A single messenger qubit in a layerwise residual quantum circuit increases gradient variance by up to 100x and speeds convergence 4-6x versus standard circuits while preserving expressibility.
Visualizing the loss landscape of neural nets,
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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Intelligence Inertia models the computational resistance to structural change in neural networks via a heuristic relativistic analogy, yielding a J-shaped cost curve that diverges from classical approximations.
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Q-LINK: Quantum Layerwise Information Residual Network via a Messenger Qubit for Barren Plateaus Mitigation
A single messenger qubit in a layerwise residual quantum circuit increases gradient variance by up to 100x and speeds convergence 4-6x versus standard circuits while preserving expressibility.
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Intelligence Inertia: Physical Isomorphism and Applications
Intelligence Inertia models the computational resistance to structural change in neural networks via a heuristic relativistic analogy, yielding a J-shaped cost curve that diverges from classical approximations.