Unified Formalization of the Theory of Micro-Phase Differences

 

Unified Formalization of the Theory of Micro-Phase Differences

A Complete Mathematical Framework

Below, I present a unified framework that completes the proposed structure into an axiomatic system with action principles and empirically testable predictions.


I. Axiomatic Foundations

Axiom 1 (Universality of Phase Fields)
All physical, cognitive, and informational states can be represented as a complex amplitude field

Ψ:M×RC\Psi: M \times \mathbb{R} \rightarrow \mathbb{C}

whose phase component ϕ\phi encodes difference, structure, and meaning.

Axiom 2 (Local U(1) Gauge Symmetry)
The phase field obeys laws invariant under the local gauge transformation

ϕ(x)ϕ(x)+λ(x),λ:MR/2πZ.\phi(x) \rightarrow \phi(x) + \lambda(x), \quad \lambda: M \rightarrow \mathbb{R}/2\pi\mathbb{Z}.

Observable quantities depend only on phase differences, connections, and curvature.

Axiom 3 (Principle of Least Action)
The time evolution of the system is determined by the stationary condition of the action functional

δS=0,\delta S = 0,

where S[Ψ]S[\Psi] integrates amplitude dynamics, phase gradients, topological invariants, and information-geometric terms.


II. Full Lagrangian Density

We propose a five-layer Lagrangian:

Ltotal=Lkinetic+Lgradient+Lpotential+Linfo-geom+Ltopological.\mathcal{L}_{\text{total}} = \mathcal{L}_{\text{kinetic}} + \mathcal{L}_{\text{gradient}} + \mathcal{L}_{\text{potential}} + \mathcal{L}_{\text{info-geom}} + \mathcal{L}_{\text{topological}}.

Layer 1: Kinetic Term (Temporal Dynamics)

Lkinetic=12[(tA)2+A2(tϕeA0)2]\mathcal{L}_{\text{kinetic}} = \frac{1}{2} \left[(\partial_t A)^2 + A^2(\partial_t \phi - eA_0)^2\right]
  • A0A_0: temporal connection (external potential)

  • ee: coupling constant (e.g., electric charge; in cognition: attention weight)


Layer 2: Gradient Energy (Spatial Structure)

Lgradient=c12(A2+A2ϕeA2)\mathcal{L}_{\text{gradient}} = -\frac{c_1}{2} \left(|\nabla A|^2 + A^2|\nabla \phi - eA|^2\right)
  • AA: spatial gauge connection

  • c1c_1: phase stiffness (controls correlation length)


Layer 3: Self-Interaction Potential

Lpotential=λ4(A2η2)2g(x)A2\mathcal{L}_{\text{potential}} = -\frac{\lambda}{4}(A^2 - \eta^2)^2 - g(x)A^2
  • Mexican-hat potential: η0\eta \neq 0 induces spontaneous symmetry breaking

  • g(x)g(x): external driving field (contextual or observational bias)


Layer 4: Information-Geometric Term

Linfo-geom=α[KL(ΨΨprior)+κF[Ψ]]\mathcal{L}_{\text{info-geom}} = -\alpha \left[ KL(\Psi \| \Psi_{\text{prior}}) + \kappa F[\Psi] \right]
  • KLKL: Kullback–Leibler divergence (cost of deviation from prior)

  • F[Ψ]=A2logA2F[\Psi] = -\int A^2 \log A^2: Fisher-information penalty

  • α,κ\alpha, \kappa: strengths of information constraints


Layer 5: Topological Term

Ltopological=βiniδ(xxi)+γFF\mathcal{L}_{\text{topological}} = \beta \sum_i n_i \delta(x - x_i) + \gamma \int F \wedge F
  • First term: phase singularities (vortices), niZn_i \in \mathbb{Z}

  • Second term: Chern–Simons / θ\theta-term in 4D


III. Field Equations

From δS=0\delta S = 0:

Amplitude Field

t2Ac12A+A(tϕeA0)2+c1AϕeA2+VeffA=0\partial^2_t A - c_1 \nabla^2 A + A(\partial_t \phi - eA_0)^2 + c_1 A |\nabla \phi - eA|^2 + \frac{\partial V_{\text{eff}}}{\partial A} = 0 Veff=λ4(A2η2)2+g(x)A2+αIinfoV_{\text{eff}} = \frac{\lambda}{4}(A^2 - \eta^2)^2 + g(x)A^2 + \alpha I_{\text{info}}

Phase Field (Continuity-like Equation)

t[A2(tϕeA0)]c1[A2(ϕeA)]+(topological source)=0\partial_t[A^2(\partial_t \phi - eA_0)] - c_1 \nabla \cdot [A^2(\nabla \phi - eA)] + (\text{topological source}) = 0

Topological sources correspond to vortex creation/annihilation.


IV. Applications Across Domains

DomainInterpretationTestable Predictions
Quantum systemsA=ρA = \rho, ϕ\phi = quantum phaseRecovers Gross–Pitaevskii; quantized vortices
Classical fields / fluidsϕ\nabla \phi = velocity potentialQuantized circulation, Kelvin-wave dispersion
Cognition / semanticsϕ\phi encodes meaningPhase gradient correlates with embedding geometry
Collective societal phenomenaϕ\phi = synchronization phaseKuramoto model as continuum limit

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