Efficient Classical Spoofing of the System Linear Cross-Entropy Score Benchmark for Quantum Hamiltonian Simulation Experiments

There exists an efficient classical algorithm that can spoof the System Linear Cross-Entropy Score (sXES) benchmark for noisy quantum Hamiltonian simulation experiments, even when the noise level is above a certain threshold. This result also shows that the complexity-theoretic assumption underlying the hardness of spoofing sXES, called the System Linear Cross-Entropy Quantum Threshold Assumption (sXQUATH), does not hold for sublinear depth quantum circuits.