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minimal-lagrangians: Generating and studying dark matter model Lagrangians with just the particle content
Computer Physics Communications ( IF 6.3 ) Pub Date : 2021-04-01 , DOI: 10.1016/j.cpc.2020.107773
Simon May

minimal-lagrangians is a Python program which allows one to specify the field content of an extension of the Standard Model of particle physics and, using this information, to generate the most general renormalizable Lagrangian that describes such a model. As the program was originally created for the study of minimal dark matter models with radiative neutrino masses, it can handle additional scalar or Weyl fermion fields which are $\mathrm{SU}(3)_{\mathrm{C}}$ singlets, $\mathrm{SU}(2)_{\mathrm{L}}$ singlets, doublets or triplets, and can have arbitrary $\mathrm{U}(1)_{\mathrm{Y}}$ hypercharge. It is also possible to enforce an arbitrary number of global $\mathrm{U}(1)$ symmetries (with $\mathbb{Z}_2$ as a special case) so that the new fields can additionally carry such global charges. In addition to human-readable and $\mathrm{\LaTeX}$ output, the program can generate SARAH model files containing the computed Lagrangian, as well as information about the fields after electroweak symmetry breaking (EWSB), such as vacuum expectation values (VEVs) and mixing matrices. This capability allows further detailed investigation of the model in question, with minimal-lagrangians as the first component in a tool chain for rapid phenomenological studies of "minimal" dark matter models requiring little effort and no unnecessary input from the user.

中文翻译:

最小拉格朗日:仅使用粒子含量生成和研究暗物质模型拉格朗日

minimum-lagrangians 是一个 Python 程序,它允许您指定粒子物理标准模型扩展的场内容,并使用此信息生成描述此类模型的最一般的可重整化拉格朗日量。由于该程序最初是为研究具有辐射中微子质量的最小暗物质模型而创建的,因此它可以处理额外的标量或外尔费米子场,这些场是 $\mathrm{SU}(3)_{\mathrm{C}}$ 单线态, $\mathrm{SU}(2)_{\mathrm{L}}$ 单峰、双峰或三峰,并且可以具有任意的 $\mathrm{U}(1)_{\mathrm{Y}}$ 超荷。还可以强制执行任意数量的全局 $\mathrm{U}(1)$ 对称性($\mathbb{Z}_2$ 作为特殊情况),以便新字段可以额外携带此类全局费用。除了人类可读的和 $\mathrm{\LaTeX}$ 输出,该程序可以生成包含计算出的拉格朗日量的 SARAH 模型文件,以及有关电弱对称破坏 (EWSB) 后场的信息,例如真空期望值 (VEV) 和混合矩阵。这种能力允许对所讨论的模型进行进一步的详细研究,将最小拉格朗日函数作为工具链中的第一个组件,用于对“最小”暗物质模型进行快速现象学研究,无需用户付出任何努力,也无需用户进行不必要的输入。
更新日期:2021-04-01
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