Causal Memory Gravity X: Emergent Fermion Sector, Asymptotic Unitarity, Relational GKSL Dynamics, and CLASS Interface

Abstract

Causal Memory Gravity X and its two addenda examine how an effective environment can suppress selected quantum coherences without changing the total particle number. The construction connects a conditional fermion sector, relational GKSL dynamics, Bell correlations, laboratory coherence, and a future cosmological solver interface. After canonical fermionic operators and a graph Hamiltonian are supplied, the relational number-difference channel preserves charge, decreases purity, gives a stability criterion for the lightest state in each fixed-charge sector, and satisfies ‖ρ(t) − U(t)ρ₀U†(t)‖₁ ≤ CD βGKSL t exp(CD βGKSL t) The physical expansion parameter is βGKSLt; it reduces to βGKSL/Ω only for a fixed number of oscillation cycles. A short-memory dilation keeps the bath correlation time separate from βGKSL, while βGKSL = CGKSLβrate remains a microscopic matching relation. The continuum density-gradient channel produces momentum diffusion and an FRW kinetic hierarchy with explicit CLASS insertion points and conservation tests. Numerical spectra and likelihood constraints require an implemented solver. The Bell/EPR supplement gives an exact two-qubit benchmark after the qubit map and generator are specified: v(t) = exp(−4βrelt), |S|max = 2√[1 + exp(−8βrelt)] It also supplies the CPTP representation, coincidence likelihood, and Fisher matrix. Frame alignment rotates the analyzer directions without changing the optimized CHSH value; a physical frame carrier and the βrel-to-βrate bridge remain microscopic inputs. The SMV laboratory addendum finds, under the fiducial matching βrel = βrate = H0, a visibility loss of 8.8 × 10⁻¹⁹ over 0.1 s and force corrections of 6.7 × 10⁻⁶²|ηcl| and 1.1 × 10⁻⁶⁶|ηcl|. These effects lie far below the proposed experimental scale of approximately 10⁻³. The decisive next step is a DPN-derived positive bath spectrum, calibrated relational rates, a physical edge carrier, and an implemented CLASS and laboratory-likelihood pipeline. For the full CMG corpus, theory map, and related materials, visit: https://cmg.beogradpc.com/