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Xun Gao

26 papers hereh-index 212.6k citations33 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author7
  • middle author15
  • last author3

Across the 25 of 26 papers where every author was matched, so the position is known.

fields
  • quant-ph25
  • cond-mat.dis-nn1
same name
  • Xun Gao — 6 papers, h 6
  • Xun Gao — 5 papers, h 4
  • Xun Gao — 4 papers, h 3
  • Xun Gao — 3 papers, h 2
  • Xun Gao — 2 papers, h 2
  • Xun Gao — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162026
most citedQuantum Optimization of Maximum Independent Set using Rydberg Atom Arrays

456 citations · 1.7k across the 24 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

quant-ph2021★ 152 cited

Fluxonium: an alternative qubit platform for high-fidelity operations

Feng Bao, Hao Deng, Dawei Ding +25

Superconducting qubits provide a promising path toward building large-scale quantum computers. The simple and robust transmon qubit has been the leading platform, achieving multipl…

quant-ph2021★ 43 cited

Limitations of Linear Cross-Entropy as a Measure for Quantum Advantage

Xun Gao, Marcin Kalinowski, Chi-Ning Chou +3

Demonstrating quantum advantage requires experimental implementation of a computational task that is hard to achieve using state-of-the-art classical systems. One approach is to pe…

quant-ph2021★ 1 cited

Quantum reservoir computing using arrays of Rydberg atoms

Rodrigo Araiza Bravo, Khadijeh Najafi, Xun Gao +1

Quantum computing promises to provide machine learning with computational advantages. However, noisy intermediate-scale quantum (NISQ) devices pose engineering challenges to realiz…

quant-ph2021★ 84 cited

Enhancing Generative Models via Quantum Correlations

Xun Gao, Eric R. Anschuetz, Sheng-Tao Wang +2

Generative modeling using samples drawn from the probability distribution constitutes a powerful approach for unsupervised machine learning. Quantum mechanical systems can produce…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.