QuIC provides a training-free quantum graph embedding proven permutation-invariant and injective for labeled graphs under an irrational-angle condition in the ideal case, with empirical separation shown on noisy hardware for hard graph families including CFI instances.
An optimal lower bound on the number of variables for graph identification
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QuIC: A Training-Free Quantum Graph Embedding from Ideal Analysis to Practical Hardware Evaluation
QuIC provides a training-free quantum graph embedding proven permutation-invariant and injective for labeled graphs under an irrational-angle condition in the ideal case, with empirical separation shown on noisy hardware for hard graph families including CFI instances.