Measurement of Spin Correlation in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>t</mml:mi><mml:mover accent="true"><mml:mi>t</mml:mi><mml:mo>¯</mml:mo></mml:mover></mml:math>Production Using a Matrix Element Approach
Bibliographic record
Abstract
We determine the fraction of $t\overline{t}$ events with spin correlation, assuming that the spin of the top quark is either correlated with the spin of the top antiquark as predicted by the standard model or is uncorrelated. For the first time we use a matrix-element-based approach to study $t\overline{t}$ spin correlation. We use $t\overline{t}\ensuremath{\rightarrow}{W}^{+}b{W}^{\ensuremath{-}}\overline{b}\ensuremath{\rightarrow}{\ensuremath{\ell}}^{+}\ensuremath{\nu}b{\ensuremath{\ell}}^{\ensuremath{-}}\overline{\ensuremath{\nu}}\overline{b}$ final states produced in $p\overline{p}$ collisions at a center-of-mass energy $\sqrt{s}=1.96\text{ }\text{ }\mathrm{TeV}$, where $\ensuremath{\ell}$ denotes an electron or a muon. The data correspond to an integrated luminosity of $5.4\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ and were collected with the D0 detector at the Fermilab Tevatron collider. The result agrees with the standard model prediction. We exclude the hypothesis that the spins of the $t\overline{t}$ are uncorrelated at the 97.7% C.L.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".