3 papers
quant-ph2026
Hardware-Aware Quantum Kernel Design Based on Graph Neural Networks
Fanxu Meng, Yuxiang Liu, Lu Wang +3
Quantum kernels hold significant promise for achieving computational advantages in quantum machine learning (QML), yet their effectiveness critically depends on the design of expre…
quant-ph2025
Quantum-Based Self-Attention Mechanism for Hardware-Aware Differentiable Quantum Architecture Search
Yuxiang Liu, Sixuan Li, Fanxu Meng +2
The automated design of parameterized quantum circuits for variational algorithms in the NISQ era faces a fundamental limitation, as conventional differentiable architecture search…
quant-ph2025
Efficient Self-Consistent Quantum Comb Tomography on the Product Stiefel Manifold
Xinlin He, Zetong Li, Congcong Zheng +3
Characterizing non-Markovian quantum dynamics is currently hindered by the self-inconsistency and high computational complexity of existing quantum comb tomography (QCT) methods. I…