Edge-Local and Qubit-Efficient Quantum Graph Learning for the NISQ Era

arXiv:2602.16018 · quant-ph, cs.ET, cs.LG · Submitted 2026-02-17 · Read on arXiv

quant-ph, cs.ET, cs.LG

Submitted: 2026-02-17

Updated: 2026-08-29

Code: https://github.com/ArminAhmadkhaniha/QGCNlib

Terminology

• Embeddings — 21× in this paper · explained in 2 episodes
• Feature Extraction — 16× in this paper · explained in 2 episodes
• Clustering — 8× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Deep Graph Infomax — 6× in this paper
• Representation Learning — 6× in this paper · explained in 2 episodes
• Aggregation — 5× in this paper · explained in 1 episode
• Quantum Alternating Operator Ansatz — 5× in this paper
• Quantum Circuits — 5× in this paper · explained in 2 episodes
• Adjacency Matrix — 4× in this paper · explained in 1 episode
• Activation Function — 3× in this paper · explained in 1 episode
• GNNs — 3× in this paper · explained in 2 episodes
• Pseudo-labels — 3× in this paper · explained in 2 episodes
• Combinatorial Optimization — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Graph Neural Networks (GNNs) — 2× in this paper · explained in 7 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Adiabatic Evolution — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Ancilla Qubits — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Hybrid Architectures — 1× in this paper · explained in 3 episodes
• Hybrid Models — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Normalized Mutual Information — 1× in this paper
• Pseudo-labeling — 1× in this paper · explained in 3 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes

Sources

• Towards Quantum Graph Neural Networks: An Ego-Graph Learning Approach
• Hybrid Quantum-Classical Graph Convolutional Network
• A Quantum Approximate Optimization Algorithm
• Classification with Quantum Neural Networks on Near Term Processors
• Semi-Supervised Classification with Graph Convolutional Networks
• Deep Graph Infomax
• Robust data encodings for quantum classifiers
• Quantum Graph Neural Networks
• How Powerful are Graph Neural Networks?
• Quantum Graph Convolutional Networks Based on Spectral Methods
• Train on classical, deploy on quantum: scaling generative quantum machine learning to a thousand qubits

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