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Skyrmion propulsion boundary

The full topology and orbit analysis now lives on Skyrmions. This propulsion page inherits its boundary: integer winding, moving solitons, collective coordinates, low effective mass, and modeled metric responses do not establish reactionless thrust, total-inertia cancellation, spacetime engineering, or transmedium propulsion.

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Computational consolidation notice

The site-wide source of truth for all Python and numerical validation is now Python and Numerical Validation. This propulsion page remains the domain-specific simulation branch. Its local code examples and runnable harness are interpreted through the canonical audit: exact software behavior where stated, but no measured thrust, force, inertial modification, spacetime curvature, reactionless momentum transfer, HFGW detection, or novel GEM field.

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Computational inclusion rule

This page contains only propulsion-adjacent formalisms represented by executable Python, NumPy/SciPy simulation, QuTiP quantum simulation, or explicit VQE circuit specifications found in Google Drive. Prose-only propulsion claims, hardware-only descriptions, and symbolic documents without a simulation layer are excluded.

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Status key: [PY] Python/NumPy/SciPy code · [QSIM] quantum simulation · [SPEC] circuit or solver specification · [PROTO] code-bearing prototype requiring correction · [MODEL] internal computational model, not experimental propulsion validation

Computational architecture

$V_2^{\otimes3}\xrightarrow{C}\xrightarrow{K=(C-6I)(C-30I)}E_{47}\xrightarrow{P_{47}}\text{simulated dynamics}$

The Drive corpus divides into five executable or simulation-specified layers:

Layer Runtime Role Status
E47 spectral substrate NumPy / QuTiP Constructs the 125-dimensional carrier, Casimir selector, and 47-dimensional kernel [PY] [QSIM]
GEM / gravito-inertial model QuTiP Couples a two-qubit superconducting sector to a truncated bosonic GEM mode [QSIM] [PROTO] [MODEL]
Scalar / spectral model NumPy / Matplotlib Evaluates kernel rank, scalar recursion, mass scaling, and attractor surfaces [PY] [MODEL]
Geodesic / metric model SciPy / NumPy Integrates an augmented geodesic flow with singularity detection [PY] [MODEL]
E47 VQE model Native-circuit specification Defines a parameterized ansatz and hybrid optimization loop [SPEC] [PROTO]

1. E47 spectral simulation substrate

Drive source: KKP Spectral Validation and QuTiP Emulation Report

The computationally stable core constructs the spin-2 generators, their tensor cube, the total Casimir, and the selector:

import numpy as np
import qutip as qt

j_x = qt.jmat(2, "x")
j_y = qt.jmat(2, "y")
j_z = qt.jmat(2, "z")
I5 = qt.qeye(5)

Jx = qt.tensor(j_x, I5, I5) + qt.tensor(I5, j_x, I5) + qt.tensor(I5, I5, j_x)
Jy = qt.tensor(j_y, I5, I5) + qt.tensor(I5, j_y, I5) + qt.tensor(I5, I5, j_y)
Jz = qt.tensor(j_z, I5, I5) + qt.tensor(I5, j_z, I5) + qt.tensor(I5, I5, j_z)

C = Jx**2 + Jy**2 + Jz**2
I125 = qt.tensor(I5, I5, I5)
K = (C - 6 * I125) * (C - 30 * I125)

evals = K.eigenenergies()
dim_E47 = int(np.count_nonzero(np.abs(evals) < 1e-10))
omega_c = dim_E47 / 125
assert dim_E47 == 47
assert np.isclose(omega_c, 47 / 125)

Normalized result:

$\dim\ker K=47,\qquad \Omega_c=47/125=0.376.$

Code audit: the Drive version uses qeye(125), whose QuTiP tensor metadata can differ from the $5\otimes5\otimes5$ operator metadata. The normalized form above uses tensor(I5,I5,I5) so the dimensions match exactly.

2. GEM / gravito-inertial QuTiP model

Drive source: Gravito-Magnetic Fields

The source defines a simulated Hamiltonian family

$H=H_{\mathrm{SC}}+H_{\mathrm{GEM}}+H_{\mathrm{RI}}$

with