Vitiello, 1995). These vacua arise through spontaneous symmetry breaking (SSB), generating long-range Nambu–Goldstone modes—dipole-wave quanta (DWQ)—that mediate coherence across scales (Del Giudice et al., 1988; Fröhlich, 1968). Free-energy minimization (Takahashi & Umezawa, 1975) selects dynamically preferred vacua, establishing attractor-like physiological configurations (Blasone, Jizba & Vitiello, 2011).

Although DQFT has been successfully applied to water coherence (Del Giudice et al., 1985), microtubular dynamics (Jibu & Yasue, 1995; Tuszynski, Hameroff & Sataric, 1995), and neural memory models (Ricciardi & Umezawa, 1967; Vitiello, 2001), existing work has focused on individual substrates rather than the organism as an integrated whole. However, physiology comprises multiple interacting domains—metabolic, immune, neural, interoceptive, structural, and electromagnetic—each associated with specific quantum substrates and coherence mechanisms.

The present work proposes a twelve-field coherence architecture representing distinct but coupled sectors of organismic order. Each coherence field Θₖ corresponds to a specific biological substrate undergoing symmetry breaking, with its own condensation amplitude θₖ(t). These fields include foundational intracellular coherence (Θ₁), immune and inflammatory regulation (Θ₂), autonomic balance (Θ₃), interoceptive integration (Θ₄), circulatory and motility coherence (Θ₅), mitochondrial metabolism (Θ₆), regenerative processes (Θ₇), chromatin and morphogenetic structure (Θ₈), circadian and restorative regulation (Θ₉), cognitive integration (Θ₁₀), affective dynamics (Θ₁₁), and whole-organism electromagnetic coherence (Θ₁₂).

By embedding this multi-field architecture into the dissipative QFT formalism, we derive macroscopic equations governing the temporal evolution of θₖ(t), show how these fields collectively define a global free-energy attractor Θ_ref, and introduce an experimentally accessible Biological Coherence Index (BCI) derived from vacuum overlap expressions.

The goal of this article is not to claim that biological systems require quantum explanations, but to show that the mathematical framework of DQFT provides a consistent way to model multi-scale coherence, state transitions, and integrative physiological dynamics. The resulting model offers testable predictions regarding cross-scale coupling, coherence breakdown, and susceptibility to external perturbations, making it relevant for systems biology, biophysics, and integrative physiology.

2. Methods: Dissipative Quantum Field Framework

This section develops the mathematical structure used to model biological coherence across multiple scales. The formalism is based on dissipative quantum field theory (DQFT), which provides a consistent treatment of open-system dynamics, spontaneous symmetry breaking (SSB), and long-range correlations in macroscopic systems (Umezawa, 1993; Celeghini, Rasetti & Vitiello, 1992; Breuer & Petruccione, 2002).

2.1. Operator Doubling and the Open-System Hilbert Space

A defining feature of DQFT is the doubling of degrees of freedom. For every quantum mode relevant to a biological substrate, two operator sets are introduced:

• physical operators: âₖ, âₖ†
• environmental (dissipative) operators: ãₖ, ãₖ†

which satisfy

[âₖ, âⱼ†] = δₖⱼ,

[ãₖ, ãⱼ†] = δₖⱼ,

all mixed commutators vanish.

The system’s Hilbert space becomes a tensor product

H_total = H ⊗ H̃,

where H carries biological excitations (water dipoles, microtubule dipole modes, chromatin excitons, ionic waves) and H̃ encodes environmental fluctuations such as hydration noise, ionic turbulence, or thermal damping (Del Giudice et al., 1985; Jibu & Yasue, 1995; Weiss, 2012).

This doubling is not optional—it is mathematically required to represent irreversible, dissipative dynamics at the operator level (Takahashi & Umezawa, 1975).

2.2. Bogoliubov Transformations and Condensation Amplitudes

Open-system evolution induces mixing between the physical and dissipative operators through Bogoliubov transformations:

Aₖ(θₖ) = âₖ·cosh(θₖ) − ãₖ†·sinh(θₖ)
Ãₖ(θₖ) = ãₖ·cosh(θₖ) − âₖ†·sinh(θₖ)

The real parameter θₖ is the condensation amplitude associated with mode k.

Its condensate density

Nₖ = sinh²(θₖ)

measures the degree of coherent ordering present even in the vacuum state. In biological systems, such condensation may correspond to water-domain coherence (Del Giudice et al., 1985; Pollack, 2013), microtubule dipole alignment (Jibu & Yasue, 1995; Hameroff & Penrose, 2014), chromatin excitonic ordering (Montagnier et al., 2011), or mitochondrial excitons (Nicholls & Ferguson, 2013).

2.3. Coherent Vacua and Unitary Inequivalence

The Bogoliubov-transformed operators define a family of coherent vacuum states:

|0(θ)⟩ = Πₖ [1 / cosh(θₖ)] · exp( tanh(θₖ) · âₖ† ãₖ† ) |0⟩.

Different condensation patterns θ ≠ θ′ yield unitarily inequivalent vacua, satisfying

⟨0(θ) | 0(θ′)⟩ = 0 (in the infinite-mode limit),

which means the organism is not described by a single ground state but by a manifold of possible macroscopic coherence states (Vitiello, 1995; Blasone et al., 2011).

State transitions correspond to vacuum transitions, a mechanism proposed for memory switching, attention shifts, and large-scale physiological reconfiguration.

2.4. Spontaneous Symmetry Breaking and Dipole-Wave Quanta

Coherent biological substrates possess internal continuous symmetries—rotational dipole symmetry of water, orientational symmetry of microtubule dipoles, phase symmetry of protein vibrations, helical symmetry of chromatin dipoles, or U(1)-like ionic phase symmetries (Fröhlich, 1968; Del Giudice et al., 1985; Bizzarri et al., 2013).

Instability of such symmetries leads to spontaneous symmetry breaking (SSB), causing the system to settle in one of many possible coherence vacua. SSB generates Nambu–Goldstone (NG) excitations, which in dipolar biological materials appear as dipole-wave quanta (DWQ)—massless or near-massless collective oscillation modes with long correlation lengths (Del Giudice et al., 1988; Jibu & Yasue, 1995).

DWQ provide the physical mechanism for:

• intracellular water coherence,
• cytoskeletal synchronization,
• microtubular dipole alignment,
• tissue-scale ionic wave propagation,
• organism-wide EM coherence (Vitiello, 2014; Scholkmann, Fels & Cifra, 2013).

A minimal field-theoretic derivation of SSB and DWQ is provided in Appendix C.

2.5. Projection from the Doubled Liouville Equation

The microscopic state ρ(t) evolves according to the doubled Liouville–von Neumann equation:

dρ/dt = −i [ H_total , ρ ].

To extract macroscopic dynamics, we define order-parameter observables Oₖ whose expectation values are

θₖ(t) = Tr [ ρ(t) · Oₖ ].

Applying the Mori–Zwanzig projection operator formalism (Breuer & Petruccione, 2002), projecting ρ(t) onto the manifold of coherent vacua |0(θ(t))⟩, and assuming time-scale separation between slow order-parameter evolution and fast microscopic fluctuations, yields effective macroscopic evolution equations of the form:

dθₖ/dt = Aₖ(θ) + noise.

In the DQFT framework, the drift term Aₖ(θ) is shown to correspond to the gradient of the free-energy functional. A detailed derivation is provided in Appendix A.

2.6. Free-Energy Functional and Vacuum Selection

The free energy associated with the vacuum |0(Θ)⟩, where Θ = {θ₁, …, θ₁₂}, is defined as

$ℱ$(Θ) = ⟨0(Θ)| H_total − (1/β) S |0(Θ)⟩.

The physically realized coherence configuration satisfies

∂$ℱ$ / ∂θₖ = 0

for all k (Takahashi & Umezawa, 1975; Vitiello, 1995).

Thus, the organism continuously relaxes toward the free-energy minimizing configuration Θ_ref, while interactions between fields distort this trajectory and allow multi-stability, bifurcations, and transitions between physiological states.

3. Results: Multi-Field Coherence Architecture and Dynamical Model

The dissipative quantum field framework developed in Section 2 allows biological coherence to be represented through a set of macroscopic order parameters θₖ(t), each associated with a coherent vacuum sector of a specific quantum substrate. In this section, we introduce a structured twelve-field architecture, derive the macroscopic dynamical equations governing these fields, and present the Biological Coherence Index (BCI) as an experimentally accessible measure.

3.1. Coherence Sectors Derived from Biological Quantum Substrates

The organism contains multiple quantum substrates capable of spontaneous symmetry breaking (SSB), including coherent water domains (Del Giudice et al., 1985; Pollack, 2013), microtubular dipole fields (Jibu & Yasue, 1995; Hameroff & Penrose, 2014), cytoskeletal vibrational modes (Fröhlich, 1968), excitonic mitochondrial dynamics (Nicholls & Ferguson, 2013), chromatin dipole oscillations (Montagnier et al., 2011; Bizzarri et al., 2013), and large-scale electromagnetic field patterns (Singer, 1999; McFadden, 2002; Vitiello, 2014).

Each substrate undergoes SSB, generating a distinct vacuum manifold and an associated set of Nambu–Goldstone modes (dipole-wave quanta, DWQ). These long-range modes support extended coherence and mediate cross-scale coupling.

On this basis, the organism can be represented by twelve coherence sectors Θ₁–Θ₁₂:

• Θ₁: foundational intracellular water and cytoskeletal coherence
• Θ₂: immune and inflammatory coherence
• Θ₃: homeostatic ionic and autonomic balance
• Θ₄: interoceptive and vagal–enteric coherence
• Θ₅: circulatory and motility coherence
• Θ₆: mitochondrial metabolic coherence
• Θ₇: regenerative and stem-cell-related coherence
• Θ₈: chromatin and morphogenetic pattern coherence
• Θ₉: circadian and restorative coherence
• Θ₁₀: cognitive–cortical coherence
• Θ₁₁: limbic and affective coherence
• Θ₁₂: global electromagnetic unity

Each Θ-field corresponds to a condensation amplitude θₖ(t) derived from the underlying vacuum structure. The condensate densities Nₖ = sinh²(θₖ) quantify the degree of quantum coherence in each sector.

The explicit physical–biological grounding of each field follows directly from its underlying substrate, allowing the model to integrate cellular, physiological, cognitive, and organism-wide electromagnetic dynamics in a single theoretical framework.

3.2. Quantum Substrates, Microscopic Variables, and Spontaneously Broken Symmetries of the Twelve Life Fields (Θ₁–Θ₁₂)

To anchor the Quantum Blueprint Formalism firmly within the dissipative quantum field theory (DQFT) framework, each Life Field Θₖ is understood as an effective symmetry-breaking sector characterized by:

• Quantum substrates (microscopic carriers)
• Field variables (operators)
• Spontaneously broken symmetries (SSB)
• An order parameter θₖ and its Goldstone-like modes

In this view, the organism is described by a twelve-dimensional manifold of ordered vacua, with dynamics governed by the evolution of the order parameters θ₁–θ₁₂. These SSB sectors are not intended as fundamental fields in the Lagrangian sense, but as coarse-grained, phenomenological condensate sectors in the DQFT spirit of Del Giudice and Vitiello.

Θ₁ – Foundation
Cellular Ground-State Coherence

Quantum substrates

• Intracellular water DWQ
• Membrane potential dipoles
• ETC electron-/proton excitons
• Cytosolic phonon-like modes
• Basal microtubule dipole coherence

Field variablesP(r), V_mem(r), ψ_ETC(r), u(r), M_MT(r)

Broken symmetries

• U(1) phase symmetry of the water–EM dipole field
• Rotational symmetry in dipole orientation

Order parameter & Goldstone modesθ₁; long-wavelength polarization waves in DWQ domains

Θ₂ – Protection
Immune–Inflammatory Coherence

Quantum substrates

• Quantum two-state receptor conformations
• Lymphatic DWQ
• Actin soliton waves in immune cells

Field variablesσᵢ, P_lymph(r), φ_actin(r)

Broken symmetries

• Z₂ symmetry of receptor-state configurations
• U(1) phase symmetry of lymphatic DWQ

Order parameter & Goldstone modesθ₂; low-frequency conformational and actin-phase modes supporting immune coherence

Θ₃ – Balance
Electrolytic, pH, and Autonomic–Vascular Homeostasis

This field emphasizes electrolytic equilibrium as central for autonomic stability.

Quantum substrates

• Coherent Ca²⁺, K⁺, Na⁺, H⁺ (pH) oscillatory fields
• Smooth muscle Davydov-type solitons
• Plasma-water polarization DWQ
• Endothelial electrochemical oscillators

Field variablesφ_ion(r) for Ca²⁺/K⁺/Na⁺/H⁺; P_plasma(r); φ_smooth(r)

Broken symmetries

• U(1) phase symmetry of ionic oscillators
• Approximate translational symmetry in vascular networks
• Effective U(1)-type symmetry associated with electrochemical potentials (broken by steady-state ionic gradients)

Order parameter & Goldstone modesθ₃; propagating electrochemical phase waves governing baroreflex stability and vascular tone

Θ₄ – Centeredness
Vagal Interoception, Gut–Brain Axis, Enteric DWQ, and Microbiome-Modulated Coherence

This field integrates vagal afferents, enteric DWQ, gut–brain-axis coupling, and microbiome-modulated dynamics.

Quantum substrates

• Vagal microtubule dipole fields
• Enteric water DWQ and mucosal dipole layers
• Piezoelectric baroreceptor and mechanoreceptor fields
• Microbiome-derived metabolic and redox oscillations that modulate DWQ and EM substrates (e.g., butyrate, lactate, indole-related metabolites)
• Gut epithelial microtubule and membrane potentials

Field variablesM_vagus(r), P_enteric(r), Q_barorec(r), M_microbio(r), φ_GBA(r)

Broken symmetries

• U(1) vagal–enteric phase symmetry
• Rotational dipole symmetry of microtubules and enteric DWQ
• Approximate metabolic symmetry of the gut–microbiome ensemble (broken by coherent preference patterns)

Order parameter & Goldstone modesθ₄; coherent vagal–gut-phase modulation waves, microbiome–GBA phase entrainment, and interoceptive prediction-like waves

Θ₅ – Flow
Circulatory and Locomotor Coherence

Quantum substrates

• Actomyosin excitons
• Cardiac microtubule dipoles
• Blood-plasma DWQ

Field variablesψ_acto(r), M_heart(r), P_blood(r)

Broken symmetries

• Approximate translational symmetry along muscular fibers
• U(1) phase symmetry of contraction oscillators

Order parameter & Goldstone modesθ₅; cardiac and myofascial contractile-phase shifts and their associated propagating coherence modes

Θ₆ – Vitality
Mitochondrial Electron–Proton Coherence

Quantum substrates

• ETC electron excitons
• Proton oscillatory modes across the inner mitochondrial membrane
• Mitochondrial DWQ domains

Field variablesψ_ETC(r), φ_H⁺(r), P_mito(r)

Broken symmetries

• U(1) phase symmetry of the ETC electron–proton system
• Effective gauge-like symmetry associated with the electrochemical potential

Order parameter & Goldstone modesθ₆; ETC phase fluctuations and coherent bioenergetic waves

Θ₇ – Renewal
Regeneration and Turnover

Quantum substrates

• DWQ condensates in stem-cell niches
• DNA vibrational modes
• ECM piezoelectric modes

Field variablesP_SC(r), φ_DNA(r), Q_ECM(r)

Broken symmetries

• Chromatin conformational symmetry
• ECM mechanical symmetry (translational and rotational invariances)

Order parameter & Goldstone modesθ₇; soft chromatin–ECM remodeling modes underlying regenerative coherence

Θ₈ – Blueprint
Epigenetic Architecture and Fascia

Quantum substrates

• Chromatin excitons
• DNA base-pair dipoles
• Hydration-shell DWQ
• Collagen piezoelectric fields
• Fascial liquid-crystal ordering
• Coherent fascial water

Field variablesψ_chrom(r), d_bp(r), P_hydr(r), Q_coll(r), n_fascia(r), P_fascia(r)

Broken symmetries

• U(1) chromatin dipole symmetry
• O(3) rotational symmetry of fascia broken to O(2) (selection of a director in collagen/fascial alignment)
• ECM translational symmetry

Order parameter & Goldstone modesθ₈; fascia director waves and chromatin soft modes representing morphogenetic “blueprint” coherence

Θ₉ – Restoration
Sleep and Circadian Coherence

Quantum substrates

• Pineal microtubules
• Molecular circadian oscillators
• Thalamo–cortical DWQ

Field variablesM_pineal(r), φ_circ(i), P_TC(r)

Broken symmetries

• U(1) circadian phase symmetry
• Time-translation symmetry (broken by persistent circadian rhythmicity)

Order parameter & Goldstone modesθ₉; circadian phase drift and sleep-cycle transitions as low-energy phase modes in the restoration sector

Θ₁₀ – Clarity
Cognitive Integration

Quantum substrates

• Cortical microtubule dipoles
• Astrocytic Ca²⁺ waves
• Cortical EM field modes

Field variablesM_cortex(r), φ_astro(r), A_cortex(r)

Broken symmetries

• U(1) cortical EM phase symmetry
• Approximate permutation/rotational symmetry among cortical assemblies (broken by phase-locked functional networks)

Order parameter & Goldstone modesθ₁₀; cortical microstate transitions and coherence shifts underlying cognitive integration

Θ₁₁ – Emotion
Limbic–Affective Coherence

Quantum substrates

• Limbic microtubule dipoles
• Limbic DWQ
• Emotion-associated EM oscillations

Field variablesM_limb(r), P_limb(r), A_limb(r)

Broken symmetries

• U(1) limbic-phase symmetry
• Possible non-compact group symmetries consistent with SU(1,1)-type coherent-state structures in affective networks (conjectural)

Order parameter & Goldstone modesθ₁₁; slow attractor transitions in emotional phase space (limbic coherence modes)

Θ₁₂ – Unity
Global Systemic Coherence

Quantum substrates

• Whole-brain EM field
• Heart–brain SU(1,1)-type coupling
• Whole-body DWQ condensate

Field variablesA_global(r), u(r), P_body(r)

Broken symmetries

• SU(1,1) coherence symmetry (coherent-state algebra)
• Global U(1) phase symmetry of large-scale EM modes

Order parameter & Goldstone modesθ₁₂; global phase-drift modes across physiological networks representing whole-system coherence (“Unity” sector)

3.3. Macroscopic Evolution Equation for the Coherence Fields

The temporal evolution of each condensation amplitude θₖ(t) is obtained by projecting the doubled Liouville equation onto the manifold of coherent vacua |0(Θ(t))⟩ (Breuer & Petruccione, 2002; Celeghini et al., 1992). Under time-scale separation, this yields an effective dynamical law:

dθₖ/dt = − γₖ ( θₖ − θₖ_ref ) + Σⱼ Λₖⱼ · Gₖⱼ(θₖ, θⱼ) + Iₖ(t) + ξₖ(t).

Here:

• γₖ > 0 is the intrinsic relaxation rate toward the free-energy minimum,
• θₖ_ref is the attractor value determined by ∂$ℱ$/∂θₖ = 0 (Takahashi & Umezawa, 1975; Vitiello, 1995),
• Λₖⱼ represents cross-field coupling coefficients (e.g., metabolism → immunity → autonomic regulation),
• Gₖⱼ(θₖ, θⱼ) encodes nonlinear interdependence,
• Iₖ(t) represents external driving (pressure, sensory input, EM fields),
• ξₖ(t) captures stochastic fluctuations of unresolved microscopic modes.

This equation describes the organism’s movement through its twelve-dimensional vacuum manifold, where functional states correspond to regions around distinct free-energy minima.

A detailed derivation is given in Appendix A.

3.4. Free-Energy Landscape and the Organismic Attractor Θ_ref

The full organismic coherence state is determined by the free-energy functional

$ℱ$(Θ) = Σₖ Fₖ(θₖ) + Σₖ<ⱼ Cₖⱼ(θₖ, θⱼ),

where Fₖ(θₖ) reflects the cost of maintaining coherence in field Θₖ, and Cₖⱼ describes cross-field energetic coupling (e.g., immune–metabolic interactions; see Franceschi & Campisi, 2014).

The attractor state is defined by the stationarity conditions:

∂$ℱ$ / ∂θₖ = 0, for all k.

The solution

Θ_ref = { θ₁_ref , … , θ₁₂_ref }

defines the global coherence configuration toward which Θ(t) relaxes.

This attractor corresponds phenomenologically to stable physiological states including:

• metabolic equilibrium (Nicholls & Ferguson, 2013),
• circadian synchrony (Roenneberg et al., 2007),
• heart–brain coherence (McCraty et al., 2009),
• stable cognitive phase locking (Singer, 1999),
• emotional integration (Pockett, 2012).

Small perturbations cause excursions in θₖ(t), but the system returns to Θ_ref unless pushed across a bifurcation threshold. Appendix A provides the mathematical foundation for this gradient-flow structure.

3.5. The Biological Coherence Index (BCI)

The Biological Coherence Index maps the theoretical order parameters Θ(t) to experimentally accessible observables. To quantify the proximity of the instantaneous vacuum |0(Θ(t))⟩ to the attractor |0(Θ_ref)⟩, we use the vacuum overlap

C(Θ(t), Θ_ref) = ⟨0(Θ_ref) | 0(Θ(t))⟩.

For small deviations Δθₖ = θₖ(t) − θₖ_ref, the overlap is

C ≈ exp( − ½ Σₖ (Δθₖ)² ).

To allow domain-specific weighting, we define:

BCI(t) = exp( − ½ Σₖ wₖ ( θₖ(t) − θₖ_ref )² ),

where wₖ adjusts the contribution of each field (e.g., Θ₆ for metabolism; Θ₁₀ for cognition). This index yields a scalar value 0–1 representing whole-organism coherence.

Appendix B provides the derivation of this expression from the vacuum overlap formula.

3.6. Model Predictions

The multi-field dissipative framework yields several experimentally testable predictions:

• Cross-scale entrainment:Coherence in Θ₆ (metabolism) modulates Θ₂ (immunity), consistent with metabolic–immune coupling (Franceschi & Campisi, 2014).
• Frequency-selective susceptibility:Linearization of the dynamical equation yields susceptibilitiesχₖ(ω) = 1 / (γₖ + iω),predicting field-specific response windows (Singer, 1999; Pilla, 2013).
• Coherence collapse:Perturbations that distort Θ(t) away from Θ_ref reduce BCI(t), potentially corresponding to stress-induced dysregulation.
• Restorative reintegration:Recovery toward Θ_ref during sleep (Θ₉) should coincide with increases in BCI and in physiological synchrony (Roenneberg et al., 2007).
• Fractal signatures:High-coherence states exhibit increased fractal scaling in physiological data (Goldberger et al., 2002), consistent with multi-level vacuum alignment.

4. Discussion and Conclusion

The multi-field dissipative quantum framework developed in this work provides a unified approach to understanding long-range coherence and integrative dynamics across biological scales. The central result is that biological organization can be represented as a twelve-dimensional manifold of coherent vacua, each vacuum sector arising from the spontaneous symmetry breaking (SSB) of a specific quantum substrate. This structure combines insights from dissipative quantum field theory (DQFT) (Celeghini, Rasetti & Vitiello, 1992; Umezawa, 1993; Blasone, Jizba & Vitiello, 2011), water-coherence theory (Del Giudice et al., 1985; Pollack, 2013), microtubule dipole models (Jibu & Yasue, 1995; Hameroff & Penrose, 2014), excitonic bioenergetics (Nicholls & Ferguson, 2013; Wallace, 2010), chromatin vibrational dynamics (Montagnier et al., 2011; Bizzarri et al., 2013), and organism-wide electromagnetic synchronization (Singer, 1999; Freeman, 2000; Vitiello, 2014).

4.1. Dissipative Structure and Biological Integration

Biological systems are inherently dissipative, exchanging energy and entropy with the environment at multiple timescales (Prigogine, 1980; Breuer & Petruccione, 2002). In the DQFT formalism, dissipation is represented intrinsically through the doubling of operators (âₖ, ãₖ), ensuring that coherence does not contradict thermodynamic irreversibility. This structural feature is crucial for explaining why living systems are able to maintain non-equilibrium coherent states rather than relaxing to equilibrium.

The multi-field architecture illustrates that coherence in biological organisms is not governed by a single dominant process, but by interacting layers of quantum substrates, each associated with a different physiological domain. For example, metabolic coherence (Θ₆) and immune coherence (Θ₂) interact strongly (Franceschi & Campisi, 2014), as do cognitive (Θ₁₀) and emotional (Θ₁₁) coherence fields (McCraty et al., 2009; Pockett, 2012). The model provides a mathematically explicit and biologically interpretable explanation for such cross-scale entrainment.

4.2. Vacuum Manifold and Functional States

Because distinct condensation patterns θₖ define unitarily inequivalent vacua, each physiological state corresponds to a specific region of the vacuum manifold. Changes in environmental or internal conditions—light, metabolic load, stress, sensory input, sleep pressure—move the system through the manifold toward or away from the free-energy minimum Θ_ref. This formalism explains:

• how coherent states (e.g., restorative sleep, metabolic equilibrium) arise from low free-energy configurations,
• how dysregulation and decoherence correspond to perturbations away from Θ_ref,
• why certain physiological transitions are abrupt, reflecting transitions between neighboring vacuum sectors, similar to phase transitions.

These features resonate with known properties of biological rhythms and coherence dynamics (Roenneberg et al., 2007; Goldberger et al., 2002).

4.3. Long-Range Coupling via Dipole-Wave Quanta

The presence of Nambu–Goldstone–like dipole-wave quanta (DWQ) is essential: these massless collective oscillations enable nonlocal coupling within and between coherence fields. DWQ propagation through structured water, cytoskeletal networks, and tissue-level EM fields provides a physical mechanism for long-range synchronization seen in:

• intracellular water domains (Del Giudice et al., 1985),
• microtubular systems (Jibu & Yasue, 1995; Tuszynski et al., 1995),
• large-scale electromagnetic brain fields (Singer, 1999; Freeman, 2000),
• cross-organ interactions such as heart–brain coherence (McCraty et al., 2009).

This mechanism complements and extends classical signaling pathways without contradicting them.

4.4. Biological Coherence Index and experimental accessibility

The Biological Coherence Index (BCI), derived from vacuum overlap expressions (Appendix B), provides a theoretical bridge to measurable physiology. The BCI predicts that alignment across coherence fields coincides with distinctive empirical signatures such as:

• increased HRV coherence (Shaffer & Ginsberg, 2017),
• gamma-band synchronization (Singer, 1999),
• restored circadian phase-locking (Roenneberg et al., 2007),
• fractal scaling in physiological signals (Goldberger et al., 2002).

Because BCI(t) reduces to a multidimensional Gaussian metric around Θ_ref, it can be estimated from multimodal biosignals using existing techniques in nonlinear dynamics and EM field analysis.

4.5. Implications and Future Directions

This modeling framework establishes a principled theoretical basis for integrative physiology. The multi-field DQFT architecture:

• unifies coherence phenomena across biological scales,
• clarifies the role of dissipation in maintaining order,
• explains multi-stability and state transitions via vacuum dynamics,
• predicts measurable coherence patterns across domains,
• suggests new empirical investigations—e.g., coherence perturbations, resonance effects, and cross-modal entrainment.

Future work may involve:

• computational simulations of the dynamical equations for θₖ(t),
• experimental tests of cross-field susceptibility spectra (χₖ(ω)),
• multimodal BCI estimation in physiological or cognitive tasks,
• mapping pathological states as distortions of the vacuum manifold,
• exploring intervention strategies to shift Θ(t) toward Θ_ref.

4.6. Conclusion

We presented a dissipative quantum field model of whole-organism coherence in which twelve substrate-derived coherence fields interact through a shared free-energy landscape. Each field emerges from spontaneous symmetry breaking in a specific biological quantum substrate and evolves according to macroscopic dynamical equations derived from DQFT. The vacuum manifold formed by these fields provides a unifying mathematical structure for multi-scale integration in biological systems. The model is compatible with known biophysical phenomena and yields testable predictions for future studies in systems biology and integrative physiology.