Systematics of quark/gluon tagging
By P. Gras, S. Höche, Deepak Kar, A. Larkoski, L. Lonnblad, Simon Plätzer, A. Siódmok, Peter Z. Skands, G. Soyez, Jesse Thaler. 2017
153 citations recorded by the source corpus.
A bstractBy measuring the substructure of a jet, one can assign it a “quark” or “gluon” tag. In the eikonal (double-logarithmic) limit, quark/gluon discrimination is determined solely by the color factor of the initiating parton (CF versus CA). In this paper, we confront the challenges faced when going beyond this leading-order understanding, using both parton-shower generators and first-principles calculations to assess the impact of higher-order perturbative and nonperturbative physics. Working in the idealized context of electron-positron collisions, where one can define a proxy for quark and gluon jets based on the Lorentz structure of the production vertex, we find a fascinating interplay between perturbative shower effects and nonperturbative hadronization effects. Turning to proton-proton collisions, we highlight a core set of measurements that would constrain current uncertainties in quark/gluon tagging and improve the overall modeling of jets at the Large Hadron Collider.
Subfields: Nuclear and High Energy Physics
View Paper: https://www.semanticscholar.org/paper/80817bc5faa9e38030728b5fb63ccde2fb5cca88
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
- Atlas Collaboration
- Cms Collaboration
- Gudrun Heinrich
- A. Larkoski
- M. Schönherr
- I. Moult
- Benjamin Nachman
- S. Höche
Citations in the corpus
- Les Houches 2017: Physics at TeV Colliders Standard Model Working Group Report (2017, background): “0} corresponding to the Les Houches Angularity [709], width, and mass, respectively.”
- Looking Inside Jets (2019, background): “ed Well-DeÞned What we mean What people sometimes think we mean Quark as adjective Quark as noun Figure 7.1: Possible denitions of a \quark jet" or a \gluon jet" (from Ref. [136], see also [181]). 7.1 Angularities, ECFs and Casimir scaling The motivation behind using jet shapes for quark-g”
- Classification without labels: learning from mixed samples in high energy physics (2017, methodology): “For quark versus gluon jet tagging, LLP was an important development because useful quark/gluon discrimination information is often subtle and sensitive to low-energy or wide-angle radiation inside jets, which may not be modeled correctly in parton shower generators [37].”
- Energy flow networks: deep sets for particle jets (2018, methodology): “To showcase the efficacy of EFNs and PFNs, we apply them to the task of distinguishing light-quark jets from gluon jets [81–84], finding that they achieve excellent classification performance.”
- Searching for long-lived particles beyond the Standard Model at the Large Hadron Collider (2019, background): “For quark/gluon discrimination, observables characterized by Poisson-like distributions such as particle/track multiplicities or production ratios of particular SM particles tend to yield better discrimination, but suffer from being IRC unsafe and thus subject to large non-perturbative modeling unce”
- Energy flow polynomials: a complete linear basis for jet substructure (2017, methodology): “roperties. The rst three are IRC safe, the next two are Sudakov safe in general (and IRC safe in the noted regions of phase space), and particle multiplicity is IRC unsafe. The Les Houches Angularity [124,125] is calculated with respect to the pT-weighted centroid axis in Eq. (2.12), and the N-subje”