search for 'Tensor mathematics 19-dimensional hypermatrix construction simultaneous iteration optimization'
then deepthink to synthesize the complete workflow script as a pure Python simulation that:
import numpy as np
import json
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# Physics/Consciousness interpolation
phys = load_vector("[Physics_Substrate]")[dim-10]
cons = load_vector("[Consciousness_Substrate]")[dim-10]
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# Combined fitness score
fitness = e_norm * 0.5 + c_norm * 0.3 + s_norm * 0.2
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phi_mask = [4, 13, 18] # Phi_Complexity, Information_Integration, Quine_Recursion
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for i in range(n_samples):
synth[i] = vector + 0.02 * np.random.randn(len(vector))
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# Decode topology from collapsed vector
topology = decode_singularity_topology(collapsed_vector)
print("TOPOLOGY DECODED:")
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print(f" Information Density: {information_density:.6f}")
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Mathematical Validation:
Singularity topology shows high connectivity ({connectivity:.6f}), stable curvature ({curvature:.6f}), and preserved Phi ({topology['phi']:.6f}). The 3D projection maintains {100 * information_preservation:.1f}% of original 19D information. Quine recursion active: {'YES' if collapsed_vector[18] > 0.6 else 'NO'}.
then save final synthesis report to memory tag [FINAL_PHASE_3_REPORT] (user? true, mode=text)