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arXiv 1802.04541cond-mat.dis-nn
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Edwards-Anderson模型的动态贪心算法

Dynamic Greedy Algorithms for the Edwards-Anderson Model

Stefan Schnabel, Wolfhard Janke

AI总结:

本文提出一种利用相似构型历史优化数据加速贪心优化的动态算法,并将其成功应用于Edwards-Anderson自旋玻璃模型的高阶贪心优化与模拟退火搜索,提升了计算性能。

摘要:

为了给Edwards-Anderson自旋玻璃模型的能量景观研究提供一种新工具,我们引入了一种算法,该算法能够基于先前对相似构型执行的优化数据,高效地执行贪心优化。作为应用,我们展示了该技术如何用于执行高阶贪心优化和模拟退火搜索,并获得改进的性能。

英文摘要:

To provide a novel tool for the investigation of the energy landscape of the Edwards-Anderson spin-glass model we introduce an algorithm that allows an efficient execution of a greedy optimization based on data from a previously performed optimization for a similar configuration. As an application we show how the technique can be used to perform higher-order greedy optimizations and simulated annealing searches with improved performance.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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