Nonlinear Quantum Dynamics in Superconducting NISQ Processors

Muhammad Umer, Eleftherios Mastorakis, Sofia Evangelou, Dimitris G. Angelakis.

A recently proposed variational quantum algorithm has expanded the horizon of variational quantum computing to nonlinear physics and fluid dynamics. In this work, we employ this algorithm to find the ground state of the nonlinear Schrödinger equation with a quadratic potential and implement it on the cloud superconducting quantum processors. We analyze the expressivity of real-amplitude ansatz to capture the ground state of the nonlinear system across various interaction regimes characterized by varying strengths of nonlinearity. Our investigation reveals that although quantum hardware noise impairs the evaluation of the energy cost function, small instances of the problem consistently converge to the ground state. We implement a variety of problem instances on IBM Q devices and report analogous discrepancies in the energy cost function evaluation attributable to quantum hardware noise. The latter are absent in the state fidelity estimation. Our comprehensive analysis offers valuable insights into the practical implementation and advancement of the variational algorithms for nonlinear quantum dynamics.

Cite as BibTex

@misc{umer2024nonlinear,
title={Nonlinear Quantum Dynamics in Superconducting NISQ Processors},
author={Muhammad Umer and Eleftherios Mastorakis and Sofia Evangelou and Dimitris G. Angelakis},
year={2024},
eprint={2403.16426},
archivePrefix={arXiv},
primaryClass={quant-ph}
}

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The QCFD (Quantum Computational Fluid Dynamics) project is funded under the European Union’s Horizon Programme (HORIZON-CL4-2021-DIGITAL-EMERGING-02-10), Grant Agreement 101080085 QCFD.