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arXiv 2503.02935hep-phhep-ex
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探测味盲SMEFT:EFT有效性与能量标度的相互影响

Probing the flavour-blind SMEFT: EFT validity and the interplay of energy scales

Luca Mantani, Veronica Sanz

AI总结:

本研究分析了味盲SMEFT对味观测量的贡献,通过结合LEP、LHC和罕见B介子衰变数据的全局拟合,揭示了低能数据对约束新物理的可靠性及高能数据的EFT有效性问题,强调了全局拟合避免偏差的重要性。

摘要:

标准模型有效场论(SMEFT)提供了一种系统方法,通过封装新物理效应的高维算子来研究对标准模型(SM)的潜在偏离。在这项工作中,我们分析了味盲SMEFT对味观测量的贡献,并评估了它们与来自LEP和LHC的高能测量之间的相互影响。我们进行了全局拟合,结合了LEP精确数据、罕见B介子衰变的味观测量以及LHC双玻色子测量,揭示了包含不同数据集如何打破参数简并并增强对SMEFT系数的灵敏度。我们的研究表明,低能味观测量即使在味盲场景下也能提供可靠的约束,而高能测量可能因运动学增长而面临EFT有效性问题。我们研究了重正化群演化(RGE)和算子混合跨能量标度的影响,强调了低能和高能数据集的互补性。结果强调了味观测量作为新物理稳健探针的重要性,并突出了全局拟合的必要性,以避免来自有限数据集的潜在偏差。最后,我们讨论了我们的发现对基于高能对撞机数据的全局SMEFT分析解释的影响,比较了在树级和圈级对SMEFT有贡献的UV模型。

英文摘要:

The Standard Model Effective Field Theory (SMEFT) offers a systematic approach to study potential deviations from the Standard Model (SM) through higher-dimensional operators that encapsulate new physics effects. In this work, we analyze flavour-blind SMEFT contributions to flavour observables and assess their interplay with high-energy measurements from LEP and LHC. We perform global fits combining LEP precision data, flavour observables from rare B-meson decays, and LHC diboson measurements, revealing how the inclusion of different datasets breaks parameter degeneracies and enhances the sensitivity to SMEFT coefficients. Our study demonstrates that low-energy flavour observables provide reliable constraints even in flavour-blind scenarios, while high-energy measurements can be subject to EFT validity concerns due to kinematic growth. We investigate the impact of renormalization group evolution (RGE) and operator mixing across energy scales, highlighting the complementary nature of low- and high-energy datasets. The results emphasize the importance of flavour observables as robust probes of new physics and underline the necessity of global fits to avoid potential biases from limited datasets. Finally, we discuss the implications of our findings for the interpretation of global SMEFT analyses based on high-energy collider data, comparing UV models that contribute to SMEFT at tree- and loop-level.

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