NLO Effects in QCD Sum-Rule Analyses of $f_{0}(500)$ as a Tetraquark state
Bibliographic record
Abstract
QCD sum-rule studies have been useful to understand and get an insight on the structure of exotic states, such as tetraquark systems. Moreover, the majority of these studies are performed only at leading-order (LO) within the light tetraquarks systems picture, overlooking the effects of higher order corrections, thus motivating our analysis. Our study [1] focused on the effects of next-to-leading order (NLO) contributions to the mass estimates of the lightest tetraquark state ($J^{PC} = 0^{++}$), the so-called $\sigma$ or $f_{0}(500)$[2], using ratios of QCD Laplace sum-rules. A variety of different models were used, which included multiple resonances and width effects, resulting in a final mass prediction of $0.52\,\text{GeV}< m_{\sigma}< 0.77\,\text{GeV}$. Even though the ratios of sum-rules demonstrated some insesitivity under superficially large NLO contributions, they added the beneficial feature of canceling the dependence on the anomalous dimension. Our findings were in good agreement with patterns found in Chiral Lagrangian studies regarding the four-quark structure of the $\sigma$ state, including the relative coupling strengths within the multiple resonance analysis.
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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 | 0.005 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".