English

Muon-Electron Scattering at NNLO

High Energy Physics - Phenomenology 2022-09-23 v1

Abstract

This thesis provides a pedagogical overview of the theoretical foundations of the McMule framework, a Monte Carlo integrator for processes with muons and other leptons. Among other things, we show how the simple infrared structure in QED can be exploited to construct FKS^\ell, a subtraction scheme for soft singularities to all orders in perturbation theory. Furthermore, we present the method of massification as a solution to the problem of multi-scale integrals in the presence of large scale hierarchies. Finally, we introduce next-to-soft stabilisation as an elegant tool to stabilise the numerically delicate real-virtual contribution. To this end, we generalise the Low-Burnett-Kroll theorem for massive fermions to one loop. This allows for a straightforward application of the method without the need of explicit calculations. We have developed all of these techniques with fully differential NNLO QED calculations in mind and have successfully applied them to many processes such as the muon decay as well as Bhabha and M{\o}ller scattering. One of the main drivers of these developments has been the MUonE experiment requiring a high-precision theory prediction for muon-electron (μ\mu-ee) scattering at the level of 10ppm10\, \text{ppm}. The multi-scale nature of μ\mu-ee scattering makes this process particularly challenging from a technical point of view. Only the combined application of FKS^\ell, massification, and next-to-soft stabilisation makes the corresponding calculation possible. This thesis therefore presents for the first time the fully differential calculation of the complete set of NNLO corrections to μ\mu-ee scattering. This represents a major step towards the ambitious 10ppm10\, \text{ppm} target precision of the MUonE experiment.

Keywords

Cite

@article{arxiv.2209.11110,
  title  = {Muon-Electron Scattering at NNLO},
  author = {Tim Engel},
  journal= {arXiv preprint arXiv:2209.11110},
  year   = {2022}
}

Comments

PhD thesis, 135 pages, partially based on arXiv:1811.06461, arXiv:1909.10244, arXiv:2007.01654, arXiv:2106.07469, arXiv:2107.12311, and arXiv:2112.07570

R2 v1 2026-06-28T01:54:36.740Z