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, 569 (7756), 355-360

Self-verifying Variational Quantum Simulation of Lattice Models

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Self-verifying Variational Quantum Simulation of Lattice Models

C Kokail et al. Nature.

Abstract

Hybrid classical-quantum algorithms aim to variationally solve optimization problems using a feedback loop between a classical computer and a quantum co-processor, while benefiting from quantum resources. Here we present experiments that demonstrate self-verifying, hybrid, variational quantum simulation of lattice models in condensed matter and high-energy physics. In contrast to analogue quantum simulation, this approach forgoes the requirement of realizing the targeted Hamiltonian directly in the laboratory, thus enabling the study of a wide variety of previously intractable target models. We focus on the lattice Schwinger model, a gauge theory of one-dimensional quantum electrodynamics. Our quantum co-processor is a programmable, trapped-ion analogue quantum simulator with up to 20 qubits, capable of generating families of entangled trial states respecting the symmetries of the target Hamiltonian. We determine ground states, energy gaps and additionally, by measuring variances of the Schwinger Hamiltonian, we provide algorithmic errors for the energies, thus taking a step towards verifying quantum simulation.

Comment in

  • Scaling up quantum simulations.
    Berges J. Berges J. Nature. 2019 May;569(7756):339-340. doi: 10.1038/d41586-019-01483-1. Nature. 2019. PMID: 31092943 No abstract available.

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