Hybrid VQLS pipeline with Carleman linearization recovers high-fidelity solutions to the weakly nonlinear Duffing equation on IBM and Xanadu hardware using symmetry-grouped measurements and optimized ansatzes.
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A temperature-scaled hybrid fusion of ResNet and trainable quantum circuit features reaches 87.82% accuracy on BreastMNIST, outperforming classical baselines.
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Measurement-Efficient Variational Quantum Linear Solver for Carleman-Linearized Nonlinear Dynamics
Hybrid VQLS pipeline with Carleman linearization recovers high-fidelity solutions to the weakly nonlinear Duffing equation on IBM and Xanadu hardware using symmetry-grouped measurements and optimized ansatzes.
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On the Complementarity of Quantum and Classical Features: Adaptive Hybrid Quantum-Classical Feature Fusion for Breast Cancer Classification
A temperature-scaled hybrid fusion of ResNet and trainable quantum circuit features reaches 87.82% accuracy on BreastMNIST, outperforming classical baselines.