Towards an understanding of jet substructure

By M. Dasgupta, Alessandro Fregoso, S. Marzani, G. Salam. 2013

564 citations recorded by the source corpus.

A bstractWe present first analytic, resummed calculations of the rates at which wide-spread jet substructure tools tag QCD jets. As well as considering trimming, pruning and the mass-drop tagger, we introduce modified tools with improved analytical and phenomenological behaviours. Most taggers have double logarithmic resummed structures. The modified mass-drop tagger is special in that it involves only single logarithms, and is free from a complex class of terms known as non-global logarithms. The modification of pruning brings an improved ability to discriminate between the different colour structures that characterise signal and background. As we outline in an extensive phenomenological discussion, these results provide valuable insight into the performance of existing tools and help lay robust foundations for future substructure studies.

Subfields: Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/ada9839034ccdc12c3fe93e0c9c9f218075847fe

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In Nuclear and High Energy Physics

1. Cms Collaboration
2. Atlas Collaboration
3. Gudrun Heinrich
4. A. Larkoski
5. M. Schönherr
6. I. Moult
7. Fabio Maltoni
8. F. Krauss

Citations in the corpus

• Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd–27th of July 2012 (2013, methodology): “10 Before the completion of this manuscript, two papers appeared [55,56] which perform analytic resummed calculations for boostedobject methods, such as trimming, pruning and mass drop, and energy correlations were computed and used for quark and gluon discrimination in Ref.”
• Les Houches 2017: Physics at TeV Colliders Standard Model Working Group Report (2017, methodology): “Monte Carlo studies have shown that in the regime where one has perturbative control, underlying event is highly suppressed after mMDT/SoftDrop [644,645].”
• Looking Inside Jets (2019, methodology): “[123]), or more quantitatively using analytic models of hadronisation (see e.”
• Power counting to better jet observables (2014, methodology): “More recently, resummation has been applied to some simple jet substructure variables [40–43], and an understanding of some of the subtleties of resummation for ratio observables, as often used in jet substructure, has been developed [44–46].”
• Energy flow polynomials: a complete linear basis for jet substructure (2017, background): “ non-perturbative contributions and jet grooming on EFPs to future work. Eventually, one hopes that the EFPs will be amenable to precision theoretical calculations of jet substructure (see e.g. Refs. [108,139{148]). This is by no means obvious, since generic EFPs have dierent power-counting structur”
• Pileup mitigation at CMS in 13 TeV data (2020, methodology): “The main grooming algorithm used in CMS is the soft drop or modified mass drop tagger [36, 37].”
• Soft drop (2014, background): “This result is the generalization to C (α) 1 of the fact that the mMDT jet mass distribution (here α = 2) is only single logarithmic [59, 60].”
• Small-radius jets to all orders in QCD (2014, methodology): “We believe that the techniques that apply would be of relevance also for the resummation of jet substructure observables such as the modified Mass Drop Tagger’s jet-mass distribution beyond the LL accuracy obtained so far [68].”
• Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV (2017, methodology): “In this paper, the soft-drop algorithm [45, 46], which recursively removes soft wide-angle radiation from a jet, is used to resolve the substructure of the AK8 jets.”
• Jet substructure at the Large Hadron Collider: A review of recent advances in theory and machine learning (2017, methodology): “cally identify soft, wide-angle radiation in a jet and remove it if it fails a threshold criteria. The rst theory calculations of the eects of jet groomers on the jet mass 49 were presented in Refs. [241,334]. These authors calculated the jet mass distribution on jets that had been groomed with trim”
• Medium response in JEWEL and its impact on jet shape observables in heavy ion collisions (2017, methodology): “It is defined through the Soft Drop procedure [50, 51] detailed below and implemented in FastJet [36] contrib.”
• Thinking outside the ROCs: Designing Decorrelated Taggers (DDT) for jet substructure (2016, methodology): “We have found that the conclusions are not strongly dependent on the groomer used, so have used soft-drop with β = 0 (mMDT) for most of our comparisons due to its smoother scaling behavior than other groomers [16].”
• Gaining (mutual) information about quark/gluon discrimination (2014, background): “One option is to do quark/gluon tagging in concert with soft drop declustering [36] (a generalization of modified mass drop tagging [34, 72]).”
• Analytic boosted boson discrimination (2015, background): “This ensures that the only logarithms which appear in a given soft function that are sensitive to both in-jet and out-of-jet scales are true non-global logarithms (NGLs) [78], which first appear at two-loop order in the calculation of a particular soft function.6 Here we focus on the refactorization”
• Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV (2017, methodology): “In this paper, the soft-drop algorithm [45, 46], which recursively removes soft wide-angle radiation from a jet, is used to resolve the substructure of the AK8 jets.”
• Les Houches 2015: Physics at TeV Colliders Standard Model Working Group Report (2016, background): “[485, 486], one can calculate the quark/gluon discrimination power for angularities after jet grooming.”
• The Lund jet plane (2018, methodology): “ading emission to be the rst emission in the Lund declustering sequence that satises z>z cut with z cut = 0:025, which corresponds to the emission that { 13 { would be selected by the mMDT tagger [19] with the same z cut or equivalently by the Soft-Drop (SD) procedure [70] with = 0 and that z cut”
• Systematics of quark/gluon tagging (2017, methodology): “[82, 83], one generically expects quark/gluon discrimination power to degrade after jet grooming, since the soft radiation that is being removed carries information about the color structure of the jet.”