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| VOLUME 118 (2023) | ISSUE 12 | PAGE 938 |
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Tensor train optimization of parameterized quantum circuits
G. Paradezhenko*, A. Pervishko*+, D. Yudin*+
*Skolkovo Institute of Science and Technology, 121205 Moscow, Russia +Laboratory of Spin- Orbitronics, Institute of High Technologies and Advanced Materials, Far Eastern Federal University, 690950 Vladivostok, Russia
Abstract
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 parameterized 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. |