Distorting the top resonance with effective interactions
Bibliographic record
Abstract
Interference effects in effective field theory (EFT) analyses can significantly distort sensitivity expectations, leaving subtle yet distinct signatures in the reconstruction of final states crucial for limit setting around Standard Model predictions. Using the specific example of four-fermion operators in top-quark pair production at the Large Hadron Collider (LHC), we provide a detailed quantitative assessment of these resonance distortions. We explore how continuum four-fermion interactions affect the resonance shapes, creating potential tensions between the high-statistics resonance regions and rare, high momentum-transfer continuum excesses. Our findings indicate that, although four-fermion interactions do modify the on-shell region comparably to continuum enhancements, current experimental strategies at the high-luminosity LHC are unlikely to capture these subtle interference-induced distortions. Nonetheless, such effects could become critical for precision analyses at future lepton colliders, such as the FCC-ee. Our work underscores the importance of resonance-shape measurements as complementary probes in global EFT approaches, guiding robust and self-consistent experimental strategies in ongoing and future high-energy physics programs.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".