Spectral explainability toolkit for quantum-assisted PINNs. It uses Fourier analysis to show how encoding and circuit depth shape a QAPINN's expressivity, pairs that with gradient-variance diagnostics to expose trainability costs, and turns both into a design methodology for choosing quantum layer architectures per PDE class. See README.
qml physics physics-engine quantum-computing simulation-framework quantum-information quantum-algorithms simulation-engine quantum-physics quantum-machine-learning pinn quantum-simulation specops wiser physics-informed-neural-networks bqp quantum-assisted qapinn qinetic-labs wiserxbqp
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Updated
Aug 6, 2026 - Python