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arXiv 2408.02728hep-ph
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三Higgs双重态模型中的$U(1)$带电暗物质

$U(1)$-charged Dark Matter in three-Higgs-doublet models

A. Kunčinas, P. Osland, M. N. Rebelo

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103 pages, 5 figures, v2: added references, minor text changes
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AI总结：

本研究分类了三Higgs双重态模型中基于未破缺$U(1)$对称性的标量暗物质嵌入方式，发现这些模型包含质量简并的暗物质对，并对最一般的$U(1) \otimes U(1)$对称3HDM进行了数值探索，验证了其在45-2000 GeV质量范围内的可行性。

摘要：

我们探索了可能容纳标量暗物质的三Higgs双重态模型，其稳定性基于未破缺的$U(1)$对称性，而非熟悉的$\mathbb{Z}_2$对称性。我们的目标是对在三Higgs双重态模型中嵌入$U(1)$对称性的所有可能方式进行分类。我们展示并比较了不同的可能性。由于真空保持（守恒）$U(1)$对称性，所有这些模型都包含质量简并的暗物质候选者对。这些模型中的大多数保持CP。在CP守恒的情况下，这些对可以被视为一个在CP下为偶，另一个在CP下为奇，或者在$U(1)$下具有相反电荷。这里提出的并非所有对称性都曾在文献中被识别过，这表明三Higgs双重态模型中仍存在许多开放问题。我们还对$U(1) \otimes U(1)$对称的3HDM进行了数值探索，这是最一般的相不变（实）三Higgs双重态模型。该模型包含一个多组分暗物质部分，具有两个独立的质量标度。在施加相关实验约束后，我们发现在45-2000 GeV的宽暗物质质量范围内存在可能的解，后者为扫描截断值。

英文摘要：

We explore three-Higgs-doublet models that may accommodate scalar Dark Matter where the stability is based on an unbroken $U(1)$-based symmetry, rather than the familiar $\mathbb{Z}_2$ symmetry. Our aim is to classify all possible ways of embedding a $U(1)$ symmetry in a three-Higgs-doublet model. The different possibilities are presented and compared. All these models contain mass-degenerate pairs of Dark Matter candidates due to a $U(1)$ symmetry unbroken (conserved) by the vacuum. Most of these models preserve CP. In the CP-conserving case the pairs can be seen as one being even and the other being odd under CP or as having opposite charges under $U(1)$. Not all symmetries presented here were identified before in the literature, which points to the fact that there are still many open questions in three-Higgs-doublet models. We also perform a numerical exploration of the $U(1) \otimes U(1)$-symmetric 3HDM, this is the most general phase-invariant (real) three-Higgs-doublet model. The model contains a multi-component Dark Matter sector, with two independent mass scales. After imposing relevant experimental constraints we find that there are possible solutions throughout a broad Dark Matter mass range, 45-2000 GeV, the latter being a scan cutoff.

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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