Search for emerging jets in <i>pp</i> collisions at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msqrt> <mml:mi>s</mml:mi> </mml:msqrt> <mml:mo>=</mml:mo> <mml:mn>13.6</mml:mn> </mml:mrow> </mml:math> TeV with the ATLAS experiment
Bibliographic record
Abstract
Abstract A search for emerging jets is presented using 51.8 fb −1 of proton–proton collision data at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msqrt> <mml:mi>s</mml:mi> </mml:msqrt> <mml:mo>=</mml:mo> <mml:mn>13.6</mml:mn> </mml:mrow> </mml:math> TeV, collected by the ATLAS experiment during 2022 and 2023. The search explores a hypothetical dark sector featuring ‘dark quarks’ that are charged under a confining gauge group and couple to the standard model (SM) via a new mediator particle. These dark quarks undergo showering and hadronisation within the dark sector, forming long-lived dark mesons that decay back into SM particles. This results in jets that contain multiple displaced vertices known as emerging jets. The analysis targets events with pairs of emerging jets, produced either through a vector mediator, Z ′, in the s -channel, or a scalar mediator, Φ, in the t -channel. No significant excess over the SM background is observed. Assuming a dark pion proper decay length between 5 mm and 50 mm, Z ′ mediator masses between 600 GeV and 2550 GeV are excluded for quark and dark quark coupling values of 0.01 and 0.1, respectively. For a quark dark-quark coupling of 0.1, Φ mediator masses between 600 GeV and 1375 GeV are excluded. These results represent the first direct search targeting emerging jet pair production via a Z ′ mediator, as well as the first study of emerging jet production mediated by a scalar particle exchanged in the t -channel.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".