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arxiv: 1311.3161 · v5 · pith:FYZ6BXHKnew · submitted 2013-11-13 · 🪐 quant-ph

Complexity classification of local Hamiltonian problems

classification 🪐 quant-ph
keywords localproblemproblemstermshamiltonianisinganaloguecharacterisation
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The calculation of ground-state energies of physical systems can be formalised as the k-local Hamiltonian problem, which is the natural quantum analogue of classical constraint satisfaction problems. One way of making the problem more physically meaningful is to restrict the Hamiltonian in question by picking its terms from a fixed set S. Examples of such special cases are the Heisenberg and Ising models from condensed-matter physics. In this work we characterise the complexity of this problem for all 2-local qubit Hamiltonians. Depending on the subset S, the problem falls into one of the following categories: in P; NP-complete; polynomial-time equivalent to the Ising model with transverse magnetic fields; or QMA-complete. The third of these classes has been shown to be StoqMA-complete by Bravyi and Hastings. The characterisation holds even if S does not contain any 1-local terms; for example, we prove for the first time QMA-completeness of the Heisenberg and XY interactions in this setting. If S is assumed to contain all 1-local terms, which is the setting considered by previous work, we have a characterisation that goes beyond 2-local interactions: for any constant k, all k-local qubit Hamiltonians whose terms are picked from a fixed set S correspond to problems either in P; polynomial-time equivalent to the Ising model with transverse magnetic fields; or QMA-complete. These results are a quantum analogue of Schaefer's dichotomy theorem for boolean constraint satisfaction problems.

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  1. The Guided Local Hamiltonian Problem for Stoquastic Hamiltonians

    quant-ph 2025-09 unverdicted novelty 8.0

    The Guided Local Hamiltonian problem for stoquastic Hamiltonians is promise BPP-hard (even 2-local on lattices), BQP-hard under fixed local constraints, and admits a deterministic classical approximation algorithm whe...