Principles of general final-state resummation and automated implementation

Abstract

Next-to-leading logarithmic final-state resummed predictions have traditionally been calculated, manually, separately for each observable. In this article we derive NLL resummed results for generic observables. We highlight and discuss the conditions that the observable should satisfy for the approach to be valid, in particular continuous globalness and recursive infrared and collinear safety. The resulting resummation formula is expressed in terms of certain well-defined characteristics of the observable. We have written a computer program, CAESAR, which, given a subroutine for an arbitrary observable, determines those characteristics, enabling full automation of a large class of final-state resummations, in a range of processes.