
Fluid Quantum Logic demonstrates that quantum circuits possess native computational primitives requiring no training. A 6-qubit reprogrammable logic unit achieves 100% accuracy on AND, OR, and XOR operations through ancilla rotation alone, with zero parameter updates. Key Results: Zero-shot logic gates (AND/OR/XOR) via circuit geometry Program synthesis reveals only 4/16 Boolean functions native to topology 43% quantum interference in attention mechanisms Perceptual bistability (62-76%) via measurement sampling 100% accuracy on audio rhythm detection with zero training Noise robustness: truth-table preservation at p=0.1 depolarizing noise Platform-independent validation (PennyLane + Qiskit) The architecture implements "field programmability via state preparation" — quantum superposition of logic gates within a single execution cycle. Patent Pending: USPTO 63/921,961 Contents: paper/fluid_quantum_logic.pdf — Full paper demonstrations/ — 5 reproducible Python experiments Requirements: PennyLane ≥0.35, PyTorch ≥2.0, NumPy ≥1.24
Parameterized Quantum Circuits, NISQ, Quantum Computing, Zero-Shot Learning, Qiskit, Quantum Circuits, Quantum Neural Networks, PennyLane, Quantum Machine Learning, Consciousness Modeling
Parameterized Quantum Circuits, NISQ, Quantum Computing, Zero-Shot Learning, Qiskit, Quantum Circuits, Quantum Neural Networks, PennyLane, Quantum Machine Learning, Consciousness Modeling
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