Mass from Nothing
Paul Romatschke, Chun-Wei Su, Ryan Weller

TL;DR
This paper demonstrates that in a massless Abelian Higgs model, radiative corrections naturally generate masses for scalar and gauge fields without spontaneous symmetry breaking, predicting new heavy scalar resonances.
Contribution
It provides a non-perturbative analysis showing mass generation without symmetry breaking and predicts observable heavy scalar resonances, offering a novel approach to the hierarchy problem.
Findings
Masses are generated radiatively without spontaneous symmetry breaking.
The model predicts two heavy scalar resonances beyond the Higgs.
The vacuum is metastable and decays to a stable non-perturbative vacuum.
Abstract
We study the Abelian Higgs model with multiple scalar fields, but without mass terms. Solving the model non-perturbatively order-by-order in the number of scalar fields, we find that radiative corrections generate masses for the scalar and gauge boson, without spontaneous symmetry breaking. The mass scales are set by the -parameter of the electroweak running coupling, thereby naturally avoiding the hierarchy problem. No part of our calculation employs a weak-coupling expansion, and we find that the perturbative vacuum is metastable, and hence must decay to the stable non-perturbative vacuum of the theory, which we identify. Although the field content of our Lagrangian is standard, our results predict the existence of two heavy scalar resonances in addition to the Higgs. We believe that these predicted resonances will ultimately allow experimentalists to discriminate between our…
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 · Quantum Chromodynamics and Particle Interactions · Computational Physics and Python Applications
