Tensor train optimization of parametrized quantum circuits

We examine a particular realization of derivative-free method as implemented on tensor train based optimization to the variational quantum eigensolver. As an example, we consider parametrized quantum circuits composed of a low-depth hardware-efficient ansatz and Hamiltonian variational ansatz for ad...

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Bibliographic Details
Published inarXiv.org
Main Authors Paradezhenko, Georgii, Pervishko, Anastasiia, Yudin, Dmitry
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 03.06.2023
Subjects
Circuits
Ising model
Mathematical analysis
Optimization
Parameterization
Tensors
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Summary:We examine a particular realization of derivative-free method as implemented on tensor train based optimization to the variational quantum eigensolver. As an example, we consider parametrized quantum circuits composed of a low-depth hardware-efficient ansatz and Hamiltonian variational ansatz for addressing the ground state of the transverse field Ising model. We further make a comparison with gradient-based optimization techniques and discuss on the advantage of using tensor train based optimization, especially in the presence of noise.
ISSN:2331-8422