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量子计算中的效率优化:平衡热力学与计算性能。

Efficiency optimization in quantum computing: balancing thermodynamics and computational performance.

作者信息

Śmierzchalski Tomasz, Mzaouali Zakaria, Deffner Sebastian, Gardas Bartłomiej

机构信息

Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, 44-100, Gliwice, Poland.

Department of Physics, University of Maryland, Baltimore County, Baltimore, MD, 21250, USA.

出版信息

Sci Rep. 2024 Feb 24;14(1):4555. doi: 10.1038/s41598-024-55314-z.

Abstract

We investigate the computational efficiency and thermodynamic cost of the D-Wave quantum annealer under reverse-annealing with and without pausing. Our demonstration on the D-Wave 2000Q annealer shows that the combination of reverse-annealing and pausing leads to improved computational efficiency while minimizing the thermodynamic cost compared to reverse-annealing alone. Moreover, we find that the magnetic field has a positive impact on the performance of the quantum annealer during reverse-annealing but becomes detrimental when pausing is involved. Our results, which are reproducible, provide strategies for optimizing the performance and energy consumption of quantum annealing systems employing reverse-annealing protocols.

摘要

我们研究了在有停顿和无停顿的反向退火情况下,D-Wave量子退火器的计算效率和热力学成本。我们在D-Wave 2000Q退火器上的演示表明,与单独的反向退火相比,反向退火和停顿相结合可提高计算效率,同时将热力学成本降至最低。此外,我们发现磁场在反向退火期间对量子退火器的性能有积极影响,但在涉及停顿时则会产生不利影响。我们的结果具有可重复性,为优化采用反向退火协议的量子退火系统的性能和能耗提供了策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2169/10894240/fbdded0733c4/41598_2024_55314_Fig3_HTML.jpg

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