pith. machine review for the scientific record. sign in

arxiv: quant-ph/0606140 · v4 · submitted 2006-06-16 · 🪐 quant-ph

Recognition: unknown

The Complexity of Stoquastic Local Hamiltonian Problems

Authors on Pith no claims yet
classification 🪐 quant-ph
keywords stoquastichamiltonianslh-minclasscomplexityhamiltonianlocalbelongs
0
0 comments X
read the original abstract

We study the complexity of the Local Hamiltonian Problem (denoted as LH-MIN) in the special case when a Hamiltonian obeys conditions of the Perron-Frobenius theorem: all off-diagonal matrix elements in the standard basis are real and non-positive. We will call such Hamiltonians, which are common in the natural world, stoquastic. An equivalent characterization of stoquastic Hamiltonians is that they have an entry-wise non-negative Gibbs density matrix for any temperature. We prove that LH-MIN for stoquastic Hamiltonians belongs to the complexity class AM -- a probabilistic version of NP with two rounds of communication between the prover and the verifier. We also show that 2-local stoquastic LH-MIN is hard for the class MA. With the additional promise of having a polynomial spectral gap, we show that stoquastic LH-MIN belongs to the class POSTBPP=BPPpath -- a generalization of BPP in which a post-selective readout is allowed. This last result also shows that any problem solved by adiabatic quantum computation using stoquastic Hamiltonians lies in PostBPP.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

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

  1. RFOX (Rotated-Field Oscillatory eXchange) quantum algorithm: Towards Parameter-Free Quantum Optimizers

    quant-ph 2026-04 unverdicted novelty 7.0

    RFOX keeps the instantaneous spectral gap flat across interpolation and disorder by using a constant XX catalyst plus derived ZX counter-diabatic drive, yielding faster ground-state convergence on small RFIM instances.