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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-ph2025
Scaling Laws of Quantum Information Lifetime in Monitored Quantum Dynamics
Bingzhi Zhang, Fangjun Hu, Runzhe Mo +3
Quantum information is typically fragile under measurements and environmental coupling. Remarkably, we find that its lifetime can scale exponentially with system size when the envi…