Energy flow polynomials: a complete linear basis for jet substructure

Komiske, Patrick T.; Metodiev, Eric M.; Thaler, Jesse

doi:10.1007/jhep04(2018)013

Cited by 165 publications

(212 citation statements)

References 124 publications

(231 reference statements)

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“…This section also explains two cryptic comments we made in previous papers: footnote 8 of Ref [9]. and footnote 4 of Ref [40]…”

mentioning

confidence: 79%

“…As shown in Ref. [9], multigraphs are an efficient and intuitive way to represent multiparticle correlators. Each of the N sums and weight factors in Eq.…”

Section: A Correlators As Graphsmentioning

confidence: 99%

“…Many common collider observables are encompassed by the EFPs [7,24] or can be cast as exact linear combinations of EFPs [25][26][27][28][29]. While it has been shown that the EFP basis can be useful for jet classification [9,30], the basis is overcomplete even for fixed β, in the sense that there are linear relations among the elements, which complicates the use of linear fitting methods. Understanding these relations is a key goal of this paper, which we will accomplish in Secs.…”

Section: Degreementioning

confidence: 99%

“…Furthermore, in special cases where the pairwise distances θ ij take the form of an inner product, we show that the complexity of computing a multiparticle correlator can be reduced from O(M N ) down to the minimally required O(M ). We highlight various connections of these mathematical results to high-energy physics, including counting kinematic polynomials relevant for superstring amplitudes [1,2] and speeding up the computation of jet substructure observables [7][8][9].…”

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confidence: 99%

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Cutting multiparticle correlators down to size

2020

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Multiparticle correlators are mathematical objects frequently encountered in quantum field theory and collider physics. By translating multiparticle correlators into the language of graph theory, we can gain new insights into their structure as well as identify efficient ways to manipulate them. In this paper, we highlight the power of this graph-theoretic approach by "cutting open" the vertices and edges of the graphs, allowing us to systematically classify linear relations among multiparticle correlators and develop faster methods for their computation. The naive computational complexity of an N -point correlator among M particles is O(M N ), but when the pairwise distances between particles can be cast as an inner product, we show that all such correlators can be computed in linear O(M ) runtime. With the help of new tensorial objects called Energy Flow Moments, we achieve a fast implementation of jet substructure observables like C2 and D2, which are widely used at the Large Hadron Collider to identify boosted hadronic resonances. As another application, we compute the number of leafless multigraphs with d edges up to d = 16 (15,641,159), conjecturing that this is the same as the number of independent kinematic polynomials of degree d, previously known only to d = 8 (279).

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“…This section also explains two cryptic comments we made in previous papers: footnote 8 of Ref [9]. and footnote 4 of Ref [40]…”

mentioning

confidence: 79%

“…As shown in Ref. [9], multigraphs are an efficient and intuitive way to represent multiparticle correlators. Each of the N sums and weight factors in Eq.…”

Section: A Correlators As Graphsmentioning

confidence: 99%

Section: Degreementioning

confidence: 99%

mentioning

confidence: 99%

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Cutting multiparticle correlators down to size

2020

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“…Tagging these top jets, which contains all the decay products of hadronically decaying top quarks is quite a mature field. A plethora of tagging algorithms have been proposed which range from the substructure analyses [2][3][4][5][6][7][8][9][10][11][12][13] to methods taking full advantage of recent advances in the machine learning [14][15][16][17][18][19][20][21][22][23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Jets with electrons from boosted top quarks

Chatterjee

Godbole

Roy

2020

J. High Energ. Phys.

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We propose a method to identify jets consisting of all the visible remnants of boosted top particles when these decay semileptonically to electrons. Within these jets, the electron shower overlaps with the shower initiated by the b quark, which makes the identification of the electron hard. Even if an electron inside a jet is identified, it is difficult to pinpoint whether the electron rich jet is indeed due to top quark decay or not, since the invisible neutrino carries away a nontrivial part of the energy-momentum of the original top quark. Broadly speaking, the method proposed here has three key components. It uses the distribution of energy in various parts of the detector to identify whether the observed jet is consistent with a jet containing an energetic electron. It uses the substructure of the jet to determine the momentum associated with the electron. Finally, it constructs new variables that carry tell-tale features of top quark decay kinematics using an extra ansatz that, there exists a massless invisible four-momentum roughly collimated to the electron, which reconstructs a W and a top when it is combined with the electron and the full jet respectively. We demonstrate the efficacy of this proposal using simulated data and show that our method not only reduces the backgrounds from light flavor jets, b jets from QCD, and hadronic top jets, it can also tell apart jets rich in electrons but not due to top quark decays.

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Looking Inside Jets

Marzani

Soyez

Spannowsky

2019

Lecture Notes in Physics

125

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Energy flow polynomials: a complete linear basis for jet substructure

Cited by 165 publications

References 124 publications

Cutting multiparticle correlators down to size

Cutting multiparticle correlators down to size

Jets with electrons from boosted top quarks

Looking Inside Jets

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