A permutation-matrix quantum Monte Carlo algorithm samples closed walks of off-diagonal operators, unifies updates across models, and outperforms stochastic series expansion on transverse-field Ising benchmarks.
Since ⟨z|ΛSiq|z⟩ = λ(z)⟨z|Siq|z⟩, for any given configura- tionC = (|z⟩,S iq), there is a contribution λ = λ(z) to the diagonal operator thermal average ⟨Λ⟩
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Permutation Matrix Representation Quantum Monte Carlo
A permutation-matrix quantum Monte Carlo algorithm samples closed walks of off-diagonal operators, unifies updates across models, and outperforms stochastic series expansion on transverse-field Ising benchmarks.