Vision-transformer neural networks trained on simulated charge stability diagrams from a disordered generalized Hubbard model predict SOC-induced spin-flip tunneling amplitudes with R² ≈ 0.94 even when other parameters are unknown.
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Integrating repetition code QEC with logical GHZ entanglement in CMOS spin qubits reduces effective dephasing and enables up to order-of-magnitude improvements in sensitivity to axion-electron coupling g_ae by restoring entanglement-enhanced sensing.
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Predicting spin-orbit coupling in hole spin qubit arrays with vision-transformer-based neural networks on a generalized Hubbard model
Vision-transformer neural networks trained on simulated charge stability diagrams from a disordered generalized Hubbard model predict SOC-induced spin-flip tunneling amplitudes with R² ≈ 0.94 even when other parameters are unknown.
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Quantum Error Correction Assisted Axion Search in CMOS Spin Qubit Arrays
Integrating repetition code QEC with logical GHZ entanglement in CMOS spin qubits reduces effective dephasing and enables up to order-of-magnitude improvements in sensitivity to axion-electron coupling g_ae by restoring entanglement-enhanced sensing.