A Practical Seedless Infrared Safe Cone Algorithm a

By G. Salam, G. Soyez. 2007

224 citations recorded by the source corpus.

Current cone jet algorithms, widely used at hadron colliders, take event particles as seeds in an iterative search for stable cones. A longstanding infrared (IR) unsafety issue in such algorithms is often assumed to be solvable by adding extra `midpoint' seeds, but actually is just postponed to one order higher in the coupling. A proper solution is to switch to an exact seedless cone algorithm, one that provably identifies all stable cones. The only existing approach takes N 2^N time to find jets among N particles, making it unusable at hadron level. This can be reduced to N^2 ln(N) time, leading to code (SISCone) whose speed is similar to that of public midpoint implementations. Monte Carlo tests provide a strong cross-check of an analytical proof of the IR safety of the new algorithm, and the absence of any 'R_{sep}' issue implies a good practical correspondence between parton and hadron levels. Relative to a midpoint cone, the use of an IR safe seedless algorithm leads to modest changes for inclusive jet spectra, mostly through reduced sensitivity to the underlying event, and significant changes for some multi-jet observables.

Subfields: Aerospace Engineering, Computational Mechanics, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/c9f146546a0960901132fa93815978c0f0b50f3c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Matteo Cacciari
2. G. Salam
3. Michael Spannowsky
4. G. Soyez
5. M. Dasgupta
6. L. Magnea
7. Wolfgang Waltenberger
8. J. Albacete

In Computational Mechanics

1. Matteo Cacciari
2. G. Salam
3. G. Soyez
4. M. Dasgupta
5. L. Magnea
6. Wolfgang Waltenberger
7. Graeme Watt
8. S. Forte

In Mechanical Engineering

1. Matteo Cacciari
2. G. Salam
3. G. Soyez
4. M. Dasgupta
5. L. Magnea
6. Wolfgang Waltenberger

Citations in the corpus

• The anti-$k_t$ jet clustering algorithm (2008, methodology): “An alternative replacement would be the following: find all stable cones (as in SISCone), label the hardest one a jet, remove its particles from the event, and then repeat the procedure on the remaining particles, over and over.”
• A Large Hadron Electron Collider at CERN: Report on the Physics and Design Concepts for Machine and Detector (2012, methodology): “Jets are found with the SISCone jet-algorithm [513].”
• Looking Inside Jets (2019, background): “hen 3 hard particles are in the same vicinity, i.e. one order later in the perturbative expansion than the JetClu algorithm. This infrared-unsafety issue was solved by the introduction of the SISCone [69] algorithm. It provably nds all possible stable cones in an event, making the stable cone search”
• The Catchment Area of Jets (2008, methodology): “Additionally, there will be a large number of other stable cones, of order of the number of ghost particles added to the event [16].”
• Non-perturbative QCD effects in jets at hadron colliders (2007, methodology): “Note that this result is independent of the overlap threshold in the split–merge stage of SISCone and similar algorithms.”
• Jet substructure at the Large Hadron Collider (2018, methodology): “This stems from the necessity of an initial axis, which was eventually solved with the formulation of the SISCone algorithm [22].”