Literature DB >> 17501258

Computational complexity of projected entangled pair states.

Norbert Schuch1, Michael M Wolf, Frank Verstraete, J Ignacio Cirac.   

Abstract

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 us 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 us to use existing results from quantum complexity.

Year:  2007        PMID: 17501258     DOI: 10.1103/PhysRevLett.98.140506

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  2 in total

1.  Efficient representation of quantum many-body states with deep neural networks.

Authors:  Xun Gao; Lu-Ming Duan
Journal:  Nat Commun       Date:  2017-09-22       Impact factor: 14.919

2.  Validating quantum-classical programming models with tensor network simulations.

Authors:  Alexander McCaskey; Eugene Dumitrescu; Mengsu Chen; Dmitry Lyakh; Travis Humble
Journal:  PLoS One       Date:  2018-12-10       Impact factor: 3.240

  2 in total

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