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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