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Gang Huang

5 papers hereh-index 324 citations6 works total

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

author position
  • middle author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • quant-ph4
  • cs.AI1
same name
  • Gang Huang — 16 papers, h 8
  • Gang Huang — 10 papers, h 19
  • Gang Huang — 8 papers, h 10
  • Gang Huang — 7 papers, h 36
  • Gang Huang — 6 papers, h 1
  • Gang Huang — 4 papers, h 5

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
20242026
collaborators
Showing quant-phShow all

4 papers · 1 filter

quant-ph2026

QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding

Shuxiang Cao, Zijian Zhang, Abhishek Agarwal +29

Quantum computing calibration depends on interpreting experimental data, and calibration plots provide the most universal human-readable representation for this task, yet no system…

quant-ph2025

CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise

Zhenxiao Fu, Leyi Zhao, Xuhong Zhang +3

Quantum Neural Networks (QNNs) have shown significant value across domains, with well-trained QNNs representing critical intellectual property often deployed via cloud-based QNN-as…

quant-ph2024

QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines

Zhenxiao Fu, Min Yang, Cheng Chu +3

Variational quantum circuits (VQCs) have become a powerful tool for implementing Quantum Neural Networks (QNNs), addressing a wide range of complex problems. Well-trained VQCs serv…

quant-ph2024

TITAN: A Distributed Large-Scale Trapped-Ion NISQ Computer

Cheng Chu, Zhenxiao Fu, Yilun Xu +4

Trapped-Ion (TI) technology offers potential breakthroughs for Noisy Intermediate Scale Quantum (NISQ) computing. TI qubits offer extended coherence times and high gate fidelity, m…

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