The PFUSRC framework establishes the 11-dimensional triple coaxial 45° biconical geometry as the universal minimal topological closure unit homologous across all scales, ranging from macroscopic cosmic structures and mesoscopic pendulum oscillation systems to proton/neutron-scale microscopic domains. Prior studies have mathematically validated the primordial steady-state property of this biconical geometry, verified its mesoscopic oscillation trajectories via pendulum experiments, and matched its two-dimensional petal projection patterns against σ-hole imaging, muon g-2 measurements and EIT topological latching observations. Nevertheless, mainstream quantum interpretive frameworks merely attribute petal orbital morphologies to wavefunction probability distributions, lacking standardized topological recognition training tools to decode intrinsic geometric structures embedded in experimental datasets. This paper distinguishes physical detection hardware and topological cognitive interpretation as two independent research dimensions, and proposes a standardized paper-path drawing training method grounded in algebraic topological homotopy invariants. The pen-and-paper simulation fully reproduces the complete projection dynamics of four-dimensional flow variables, including waist-ring convergence, layered outflow and global topological latching on planar observational cross-sections. Hand-drawn trajectories share strict path homomorphism with microscopic orbital petals, unified under the invariant rule of “single entry, central crossing, dual exit, closed latching” constrained by 55 global curvature anchors. The proposed three-tier training protocol covers single-layer steady-state structures, multi-layer nested superpositions and transient incomplete projections, corresponding to ground-state orbitals, hybrid orbitals and high-energy excited states with critical residual ΔA ≈ 0.0364. This methodology serves as a complementary cognitive tool rather than a replacement for precision detection facilities or quantitative quantum derivations. It bridges macroscopic topological axioms, mesoscopic pendulum evidence and microscopic quantum patterns, completing the PFUSRC five-level closed loop spanning ontology, empirical phenomena, experimental measurement and human topological cognition, and delivering a zero-threshold, falsifiable standardized workflow for microscopic topological identification.
Zhenmin Wang (Thu,) studied this question.
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