b-Jet Identification in the D0 Experiment

et al; The D0 Collaboration: V. Abazov

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b-Jet Identification in the D0 Experiment

High Energy Physics - Experiment · Submitted 22 Feb 2010

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim This article describes the methods that have been used to identify b-quark jets, exploiting in particular the long lifetimes of b-flavored hadrons, and the calibration of the performance of these algorithms based on collider data.

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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 2,331 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.06 · human participants 0.02 · controlled comparison 0.05 · randomized assignment 0.01 · states quantitative result 0.04 · compares with prior results 0.07 · mentions code or data availability 0.03.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; show every role.

Algorithms distinguishing jets originating from b quarks from other jet flavors are important tools in the physics program of the D0 experiment at the Fermilab Tevatron p-pbar collider. This article describes the methods that have been used to identify b-quark jets, exploiting in particular the long lifetimes of b-flavored hadrons, and the calibration of the performance of these algorithms based on collider data.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#	sentence	role	the authors' own work	states the main conclusion	strength
s0	Algorithms distinguishing jets originating from b quarks from other jet flavors are important tools in the physics program of the D0 experiment at the Fermilab Tevatron p-pbar collider.	background 1.00	0.08	0.06	asserted 1.00
s1	This article describes the methods that have been used to identify b-quark jets, exploiting in particular the long lifetimes of b-flavored hadrons, and the calibration of the performance of these algorithms based on collider data.	contribution 0.77	0.75	0.16	asserted 0.97

What kind of paper the classifier reports this is: method or tool 0.92 · evidence from analysis of existing data 0.73.

What was examined, and what was not

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arXiv listing abstract v1

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full text
figures and tables
references and citing sentences
relations to other papers

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P abstract

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S sections
T body sentences
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R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper

Original abstract

Algorithms distinguishing jets originating from b quarks from other jet flavors are important tools in the physics program of the D0 experiment at the Fermilab Tevatron p-pbar collider. This article describes the methods that have been used to identify b-quark jets, exploiting in particular the long lifetimes of b-flavored hadrons, and the calibration of the performance of these algorithms based on collider data.

Human review

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References

Forward citations

Cited by 6 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV
physics.ins-det 2017-12 accept novelty 6.0 of 10

CMS presents improved bottom- and charm-jet identification algorithms for 13 TeV LHC data, reaching 68% b-jet efficiency at 1% light-flavour misidentification, together with data-driven efficiency scale factors.
Identification of b-quark jets with the CMS experiment
hep-ex 2012-11 accept novelty 6.0 of 10

CMS's b-jet taggers reach 85% efficiency at 10% light-parton misidentification and 70% at 1.5%, with data-to-simulation scale factors measured to 2 to 8% precision.
LHC Predictions from a Tevatron Anomaly in the Top Quark Forward-Backward Asymmetry
hep-ph 2011-01 conditional novelty 6.0 of 10

A color-octet axigluon can fit the CDF top forward-backward asymmetry and survive LHC dijet limits only if an added vector-like quark decouples its light-quark and top couplings, leaving a narrow window near 1 TeV.
Performance of $b$-Jet Identification in the ATLAS Experiment
hep-ex 2015-12 accept novelty 5.0 of 10

ATLAS calibrates its b-jet, c-jet and light-flavour mistag efficiencies on 4.7 fb-1 of 7 TeV data with multiple independent methods and combines them into data-to-simulation scale factors consistent with unity.
An Upgrade Proposal from the PHENIX Collaboration
nucl-ex 2015-01 conditional novelty 5.0 of 10

PHENIX proposes sPHENIX, a 1.5 T solenoid-based jet and Upsilon detector at RHIC, with GEANT 4 projections showing it could measure jet quenching and Upsilon suppression from 20 to 80 GeV.

Show 1 more citing papers

First combination of Tevatron and LHC measurements of the top-quark mass
hep-ex 2014-03 conditional novelty 5.0 of 10

Combining eleven top-mass measurements from the Tevatron and the LHC yields 173.34 plus or minus 0.76 GeV, a 28 percent precision gain over the best single measurement.

How the literature uses it

16 arXiv papers cite this in 23 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

Papers citing it · 12 sentences without a confident label

Uses its method or tool 7 papers

This algorithm is an upgraded version of the neural network $b$-tagging tool used previously [ref] .

Evidence for WZ and ZZ production in final states with b-tagged jets · Summary of Contributing Analyses · 0.87
This algorithm is an upgraded version of the neural network $b$-tagger used previously [ref] .

Updated Combination of Searches for the Standard Model Higgs Boson at the D0 Experiment in 9.7 fb-1 of Data · Summary of Contributing Analyses · 0.86
Jets originating from $b$ quarks are identified by displaced vertices via a $b$-tagging neural net algorithm [ref] .

Measurement of the forward-backward asymmetry in top-antitop quark production in proton-antiproton collisions · Event Selection and Reconstruction · 1.00

Uses its data or values 1 paper

We take these efficiencies from [ref] , where they are parametrized as functions of jet $p_T$ and $η$.

Double parton interactions as a background to associated HW production at the Tevatron · Account of $b$-jet identification efficiencies · 0.97

Cites it as background 2 papers

The heavy flavour tagging algorithms used at the Large Electron-Positron collider (LEP) [ref] and the Tevatron [ref] experiments exploited variables derived from the displaced charged tracks originating from these decayed $b$ or $c$ hadrons to distinguish the heavy flavoured jets from $s$, $u$, $d$ quark and gluon jets.

Tagging more quark jet flavours at FCC-ee at 91 GeV with a transformer-based neural network · Review of Jet Flavour Tagging · 0.84
The first b and c quark tagging algorithms were developed at LEP [ref] and the Tevatron [ref] .

Jet Flavour Tagging for Future Colliders with Fast Simulation · Introduction · 0.99

What it cites · 1 sentence without a confident label

Uses the method or tool of 1 paper

Specifically, the cone jet reconstruction algorithm used within is the Run II cone jet algorithm [ref] .

Run II Jet Physics: Proceedings of the Run II QCD and Weak Boson Physics Workshop · Jet reconstruction and calibration · 1.00

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