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The Complexity of Translationally Invariant Spin Chains with Low Local Dimension

dc.creatorBausch, Johannes
dc.creatorCubitt, Toby
dc.creatorOzols, Maris
dc.date.accessioned2017-06-29
dc.date.accessioned2018-11-24T23:20:42Z
dc.date.available2017-11-20T12:23:14Z
dc.date.available2018-11-24T23:20:42Z
dc.date.issued2017-11
dc.identifierhttps://www.repository.cam.ac.uk/handle/1810/269416
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/123456789/3633
dc.description.abstractWe prove that estimating the ground state energy of a translationally-invariant, nearest-neighbour Hamiltonian on a 1D spin chain is QMAEXP-complete, even for systems of low local dimension (roughly 40). This is an improvement over the best previously-known result by several orders of magnitude, and it shows that spin-glass-like frustration can occur in translationally-invariant quantum systems with a local dimension comparable to the smallest-known non-translationally-invariant systems with similar behaviour. While previous constructions of such systems rely on standard models of quantum computation, we construct a new model that is particularly well-suited for encoding quantum computation into the ground state of a translationally-invariant system. This allows us to shift the proof burden from optimizing the Hamiltonian encoding a standard computational model to proving universality of a simple model. Previous techniques for encoding quantum computation into the ground state of a local Hamiltonian allow only a linear sequence of gates, hence only a linear (or nearly linear) path in the graph of all computational states. We extend these techniques by allowing significantly more general paths, including branching and cycles, thus enabling a highly efficient encoding of our computational model. However, this requires more sophisticated techniques for analysing the spectrum of the resulting Hamiltonian. To address this, we introduce a framework of graphs with unitary edge labels. After relating our Hamiltonian to the Laplacian of such a unitary labelled graph, we analyse its spectrum by combining matrix analysis and spectral graph theory techniques.
dc.publisherAnnales Henri Poincaré
dc.rightshttp://creativecommons.org/licenses/by/4.0/
dc.rightsAttribution 4.0 International
dc.titleThe Complexity of Translationally Invariant Spin Chains with Low Local Dimension
dc.typeArticle


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