Combination of Searches for Higgs Boson Pair Production in pp Collisions at √s=13 TeV with the ATLAS Detector
Bibliographic record
Abstract
This Letter presents results from a combination of searches for Higgs boson pair production using \( 126\text{–}140\,\,\text{fb}^{-1} \) of proton-proton collision data at \( \sqrt{s} = 13\,\,\text{TeV} \) recorded with the ATLAS detector. At 95% confidence level (CL), the upper limit on the production rate is 2.9 times the standard model (SM) prediction, with an expected limit of 2.4 assuming no Higgs boson pair production. Constraints on the Higgs boson self-coupling modifier \( \kappa_{\lambda} = \lambda_{HHH}/\lambda_{SM}^{HHH} \), and the quartic \( HHVV \) coupling modifier \( \kappa_{2V} = g_{HHVV}/g_{SM}^{HHVV} \), are derived individually, fixing the other parameter to its SM value. The observed 95% CL intervals are \( -1.2 < \kappa_{\lambda} < 7.2 \) and \( 0.6 < \kappa_{2V} < 1.5 \), respectively, while the expected intervals are \( -1.6 < \kappa_{\lambda} < 7.2 \) and \( 0.4 < \kappa_{2V} < 1.6 \) in the SM case. Constraints obtained for several interaction parameters within Higgs effective field theory are the strongest to date, offering insights into potential deviations from SM predictions.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".