Two DNN models map target cavity observables and transmon-cavity parameters (g, ν_q, α) to candidate geometries, recovering designs that match targets within ~5% and ~2% upon re-simulation.
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quant-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A SQUID-array Josephson parametric amplifier achieves near-quantum-limited 20 dB gain over ~50 MHz bandwidth, with its complex gain spectra analytically reproduced by adding Fabry-Pérot interference to a quantum input-output model.
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Neural-Network Inverse Design of SRF Cavities and Transmons for Bosonic Quantum Computation
Two DNN models map target cavity observables and transmon-cavity parameters (g, ν_q, α) to candidate geometries, recovering designs that match targets within ~5% and ~2% upon re-simulation.
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High-gain and large-bandwidth Josephson parametric amplifier influenced by Fabry-P\'erot interference
A SQUID-array Josephson parametric amplifier achieves near-quantum-limited 20 dB gain over ~50 MHz bandwidth, with its complex gain spectra analytically reproduced by adding Fabry-Pérot interference to a quantum input-output model.