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arXiv 1902.00941nucl-thcs.LGstat.ML
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从头算核物理中的贝叶斯优化

Bayesian optimization in ab initio nuclear physics

Chalmers University of Technology(查尔姆斯理工大学);University of Gothenburg(哥德堡大学)

A. Ekström, C. Forssén, C. Dimitrakakis, D. Dubhashi, H. T. Johansson, A. S. Muhammad, H. Salomonsson, A. Schliep

摘要:

强核相互作用的理论模型包含未知的耦合常数(参数),必须使用校准数据池来确定。在模型复杂的情况下,导致计算耗时,系统地搜索相应的参数域以获得与数据的最佳拟合是特别具有挑战性的。本文探讨了在核相互作用的手征有效场论描述中,应用贝叶斯优化来约束耦合常数的前景。我们发现贝叶斯优化在低维参数域中表现得相当好,并且可以预见它对于优化较小的耦合常数集特别有用。一个具体的例子可以是使用有限核或三核子散射实验的数据来确定主导的三核子力。

英文摘要:

Theoretical models of the strong nuclear interaction contain unknown coupling constants (parameters) that must be determined using a pool of calibration data. In cases where the models are complex, leading to time consuming calculations, it is particularly challenging to systematically search the corresponding parameter domain for the best fit to the data. In this paper, we explore the prospect of applying Bayesian optimization to constrain the coupling constants in chiral effective field theory descriptions of the nuclear interaction. We find that Bayesian optimization performs rather well with low-dimensional parameter domains and foresee that it can be particularly useful for optimization of a smaller set of coupling constants. A specific example could be the determination of leading three-nucleon forces using data from finite nuclei or three-nucleon scattering experiments.

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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