Factorization for groomed jet substructure beyond the next-to-leading logarithm
Christopher Frye, Andrew J. Larkoski, Matthew D. Schwartz, Kai Yan

TL;DR
This paper develops a factorization framework for soft drop jet substructure observables, enabling precise resummation and improved theoretical understanding of groomed jets at the LHC.
Contribution
It derives a universal factorization formula for soft drop jet observables, simplifying calculations and enabling next-to-next-to-leading logarithmic resummation.
Findings
No non-global logarithms in soft drop observables
Resummed jet mass predictions at NNLL accuracy
Reduced hadronization sensitivity in groomed jets
Abstract
Jet grooming algorithms are widely used in experimental analyses at hadron colliders to remove contaminating radiation from within jets. While the algorithms perform a great service to the experiments, their intricate algorithmic structure and multiple parameters has frustrated precision theoretic understanding. In this paper, we demonstrate that one particular groomer called soft drop actually makes precision jet substructure easier. In particular, we derive a factorization formula for a large class of soft drop jet substructure observables, including jet mass. The essential observation that allows for this factorization is that, without the soft wide-angle radiation groomed by soft drop, all singular contributions are collinear. The simplicity and universality of the collinear limit in QCD allows us to show that to all orders, the normalized differential cross section has no…
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