6 papers
Near-optimal quantum metrology with few-qubit measurements
Liang Mao, Senrui Chen, Hsin-Yuan Huang +2
Quantum metrology, which addresses parameter estimation in quantum systems, has broad applications across science and technology. Conventional metrology protocols for multi-qubit s…
Efficient learning of logical noise from syndrome data
Han Zheng, Chia-Tung Chu, Senrui Chen +4
Characterizing errors in quantum circuits is essential for device calibration, yet detecting rare error events requires a large number of samples. This challenge is particularly se…
Advancing quantum imaging through learning theory
Yunkai Wang, Changhun Oh, Junyu Liu +2
We study quantum imaging by applying the resolvable expressive capacity (REC) formalism developed for physical neural networks (PNNs). In this paradigm of quantum learning, the ima…
Quantum learning advantage on a scalable photonic platform
Zheng-Hao Liu, Romain Brunel, Emil E. B. Ãstergaard +12
Recent advancements in quantum technologies have opened new horizons for exploring the physical world in ways once deemed impossible. Central to these breakthroughs is the concept…
Tight bounds on Pauli channel learning without entanglement
Senrui Chen, Changhun Oh, Sisi Zhou +2
Quantum entanglement is a crucial resource for learning properties from nature, but a precise characterization of its advantage can be challenging. In this work, we consider learni…
Entanglement-enabled advantage for learning a bosonic random displacement channel
Changhun Oh, Senrui Chen, Yat Wong +8
We show that quantum entanglement can provide an exponential advantage in learning properties of a bosonic continuous-variable (CV) system. The task we consider is estimating a pro…