The Quantum Blueprint Formalism: An Informational Extension of Dissipative Quantum Field Theory in Living Systems

1. Introduction

Biological systems maintain long-range order far from thermodynamic equilibrium, continuously exchanging energy and information with their environment. Classical thermodynamics cannot account for such persistent coherence (Prigogine & Stengers, 1984). To address this, Celeghini, Rasetti, and Vitiello (1992) formulated a dissipative quantum field theory (DQFT) based on Thermo Field Dynamics (TFD) (Umezawa, 1967), in which the Hilbert space is doubled to include both the system (ψ) and its conjugate (ψ̃), representing the time-reversed dynamical partner required for dissipation.

In this framework, coherence arises from spontaneous symmetry breaking and the condensation of Nambu–Goldstone modes, producing macroscopic quantum domains that underlie perception, memory, and self-organization (Freeman & Vitiello, 2006). While the tilde field ψ̃ in DQFT encodes the environmental and historical degrees of freedom necessary for irreversibility and memory, it does not explicitly implement informational feedback into the system’s evolution.

The Quantum Blueprint Formalism (QBF) extends this idea by assigning ψ̃ an explicit informational role that elaborates—and does not contradict—the active function already present in dissipative quantum field theory (DQFT). In the original DQFT of Celeghini, Rasetti, and Vitiello, the conjugate field ψ̃ is not a passive repository of dissipated modes but an active dynamical partner of ψ. Their SU(1,1)-mediated coupling is governed by the Bogoliubov parameters θₖ, which encode the degree of mixing between the two sectors and thereby regulate memory formation, irreversibility, and long-range coherence. In other words, the feedback between system and tilde-system is already mediated by θₖ in DQFT, where these parameters label distinct inequivalent vacua and determine the strength of ψ–ψ̃ entanglement.

QBF builds on this foundation by interpreting the correlation parameters Θ = {θₖ} not only as markers of vacuum structure but as informational coherence amplitudes that dynamically encode the system’s evolving resonance with its own history of ordered states. In this generalized framework, the ψ–ψ̃ coupling becomes explicitly state-dependent, and ψ̃ functions as an informational attractor that reorganizes the physical system through correlation-sensitive feedback. The dynamics of Θ(t) thus quantify the organism’s capacity to restore order following perturbation, translating the inherent feedback structure of DQFT into a biologically and informationally meaningful form.

2. Mathematical Structure of the Quantum Blueprint Formalism

2.1. The Doubled Hilbert Space

In thermo-field dynamics (TFD), the state of an open quantum system is expressed as

|Ψ⟩ = |ψ⟩ ⊗ |ψ̃⟩

where |ψ̃⟩ represents the time-reversed copy required to describe dissipation.

The evolution is generated not by introducing an additional dissipative operator, but by the non-Hermitian structure of the doubled Hamiltonian:

H_total = H − H̃

where H̃ is obtained from H by tilde conjugation and encodes the environmental (time-reversed) degrees of freedom.

Irreversibility and energy flow arise from the Bogoliubov transformations that mix ψ and ψ̃, while DQFT ensures energy balance via

⟨ψ|H|ψ⟩ = ⟨ψ̃|H̃|ψ̃⟩.

In QBF, dissipation remains entirely contained in the doubled (ψ, ψ̃) structure, but the coupling between the two sectors becomes state-dependent. This is expressed by allowing the mixing parameters (or the transformation generator) to depend on instantaneous correlations between ψ and ψ̃:

H_total = H − H̃ (with state-dependent ψ–ψ̃ coupling).

Instead of adding an operator Γ(ψ, ψ̃), QBF modifies the correlation-dependent mixing between the two sectors, so that informational feedback and coherence restoration arise dynamically from the structure of the doubled Hilbert space.

2.2. Ordered Vacua and Correlation Parameters

In both DQFT and QBF, ordered vacua |0(Θ)⟩ are parameterized by Bogoliubov transformations:

aₖ(θₖ)|0(Θ)⟩ = 0 = ãₖ(θₖ)|0(Θ)⟩

The modal occupation number is

Nₖ = ⟨0(Θ)|aₖ† aₖ|0(Θ)⟩ = sinh²(θₖ).

The overlap between vacua defines the correlation function

C(Θ, Θ′) = ⟨0(Θ′)|0(Θ)⟩ = Πₖ [ 1 / cosh(θₖ − θ′ₖ) ].

In QBF, a reference configuration Θ_ref denotes the attractor state toward which the system tends when its ψ–ψ̃ correlations are maximally coherent. Deviations Δθₖ = θₖ − θₖ,ref quantify departures from this coherence state and therefore measure informational disorder.

2.3. Dynamical Evolution of Correlation Parameters

The time evolution of Θ(t) follows a dissipative–stochastic equation derived from the non-Hermitian Hamiltonian:

dθₖ/dt = −κₖ(θₖ − θₖ,ref) + gₖ h(t) + Σⱼ μₖⱼ F(θₖ, θⱼ) + ηₖ(t)

where:

• κₖ is the intrinsic relaxation rate of mode k;
• gₖ h(t) describes external perturbations (e.g., electromagnetic or thermal fields);
• μₖⱼ F(θₖ, θⱼ) accounts for cross-mode coupling between correlated domains;
• ηₖ(t) represents stochastic noise from environmental or quantum sources.

The first term drives the system toward its informational attractor Θ_ref, while the coupling matrix μₖⱼ introduces hierarchical coherence across scales.

The global coherence measure is given by the Blueprint Coherence Index (BCI):

BCI(t) = exp[ −½ Σₖ wₖ (θₖ − θₖ,ref)² ].

BCI ∈ [0,1] quantifies the instantaneous informational alignment between ψ and ψ̃.

3. Derivation from the Dissipative Lagrangian

Starting from the non-Hermitian Lagrangian density

$ℒ$_eff = $ℒ$(ψ) − $ℒ$(ψ̃) + i·Φ(ψ, ψ̃),

the Euler–Lagrange equations yield

δ$ℒ$_eff/δψ = 0, δ$ℒ$_eff/δψ̃ = 0.

If Φ depends on the phase correlation between ψ and ψ̃,

Φ(ψ, ψ̃) = Σₖ κₖ (θₖ − θₖ,ref)² / 2 − Σⱼ μₖⱼ F(θₖ, θⱼ),

then the variational derivative with respect to θₖ leads directly to

dθₖ/dt = −∂Φ/∂θₖ + ηₖ(t),

which recovers the QBF dynamic equation.

Thus, QBF remains variationally consistent with the dissipative Lagrangian formalism and extends it by including an informational potential Φ(ψ, ψ̃).

4. Constructive Noise and Stochastic Resonance

The stochastic term ηₖ(t) can be expressed as

ηₖ(t) = ξₖ ζ(t)

with ζ(t) representing quantum noise (white or pink) and ξₖ its coupling amplitude. The response of mode k is characterized by its susceptibility

χₖ(ω) = gₖ / [(ωₖ² − ω²) + i γₖ ω].

When the spectral density S_η(ω) overlaps with |χₖ(ω)|², noise enhances coherence — a phenomenon known as stochastic resonance (McDonnell & Ward 2011). This mechanism explains how biological systems can exploit fluctuations to maintain order near criticality.

5. Empirical Correspondence and Testability

The QBF provides quantitative links between theoretical parameters and measurable physiological observables.

Theoretical variable	Empirical observable	Method
Δθₖ = θₖ − θₖ,ref	HRV phase deviation	Fourier and wavelet HRV analysis
BCI(t)	HRV coherence index	0.1 Hz spectral power ratio (Shaffer & Ginsberg 2017)
ψ̃ feedback	Ultraweak photon emission (UPE)	Biophoton photomultiplier counts (Popp 1992; Van Wijk 2014)
χₖ(ω)	EEG phase coherence, dielectric spectroscopy	FFT/PSD methods
ηₖ(t)	Controlled noise input or QRNG modulation	Correlation and entropy measures
Θ_ref drift	Longitudinal HRV + photonic correlations	Week-to-week BCI trajectory

5.1. HRV and Systemic Coherence

Heart rate variability reflects the organism’s capacity for self-regulation. Within QBF, HRV coherence corresponds to convergence of the low-frequency (~0.1 Hz) oscillatory mode toward its Θ_ref. High BCI(t) values correlate with stable 0.1 Hz oscillations (Shaffer & Ginsberg 2017).

5.2. EEG Coherence

EEG phase synchronization represents high-frequency analogues of θₖ dynamics in neural domains. Periods of sustained alpha or gamma synchronization correspond to temporary increases in ψ–ψ̃ alignment.

5.3. Water and Dielectric Spectroscopy

Experimental work by Del Giudice and Pollack (2013) suggests that structured water forms coherent domains at infrared frequencies. Dielectric phase measurements reveal dynamic order consistent with correlated θₖ modes.

5.4. Ultraweak Photon Emission (UPE)

Biophotons, as observed by Popp (1992) and Van Wijk (2014), display coherence signatures that reflect ψ̃ feedback. Temporal correlations in photon count distributions could serve as experimental proxies for Δθₖ dynamics.

6. Discussion

6.1. Informational Feedback and Self-Organization

In the dissipative quantum field theory (DQFT) of Ricciardi and Vitiello, the doubled Hilbert space is introduced not as a mathematical convenience but as a structural necessity for describing open quantum systems. The conjugate, or tilde, field ψ̃ does not represent a passive repository of dissipated modes. Rather, ψ̃ is an active dynamical partner that encodes the time-reversed degrees of freedom required for irreversibility, memory formation, and long-range ordering in the system. Through the SU(1,1) Bogoliubov mixing between ψ and ψ̃, the tilde sector participates directly in the selection of inequivalent vacuum states and thereby shapes the system’s coherent evolution.

Within this framework, ψ̃ carries contextual and historical information about the accessible vacuum configurations and contributes actively to the system’s dynamics. Dissipation in DQFT therefore arises not from an added operator but from the interaction between the two sectors, which jointly determine the temporal arrow and the formation of stable, ordered patterns.

The Quantum Blueprint Formalism (QBF) builds on this foundation by extending the role of the ψ̃ field. While DQFT treats ψ̃ as an indispensable but implicitly defined partner in the dissipative process, QBF interprets the conjugate field as an informationally structured domain whose state reflects the organism’s history of coherence and pattern formation. In this view, ψ̃ interacts with ψ through correlation-dependent couplings encoded by the parameters Θ(t), allowing informational structure to influence the physical evolution of the system.

This generalization preserves the essential features of dissipative quantum dynamics while introducing a mechanism through which informational coherence—rather than energy flow alone—guides the stability, recovery, and adaptation of living matter.

6.2. Connection to Open-System Thermodynamics

The informational feedback implied by QBF is consistent with nonequilibrium thermodynamics and the concept of dissipative structures (Prigogine & Stengers 1984). The informational field ψ̃ effectively functions as a low-entropy reservoir that stores correlation information rather than energy. The system therefore minimizes its informational free energy rather than its energetic free energy, a principle reminiscent of Friston’s “free-energy principle” in neuroscience, but derived here from first principles in quantum field dynamics. The attractor Θ_ref may thus be understood as the instantaneous configuration minimizing the informational free-energy functional

F_info(Θ) = ½ Σₖ κₖ (θₖ − θₖ,ref)² − Σₖⱼ μₖⱼ F(θₖ, θⱼ).

This perspective situates the QBF squarely within the physics of informational thermodynamics, where order and meaning emerge as physical invariants of open quantum systems.

6.3. Relation to Quantum Biology

A number of experimental findings in quantum biology resonate with the assumptions of the QBF. Long-range coherence in hydrated biomolecules (Fröhlich 1968), collective dipole oscillations in water (Del Giudice et al. 1988), and coherent energy transfer in photosynthetic complexes all exemplify stable coherence under dissipative conditions. These phenomena suggest that living matter operates close to critical points where small informational perturbations can reorganize macroscopic order. The feedback mechanism ψ ↔ ψ̃ provides a plausible mathematical foundation for this critical adaptability.

Furthermore, the stochastic-resonance term ηₖ(t) offers a framework for interpreting the beneficial role of biological noise observed in neural, cardiac, and genetic systems (McDonnell & Ward 2011). Instead of disrupting coherence, noise can modulate the effective susceptibility χₖ(ω) of coherence modes, enabling adaptive synchronization. The QBF thus integrates coherence, noise, and self-organization into a single dynamical principle.

6.4. Empirical Perspectives

While fundamentally theoretical, the QBF is testable through observable correlates of informational coherence. Heart-rate-variability coherence (Shaffer & Ginsberg 2017) reflects slow global oscillations (≈ 0.1 Hz) associated with high BCI(t). EEG phase synchronization represents faster local coherence dynamics corresponding to individual θₖ modes. Ultraweak photon emission (Popp 1992; Van Wijk 2014) and dielectric relaxation of water (Pollack 2013) may serve as proxies for ψ̃ feedback processes. Together, these measurements could enable experimental estimation of the parameters κₖ, μₖⱼ, and ηₖ(t) and permit empirical mapping of the system’s informational phase trajectory Θ(t).

Such an integrative approach would transform the study of living coherence from qualitative speculation into quantitative modeling, allowing explicit tests of whether coherence restoration follows the predicted exponential convergence toward Θ_ref and whether noise indeed enhances rather than degrades BCI(t).

6.5. Conceptual Implications

By redefining dissipation as a channel for information flow, the QBF reframes life not as a thermodynamic anomaly but as a lawful outcome of open-system physics. The conjugate field ψ̃ becomes the mathematical representation of context: the total information of the organism’s past interactions that continuously informs its present structure. In this view, coherence, adaptation, and even memory are not separate biological functions but emergent properties of the same informational coupling that underlies all living systems.

7. Conclusion

The Quantum Blueprint Formalism (QBF) extends the dissipative quantum field theory as developed by Celeghini, Rasetti, and Vitiello by introducing an explicit informational feedback mechanism between the physical and conjugate sectors of the doubled Hilbert space. Instead of modifying the Hamiltonian through an additional dissipative operator Γ, dissipation in QBF—consistent with DQFT—is generated entirely through the SU(1,1) Bogoliubov mixing between ψ and ψ̃.

The innovation of QBF does not lie in making the ψ–ψ̃ coupling parameters state-dependent—since in DQFT the Bogoliubov parameters θₖ already evolve with the system’s state—but in interpreting these parameters as informational coherence variables that dynamically encode the organism’s changing ψ–ψ̃ correlations. On this basis, QBF formulates explicit dynamical equations for the correlation parameters Θ = {θₖ}, describing how coherence is lost and actively regenerated over time. The introduction of an informational attractor Θ_ref transforms the theory from a model primarily concerned with memory preservation into a model of self-restoring coherence, in which the system continuously reorganizes itself through informational feedback between the physical and conjugate sectors.

Mathematically, QBF remains consistent with the variational and algebraic structure of dissipative field theory while expanding its descriptive power through the informational potential Φ(ψ, ψ̃) and the Blueprint Coherence Index BCI(t). Physically, it provides a bridge between quantum field dynamics, open-system thermodynamics, and information theory. Biologically, it offers a unifying explanation for coherence phenomena observed across molecular, cellular, and systemic scales.

QBF suggests that living systems operate as informational oscillators coupled to their own conjugate fields, continually regenerating order through the feedback of structured information. This insight reframes the classical dichotomy between matter and information: matter appears as the transient projection of an underlying informational process, and life emerges as the perpetual dialogue between the two.

Future research should aim to (1) derive the full QBF equations from a generalized non-Hermitian Lagrangian within the doubled Hilbert-space formalism, (2) identify empirical signatures of ψ–ψ̃ coupling through HRV, EEG, dielectric, and photonic measurements, and (3) explore whether the informational potential Φ can be related to entropy production or algorithmic information content. If confirmed, the Quantum Blueprint Formalism may provide the missing physical basis for understanding biological coherence, adaptability, and the continuity between physics, information, and consciousness.