Measurement of inclusive jet and dijet cross-sections in proton-proton collisions at $\sqrt{s}=13$ TeV with the ATLAS detector
Bibliographic record
Abstract
- Measurement of inclusive jet cross-sections with the ATLAS Detector at a centre-of-mass energy 13 TeV Inclusive jet and dijet cross-sections are measured in proton-proton collisions at a centre-of-mass energy of 13 TeV. The measurement uses a dataset with an integrated luminosity of 3.2 fb$^{−1} recorded in 2015 with the ATLAS detector at the Large Hadron Collider. Jets are identified using the anti-kt algorithm with a radius parameter value of R=0.4. The inclusive jet cross-sections are measured double-differentially as a function of the jet transverse momentum, covering the range from 100 GeV to 3.5 TeV, and the absolute jet rapidity up to |y|=3. The double-differential dijet production cross-sections are presented as a function of the dijet mass, covering the range from 300 GeV to 9 TeV, and the half absolute rapidity separation between the two leading jets within |y|<3, y∗, up to y∗=3. Next-to-leading-order, and next-to-next-to-leading-order for the inclusive jet measurement, perturbative QCD calculations corrected for non-perturbative and electroweak effects are compared to the measured cross-sections. - The HepData contain the following files: o) HepData base tables in yaml format for each cross-section (rapidity or ystar bin) Example: atlas_2015_jet_antiktr04_incljet_eta1.txt for R=04 and 0<|Y|<0.5 atlas_2015_jet_antiktr04_mjj_ystar1.txt for R=0.4 and Ystar<0.5 These files are for the default correlation scenario (see below) Sometimes up and down uncertainties can have the same sign. They need to be symmetrized for the chi2 calculation. o) Replica encoding the statistical uncertainties, e.g. to calculate the global statistical correlation matrix The replica can be used to calculate the statistical uncertainty within a few percent. For convenience, the cross-section tables also contains the statistical uncertainty. For inclusive jets: hepdata_tables_data_replicas_incljets.tar.gz For dijets: hepdata_tables_data_replicas_dijets.tar.gz The tarfile contains for each cross-section 10k replica files of the form heprep9997_R06_Eta6.txt The first number is the replica number (random), the following the jet cone size and the rapidity bin In each replica file the format is as follows: The first lines are a description of the cross-section (following old HepData conventions). It includes the replica number of each file, the rapidity bin and the jet cone radius (same as in file name). The following lines with the numbers are the minimum and maximum bin edge and the fluctuated cross-section. o) The alternative splitting of the 2-points systematics is encoded in the following tables: atlas_2015_jet_antiktr04_incljet_altcorr1_eta1.txt For the dijet no alternative correlation scenario is provided. To get the chi2 values as quoted in the paper the theory systematics need to be also decorrelated as described in the paper. Note, that the splitting of the theory numbers has a large effect on the global chi2. o) Electro-weak corrections as function of jet pt (for each rapidity bins) as calculated with the method described in Dittmaier, Huss, Speckner HEP11(2012) 095 arXiv:1210.0438 are given in special tables like atlas_2015_jet_antiktr04_incljetpt_eta5_ewcorr.txt (as example for R=0.4 and 2<|y|<0.5) Each line gives the bin minimum and maximum and the correction The corrections are given as calculated. No uncertainty is given. For some bins at high-pt the values need to be merged to compare to the measurements. o) Non-perturbative correction (hadronisation corrections and underlying event) as function of jet pt (for each rapidity bins). See the paper for a description and references. As described in the tables the default corrections is based on Pythia8AU2CT10_PYHW tune The uncertainty based on pythia8 tunes: 4C MONASH ATLASA14NNPDF ATLASA14MRSTWLO ATLASA14CTEQL1 and on Herwig tunes. Each line gives the middle of the pt bin, the bin minimum and maximum, the default correction and the up and down uncertainty. Comments to HepData tables: o) The systematic uncertainties with the same names are correlated across the cross-section in the various rapidity bins, The statistical uncertainties are uncorrelated in rapidity. (see section 6 in arXiv:1706.03192 and ATLAS-CONF-2015-037) o) The statistical uncertainty of the in situ methods (Gjet, Zjet, MJB, EtaStat ) should be treated as any other systematic uncertainty across pt and eta, but they are uncorrellated with the systematic uncertainties from a different data-set (e.g. ATLAS 2012 and ATLAS 2015 data) even if they have the same name. o) The beam uncertainty is considered as theory systematics since it can be calculated from the applgrid tables.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".