1 citations · 1 across the 3 of their papers we have counts for
7 papers
Unveiling Hierarchical Invariants in Multiphoton Linear Optics
Baichuan Yang, Hao Zhan, Minghao Mi +3
Linear optical networks driven by quantum states of light are important building blocks of photonic quantum technologies. They access large bosonic Hilbert spaces through multiphot…
Machine learning of quantum data using optimal similarity measurements
Zhenghao Li, Hao Zhan, Shana H. Winston +11
Quantum machine learning seeks a computational advantage in data processing by evaluating functions of quantum states, such as their similarity, that can be classically intractable…
Experimental Efficient Influence Sampling of Quantum Processes
Hao Zhan, Zongbo Bao, Zekun Ye +4
Characterizing quantum processes is essential for unlocking the potential of quantum devices. However, standard quantum process tomography is resource-intensive and becomes infeasi…
Variational Graphical Quantum Error Correction Codes
Yuguo Shao, Yong-Chang Li, Fuchuan Wei +5
Quantum error correction is essential for achieving fault-tolerant quantum computation. However, most typical quantum error-correcting codes are designed for generic noise models,…
Experimental benchmarking of quantum state overlap estimation strategies with photonic systems
Hao Zhan, Ben Wang, Minghao Mi +4
Accurately estimating the overlap between quantum states is a fundamental task in quantum information processing. While various strategies using distinct quantum measurements have…
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning
Zhenghao Li, Matthew J. H. Kendall, Gerard J. Machado +7
Transition-Edge Sensors (TESs) are very effective photon-number-resolving (PNR) detectors that have enabled many photonic quantum technologies. However, their relatively slow therm…