# Soft Functions for Generic Jet Algorithms and Observables at Hadron Colliders

## TL;DR

This paper develops a general method to compute one-loop soft functions for various jet algorithms and observables at hadron colliders, enabling precise predictions for jet-related measurements.

## Contribution

It introduces a generalized approach to calculate soft functions for different jet definitions and observables, extending previous hemisphere decompositions and including small-radius expansions.

## Key findings

- Soft functions computed for multiple jet algorithms.
- Small-R expansion accurately approximates full soft functions.
- Explicit results for angularity measurements in pp collisions.

## Abstract

We introduce a method to compute one-loop soft functions for exclusive $N$-jet processes at hadron colliders, allowing for different definitions of the algorithm that determines the jet regions and of the measurements in those regions. In particular, we generalize the $N$-jettiness hemisphere decomposition of [Jouttenus 2011] in a manner that separates the dependence on the jet boundary from the observables measured inside the jet and beam regions. Results are given for several factorizable jet definitions, including anti-$k_T$, XCone, and other geometric partitionings. We calculate explicitly the soft functions for angularity measurements, including jet mass and jet broadening, in $pp \to L + 1$ jet and explore the differences for various jet vetoes and algorithms. This includes a consistent treatment of rapidity divergences when applicable. We also compute analytic results for these soft functions in an expansion for a small jet radius $R$. We find that the small-$R$ results, including corrections up to $\mathcal{O}(R^2)$, accurately capture the full behavior over a large range of $R$.