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A 0.5B-parameter neural tensor-network pre-trained on hundreds of thousands of Hamiltonians generalizes to arbitrary systems—scaling to 8100 qubits.

GeoPT learns physics from synthetic geometry, not labeled data — cutting training data by 60% and hitting peak performance 4x faster on industrial simulations.