Numerical hardware-efficient variational quantum simulation of a soliton
solution
- URL: http://arxiv.org/abs/2105.06208v2
- Date: Thu, 12 Aug 2021 16:59:22 GMT
- Title: Numerical hardware-efficient variational quantum simulation of a soliton
solution
- Authors: Andrey Kardashin, Anastasiia Pervishko, Jacob Biamonte, Dmitry Yudin
- Abstract summary: We discuss the capabilities of quantum algorithms with special attention paid to a hardware-efficient variational eigensolver.
A delicate interplay between magnetic interactions allows one to stabilize a chiral state that destroys the homogeneity of magnetic ordering.
We argue that, while being capable of correctly reproducing a uniform magnetic configuration, the hardware-efficient ansatz meets difficulties in providing a detailed description to a noncollinear magnetic structure.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Implementing variational quantum algorithms with noisy intermediate-scale
quantum machines of up to a hundred qubits is nowadays considered as one of the
most promising routes towards achieving a quantum practical advantage. In
multiqubit circuits, running advanced quantum algorithms is hampered by the
noise inherent to quantum gates which distances us from the idea of universal
quantum computing. Based on a one-dimensional quantum spin chain with competing
symmetric and asymmetric pairwise exchange interactions, herein we discuss the
capabilities of quantum algorithms with special attention paid to a
hardware-efficient variational eigensolver. A delicate interplay between
magnetic interactions allows one to stabilize a chiral state that destroys the
homogeneity of magnetic ordering, thus making this solution highly entangled.
Quantifying entanglement in terms of quantum concurrence, we argue that, while
being capable of correctly reproducing a uniform magnetic configuration, the
hardware-efficient ansatz meets difficulties in providing a detailed
description to a noncollinear magnetic structure. The latter naturally limits
the application range of variational quantum computing to solve quantum
simulation tasks.
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