Nearly-frustration-free ground state preparation
Matthew Thibodeau, Bryan K. Clark

TL;DR
This paper introduces a quantum algorithm for preparing ground states of a specific subclass of Hamiltonians called nearly-frustration-free, achieving better dependence on the spectral gap than previous methods, with applications to excited states.
Contribution
The paper presents a new quantum ground state preparation algorithm with improved gap dependence for nearly-frustration-free Hamiltonians, including excited state preparation extensions.
Findings
Algorithm scales as δ^{y/2-1}, better than previous methods.
Provides examples of physically motivated Hamiltonians in the subclass.
Extension allows excited state preparation with similar speedup.
Abstract
Solving for quantum ground states is important for understanding the properties of quantum many-body systems, and quantum computers are potentially well-suited for solving for quantum ground states. Recent work has presented a nearly optimal scheme that prepares ground states on a quantum computer for completely generic Hamiltonians, whose query complexity scales as , i.e. inversely with their normalized gap. Here we consider instead the ground state preparation problem restricted to a special subset of Hamiltonians, which includes those which we term "nearly-frustration-free": the class of Hamiltonians for which the ground state energy of their block-encoded and hence normalized Hamiltonian is within of -1, where is the spectral gap of and . For this subclass, we describe an algorithm whose dependence on…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum many-body systems · Neural Networks and Reservoir Computing
