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
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it