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arXiv 2205.05041hep-ph
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$\rho$参数与CDF W质量反常:关于标量三重态作用的观测研究

The $ρ$ parameter and the CDF W-mass anomaly: observations on the role of scalar triplets

Rituparna Ghosh, Biswarup Mukhopadhyaya, Utpal Sarkar

AI总结:

本研究针对CDF-II的W玻色子质量反常结论,用$\rho$参数检验非二重态希格斯模型,发现含复标量三重态及Georgi-Machacek模型可与新数据自洽,后者需复、实三重态真空期望值有微小劈裂,并探讨了相关物理影响。

摘要:

$\rho$参数与W玻色子、Z玻色子质量一起,可作为电弱对称性破缺区扩展模型的奥卡姆剃刀准则。我们将其应用于非二重态希格斯情形,检验CDF-II(对撞机探测器II期)关于W玻色子质量的观测结论。暂不对CDF的结论作任何评判,我们研究表明:一般而言,在树图近似下,若仅采用现有Z玻色子质量、以及来自全局拟合或ATLAS(超环面仪器)实验的早期$M_W$取值,那些树图层面预言$\rho=1$的理论模型与CDF的结论存在4-6个标准差的不一致。我们选取了若干物理动机充分的模型场景,它们除了包含常规的希格斯二重态外,还带有一个或多个SU(2)标量三重态。研究显示,包含复标量三重态的场景、以及同时包含复三重态与实三重态的场景(即Georgi-Machacek模型),都可以与新的实验数据相自洽;其中第二种场景要求复三重态与实三重态的真空期望值之间存在微小劈裂。我们将探讨这种劈裂带来的影响,包括树图层面的效应,以及来自不可计算的新物理对$M_W$的贡献,并以$H^{\pm}W^{\mp}Z$型相互作用顶点为例说明其物理意义。

英文摘要:

The $ρ$-parameter, together with the W-and Z-masses, acts as Occam's razor on extensions of the electroweak symmetry breaking sectors. We apply this to non-doublet Higgs scenarios, by examining the CDF- $II$ claim on the W-boson mass. Suspending any judgement on the CDF claim, we show that in general, if one works at the tree level, theoretical models which predict $ρ=1$ at the tree-level are inconsistent with the CDF claims at 4-6 standard deviations if one confines oneself to the existing Z-boson mass, and the earlier $M_W$ value from either the global fit or the ATLAS data. We take some well-motivated scenarios containing one or more scalar SU(2) triplets in addition to the usual doublet, and show that, both a scenario including a complex scalar triplet and one with a complex as well as a real triplet (the Georgi-Machacek model) can be made consistent with the new data, where a small splitting between the complex and the real triplet vacuum expectation values is required in the second scenario. We will explore the consequences of this splitting, either at tree level or via incalculable new physics contribution to $M_W$, and indicate, as illustrations its implications in $H^{\pm}W^{\mp}Z$ type interaction vertices.

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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