Oblique Lessons from the $W$ Mass Measurement at CDF II
Pouya Asadi, Cari Cesarotti, Katherine Fraser, Samuel Homiller, Aditya, Parikh

TL;DR
The paper analyzes the implications of the new $W$ boson mass measurement from CDF II on the Standard Model fit, exploring potential beyond the SM explanations through oblique parameters and specific new physics models.
Contribution
It demonstrates how the large $M_W$ value can be explained by nonzero oblique parameter $U$ or large positive $T$, and proposes models like a real SU(2)$_L$ triplet scalar or singlet-doublet fermions to generate these effects.
Findings
Large $M_W$ can be accommodated with a nonzero $U$ parameter.
Electroweak fit favors large, positive $T$ when $U=0$.
Models like a triplet scalar or fermion pairs can produce the required oblique parameters.
Abstract
The CDF collaboration recently reported a new precise measurement of the boson mass with a central value significantly larger than the SM prediction. We explore the effects of including this new measurement on a fit of the Standard Model (SM) to electroweak precision data. We characterize the tension of this new measurement with the SM and explore potential beyond the SM phenomena within the electroweak sector in terms of the oblique parameters , and . We show that the large value can be accommodated in the fit by a large, nonzero value of , which is difficult to construct in explicit models. Assuming , the electroweak fit strongly prefers large, positive values of . Finally, we study how the preferred values of the oblique parameters may be generated in the context of models affecting the electroweak sector at tree- and loop-level. In particular,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsParticle physics theoretical and experimental studies · Computational Physics and Python Applications · Distributed and Parallel Computing Systems
