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The computational complexity of PEPS

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arxiv quant-ph/0611050 v2 pith:GNF77RWH submitted 2006-11-06 quant-ph cond-mat.other

The computational complexity of PEPS

classification quant-ph cond-mat.other
keywords pepscomplexitycreatingallowscomputationalstatesthemapproximate
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We determine the computational power of preparing Projected Entangled Pair States (PEPS), as well as the complexity of classically simulating them, and generally the complexity of contracting tensor networks. While creating PEPS allows to solve PP problems, the latter two tasks are both proven to be #P-complete. We further show how PEPS can be used to approximate ground states of gapped Hamiltonians, and that creating them is easier than creating arbitrary PEPS. The main tool for our proofs is a duality between PEPS and postselection which allows to use existing results from quantum compexity.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Algorithmic Aspects of Gauged Gaussian Fermionic PEPS: Gauge Fixing and Translation Invariance

    hep-lat 2025-12 conditional novelty 6.0

    For Z2 GGFPEPS Monte Carlo in 2+1D, updating 1/4–1/2 of links per step is fastest in wall-clock time, gauge fixing generally slows convergence, and explicit spatial averaging helps the magnetic energy error.

  2. Projected Entangled Pair States for Lattice Gauge Theories with Dynamical Fermions

    hep-lat 2024-12 unverdicted novelty 6.0

    Gauged Gaussian PEPS ansatz demonstrated on Z2 gauge theory with dynamical fermions, agreeing with exact diagonalization on small lattices and feasible for larger ones.