Towards jetography

By G. Salam. 2009

516 citations recorded by the source corpus.

As the LHC prepares to start taking data, this review is intended to provide a QCD theorist’s understanding and views on jet finding at hadron colliders, including recent developments. My hope is that it will serve both as a primer for the newcomer to jets and as a quick reference for those with some experience of the subject. It is devoted to the questions of how one defines jets, how jets relate to partons, and to the emerging subject of how best to use jets at the LHC.

Subfields: Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/9cc0378662d68b86295e3f06e3900ad694f2faae

How researchers see this paper

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

In Nuclear and High Energy Physics

Citations in the corpus

Jet shapes and jet algorithms in SCET (2010, methodology): “with other jet algorithms in [64] and their description in SCET is given in [32].”
QCD-aware recursive neural networks for jet physics (2017, methodology): “while dii′ is less than min(p 2α ti , p 2α ti′ ) [16, 17].”
Les Houches 2017: Physics at TeV Colliders Standard Model Working Group Report (2017, background): “Jet shapes are particularly sensitive to pileup; for example, the jet mass scales as O(A2) [680] for the jet catchment area A [681] (whereas the jet pT scales linearly with A).”
Introduction to Soft-Collinear Effective Theory (2014, background): “A review of different jet algorithms and their applications can be found in [243].”
The Structure of the Proton in the LHC Precision Era (2017, background): “The definition of jet cross sections starts from a well–defined jet algorithm [220], which is usually chosen to be infrared and collinear safe so that the corresponding parton–level cross section for hard scattering at high energies can be calculated in perturbative QCD.”
Higgs Physics at the HL-LHC and HE-LHC (2019, background): “In addition, the di-Higgs system will acquire a substantial boost in the presence of BSM dynamics, and jet substructure techniques [455, 456, 457] make it possible to fully exploit the high-energy limit and optimise the signal significance.”
Jet substructure at the Large Hadron Collider: A review of recent advances in theory and machine learning (2017, background): “There are also a number of more specialized and earlier reviews on different aspects of jet substructure, to which we refer the interested reader [5, 6, 7, 8, 1, 2, 3, 4, 9].”
Boosted objects: a probe of beyond the standard model physics (2010, methodology): “Then in the top candidate rest frame, the top constituents are reclustered into exactly three jets using the e+e− style kT algorithm (see [63] for a description).”
Jet substructure at the Large Hadron Collider (2018, background): “[32, 33] as well as the theory companion this experimental review, Ref.”
Maximizing boosted top identification by minimizing N-subjettiness (2011, background): “Using modern infrared- and collinear-safe jets algorithms [1, 2], the LHC experiments are searching for new physics in monojet production [3, 4], high-mass dijet resonances [5, 6], as well as multijet final states [7, 8], and these searches have an impressive reach for new phenomena.”