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20182021
most citedMachine Learning Topological Phases with a Solid-state Quantum Simulator

69 citations · 83 across the 2 of their papers we have counts for

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quant-ph2021

Quantum federated learning through blind quantum computing

Weikang Li, Sirui Lu, Dong-Ling Deng

Private distributed learning studies the problem of how multiple distributed entities collaboratively train a shared deep network with their private data unrevealed. With the secur…

quant-ph2019

Quantum Adversarial Machine Learning

Sirui Lu, Lu-Ming Duan, Dong-Ling Deng

Adversarial machine learning is an emerging field that focuses on studying vulnerabilities of machine learning approaches in adversarial settings and developing techniques accordin…

quant-ph201914 cited

Optimizing QAOA: Success Probability and Runtime Dependence on Circuit Depth

Murphy Yuezhen Niu, Sirui Lu, Isaac L. Chuang

The quantum approximate optimization algorithm~(QAOA) first proposed by Farhi et al. promises near-term applications based on its simplicity, universality, and provable optimality.…

quant-ph2019

Determining system Hamiltonian from eigenstate measurements without correlation functions

Shi-Yao Hou, Ningping Cao, Sirui Lu +3

Local Hamiltonians arise naturally in physical systems. Despite its seemingly `simple' local structure, exotic features such as nonlocal correlations and topological orders exhibit…

quant-ph2018

Efficient Representation of Topologically Ordered States with Restricted Boltzmann Machines

Sirui Lu, Xun Gao, L. -M. Duan

Representation by neural networks, in particular by restricted Boltzmann machines (RBM), has provided a powerful computational tool to solve quantum many-body problems. An importan…

quant-ph2018

Local-measurement-based quantum state tomography via neural networks

Tao Xin, Sirui Lu, Ningping Cao +5

Quantum state tomography is a daunting challenge of experimental quantum computing even in moderate system size. One way to boost the efficiency of state tomography is via local me…