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20182026
most citedUnboxing Quantum Black Box Models: Learning Non-Markovian Dynamics

8 citations · 13 across the 3 of their papers we have counts for

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12 papers · 1 filter

quant-ph2026

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…

quant-ph2026

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…

quant-ph2025

Quantum learning advantage on a scalable photonic platform

Zheng-Hao Liu, Romain Brunel, Emil E. B. Østergaard +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…

quant-ph2025

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…

quant-ph20208 cited

Unboxing Quantum Black Box Models: Learning Non-Markovian Dynamics

Stefan Krastanov, Kade Head-Marsden, Sisi Zhou +3

Characterizing the memory properties of the environment has become critical for the high-fidelity control of qubits and other advanced quantum systems. However, current non-Markovi…

quant-ph2020

Asymptotic theory of quantum channel estimation

Sisi Zhou, Liang Jiang

The quantum Fisher information (QFI), as a function of quantum states, measures the amount of information that a quantum state carries about an unknown parameter. The (entanglement…