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quant-ph2026
High-fidelity Quantum Readout Processing via an Embedded SNAIL Amplifier
Leon Bello, Boris Mesits, Michael Hatridge +1
Scalable, high-fidelity quantum-state readout remains a central challenge in the development of large-scale superconducting quantum processors. Conventional dispersive readout arch…
quant-ph2025
End-to-end Optimization of Single-Shot Quantum Machine Learning for Bayesian Inference
Theodoros Ilias, Fangjun Hu, Marti Vives +1
We introduce an end-to-end optimization strategy for quantum machine learning that directly targets performance under finite measurement resources, where learning objectives are de…
quant-ph2023
Quantifying the Expressive Capacity of Quantum Systems: Fundamental Limits and Eigentasks
Fangjun Hu, Gerasimos Angelatos, Saeed A. Khan +6
The expressive capacity of quantum systems for machine learning is limited by quantum sampling noise incurred during measurement. Although it is generally believed that noise limit…