A deep photonic QNN achieves nonlinear operations via virtual Hilbert space expansion on a linear chip with four entanglement sources, demonstrated on classification, generation, and state preparation tasks.
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VQE with Dicke state ansatz encodes diversification constraints for multiclass portfolio optimization and outperforms other optimizers when paired with CMA-ES on convergence and approximation metrics.
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Photonic-Implemented Efficient Deep Quantum Neural Network via Virtual-Driven Hilbert Space Expansion
A deep photonic QNN achieves nonlinear operations via virtual Hilbert space expansion on a linear chip with four entanglement sources, demonstrated on classification, generation, and state preparation tasks.
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Multiclass Portfolio Optimization via Variational Quantum Eigensolver with Dicke State Ansatz
VQE with Dicke state ansatz encodes diversification constraints for multiclass portfolio optimization and outperforms other optimizers when paired with CMA-ES on convergence and approximation metrics.