Recent developments in automated NLO calculations: the HELAC‐NLO case

Abstract

Achieving a precise description of multi‐parton final states is crucial for the interpretation of the LHC data. Recent years have seen a huge effort in developing methods for an efficient and fully automated computation of cross sections at the one‐loop level enlarging the wealth of predictions accessible at the next‐to‐leading order (NLO). In this proceedings contribution we briefly review the main features of the HELAC‐NLO method and show, as an illustratory example, some results of a complete NLO study of Higgs signal versus irreducible QCD background in production at the LHC.

Merging meets matching in MC@NLO

“…3 Secondly, in order for the above solution not to remain an academic achievement, the computations must be feasible of all matrix elements involved in the relevant NLO cross sections (i.e., up to relatively large multiplicities). This is indeed the case thanks to the extremely high level of automation achieved in the past few years for the one-loop [34][35][36][37][38][39][40][41][42][43][44] and the subtracted real [45][46][47][48][49][50] contributions, both of which have greatly benefitted from the thorough understanding of tree-level-amplitude calculations [51][52][53][54][55][56][57][58][59][60][61].…”

“…7 We have introduced the quantity 38) with r a random number, to be generated event by event; one has p …”

Scaling patterns for QCD jets

“…However, over the past few years this field has progressed enormously. As a consequence for Standard Model processes a similar level of automation as for leadingorder calculations is within reach [34][35][36][37][38][39][40][41][42][43]. An approach applicable for general New Physics extensions, though limited to 2 → 2 processes, has been presented in [44,45].…”