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quant-ph2026
Reduced Cost Quantum Kernel Training
Daniel R. Germain, Benjamin Goldweber, Kayla J. Rodriguez +1
Quantum kernel methods are promising for near-term quantum machine learning, but their training costs are driven by the quadratic scaling of Gram-matrix construction and the measur…
quant-ph2021★ 25 cited
Feasibility study of quantum computing using trapped electrons
Qian Yu, Alberto M. Alonso, Jackie Caminiti +7
We investigate the feasibility of using electrons in a linear Paul trap as qubits in a future quantum computer. We discuss the necessary experimental steps to realize such a device…