For PEPS with strong injectivity above a threshold, belief propagation finds fixed points efficiently and cluster-corrected BP approximates observables to 1/poly(N) error in poly(N) time, with local perturbations affecting the fixed point only locally.
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quant-ph 2years
2026 2representative citing papers
QCPP implements polynomial transformations of Hamiltonians via stochastic mixtures of unitary channels, achieving a tunable tradeoff between query and sample complexity.
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Algorithmic Locality via Provable Convergence in Quantum Tensor Networks
For PEPS with strong injectivity above a threshold, belief propagation finds fixed points efficiently and cluster-corrected BP approximates observables to 1/poly(N) error in poly(N) time, with local perturbations affecting the fixed point only locally.
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Quantum Channel Polynomial Processing
QCPP implements polynomial transformations of Hamiltonians via stochastic mixtures of unitary channels, achieving a tunable tradeoff between query and sample complexity.