50 citations · 55 across the 10 of their papers we have counts for
10 papers
The trainability of photonic quantum circuits
Alexander Makarovskiy, Adam Taylor, Zhenghao Li +5
Variational quantum algorithms are a leading approach to near-term quantum computing, but their scalability can be limited by barren plateaus and the sampling cost of resolving sma…
Gaussian Boson Sampling for Asset Clustering in Statistical Arbitrage Portfolios
Dayne Marcus Lopena, Daniel Buguks, Zhenghao Li +7
Gaussian Boson Sampling (GBS) provides a native photonic quantum heuristic for sampling dense subgraphs from adjacency matrices, offering a scalable physical approach to combinator…
Improving the loss threshold for quantum advantage in photonic sensors by complete photon counting
Gerard J. Machado, Yazeed K. Alwehaibi, Guillaume Thekkadath +9
Tolerance to imperfections is a defining performance criterion for quantum sensors. The threshold for achieving a quantum advantage depends on the input state, sensor configuration…
Displaced Gaussian Boson Sampling for enhanced max-clique search
Ewan Mer, Zhenghao Li, Shang Yu +2
Gaussian Boson Sampling (GBS) is capable of solving certain classes of graph problems owing to the samples produced by such a device having a connection to the hafnian matrix funct…
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…
Extensible universal photonic quantum computing with nonlinearity
Shang Yu, Jinzhao Sun, Kuan-Cheng Chen +17
Universal quantum computing requires an architecture that supports both linear circuits and, crucially, strong nonlinear resources. For quantum photonic systems, integrating such n…
Topological network analysis using a programmable photonic quantum processor
Shang Yu, Jinzhao Sun, Zhenghao Li +11
Understanding topological features in networks is crucial for unravelling complex phenomena across fields such as neuroscience, condensed matter, and high-energy physics. However,…
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…
Shedding Light on the Future: Exploring Quantum Neural Networks through Optics
Shang Yu, Zhian Jia, Aonan Zhang +7
At the dynamic nexus of artificial intelligence and quantum technology, quantum neural networks (QNNs) play an important role as an emerging technology in the rapidly developing fi…
A universal programmable Gaussian Boson Sampler for drug discovery
Shang Yu, Zhi-Peng Zhong, Yuhua Fang +21
Gaussian Boson Sampling (GBS) exhibits a unique ability to solve graph problems, such as finding cliques in complex graphs. It is noteworthy that many drug discovery tasks can be v…