This package implements sequential Jet Reconstruction (clustering) algorithms, which are used in high-energy physics as part of event reconstruction for $pp$ and $e^+e^-$ colliders.
Algorithms used are based on the C++ FastJet package (https://fastjet.fr, hep-ph/0512210, arXiv:1111.6097), reimplemented natively in Julia.
The algorithms include anti-${k}_\text{T}$, Cambridge/Aachen, inclusive $k_\text{T}$, generalised $k_\text{T}$ for $pp$ events; and the Durham algorithm and generalised $k_\text{T}$ for $e^+e^-$.
The main interface for reconstruction is jet_reconstruct, called as, e.g.,
jet_reconstruct(particles; algorithm = JetAlgorithm.AntiKt, R = 1.0)
or with some of the optional arguments,
jet_reconstruct(particles; algorithm = JetAlgorithm.GenKt, R = 0.4,
+ p = 0.5, recombine = +, strategy = RecoStrategy.Best)
Where particles is a collection of 4-vector objects (see Input Particle Types) to reconstruct and the algorithm is either given explicitly or implied by the power value.
For the case of generalised $k_T$ (for $pp$ and $e^+e^-$) both the algorithm (GenKt, EEKt) and p are needed.
The R value determines the cone size; in the case of the Durham algorithm the R value is ignored.
The object returned is a ClusterSequence, which internally tracks all merge steps and is used for Inclusive and Exclusive Selections.
Each known algorithm is referenced using a JetAlgorithm scoped enum value.
| Algorithm | Type name | Notes |
|---|
| anti-${k}_\text{T}$ | JetAlgorithm.AntiKt | Implies p=-1 |
| Cambridge/Aachen | JetAlgorithm.CA | Implies p=0 |
| inclusive $k_\text{T}$ | JetAlgorithm.Kt | Implies p=1 |
| generalised $k_\text{T}$ | JetAlgorithm.GenKt | For $pp$, value of p must also be specified |
| $e^+e-$ $k_\text{T}$ / Durham | JetAlgorithm.Durham | R value ignored and can be omitted |
| generalised $e^+e-$ $k_\text{T}$ | JetAlgorithm.EEKt | For $e^+e^-$, value of p must also be specified |
For the three $pp$ algorithms with fixed p values, the p value can be given instead of the algorithm name. However, this should be considered deprecated and will be removed in a future release.
Generally one does not need to manually specify a strategy, but Algorithm Strategy describes how to do this, if desired.
To obtain final jets both inclusive ($p_T$ cut) and exclusive ($n_{jets}$ or $d_{ij}$ cut) selections are supported:
(For exclusive_jets either dcut or njets is needed, but not both.)
Sorting vectors is trivial in Julia, no special sorting methods are provided. As an example, to sort exclusive jets of $>5.0$ (usually GeV, depending on your EDM) from highest energy to lowest:
sorted_jets = sort!(inclusive_jets(cs::ClusterSequence; ptmin=5.0),
+ by=JetReconstruction.energy, rev=true)
Although it has been developed further since the CHEP2023 conference, the CHEP conference proceedings, 10.1051/epjconf/202429505017, should be cited if you use this package:
@article{refId0,
+ author = {{Stewart, Graeme Andrew} and {Gras, Philippe} and {Hegner, Benedikt} and {Krasnopolski, Atell}},
+ doi = {10.1051/epjconf/202429505017},
+ journal = {EPJ Web of Conf.},
+ pages = {05017},
+ title = {Polyglot Jet Finding},
+ url = {https://doi.org/10.1051/epjconf/202429505017},
+ volume = 295,
+ year = 2024,
+ eprint={2309.17309},
+ archivePrefix={arXiv},
+ primaryClass={hep-ex}
+}
The original paper on arXiv is:
@misc{stewart2023polyglot,
+ title={Polyglot Jet Finding},
+ author={Graeme Andrew Stewart and Philippe Gras and Benedikt Hegner and Atell Krasnopolski},
+ year={2023},
+ eprint={2309.17309},
+ archivePrefix={arXiv},
+ primaryClass={hep-ex}
+}
Code in this package is authored by:
- Atell Krasnopolski <delta_atell@protonmail.com>
- Graeme A Stewart <graeme.andrew.stewart@cern.ch>
- Philippe Gras <philippe.gras@cern.ch>
and is Copyright 2022-2024 The Authors, CERN.
The code is under the MIT License.
