MPS TE-PAI achieves unbiased classical time evolution by averaging tensor-network representations of randomized shallow Trotter circuits, yielding lower gate counts per sample and better tolerance to bond-dimension truncation than standard methods.
This gate-count is bounded from below asν ∞ ≥2 √ 2∥¯c∥1 T, with equality at ∆ = 2 arctan 1/ √ 2 ≈0.392π[13]
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Quantum-inspired classical simulation through randomized time evolution
MPS TE-PAI achieves unbiased classical time evolution by averaging tensor-network representations of randomized shallow Trotter circuits, yielding lower gate counts per sample and better tolerance to bond-dimension truncation than standard methods.