Light-quark <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>S</mml:mi><mml:mi>U</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mn>3</mml:mn><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:math> flavor splitting of heavy-light constituent diquark masses and doubly strange diquarks from QCD sum rules
Bibliographic record
Abstract
QCD Laplace sum rules are used to examine the constituent mass spectrum of ${J}^{P}\ensuremath{\in}{{0}^{+},{1}^{+}}$ (scalar, axial vector) heavy-light $[Qq]$ diquarks with $Q\ensuremath{\in}{c,b}$ (charm, bottom) and $q\ensuremath{\in}{u,d,s}$ (up, down, strange). As in previous sum-rule studies, the negative parity ${J}^{P}\ensuremath{\in}{{0}^{\ensuremath{-}},{1}^{\ensuremath{-}}}$ (pseudoscalar, vector) $[Qq]$ diquark mass predictions do not stabilize, so the sum-rule analysis focuses on positive parity $[Qq]$ diquarks. Doubly strange ${J}^{P}={1}^{+}$ (axial vector) $[ss]$ diquarks are also examined, but the resulting sum rules do not stabilize. Hence there is no sum-rule evidence for ${J}^{P}={1}^{+}$ $[ss]$ diquark states, aiding the interpretation of sum-rule analyses of fully strange tetraquark states. The $SU(3)$ flavor splitting effects for $[Qq]$ diquarks are obtained by calculating QCD correlation functions of ${J}^{P}\ensuremath{\in}{{0}^{+},{1}^{+}}$ diquark composite operators up to next-to-leading order in perturbation theory, leading-order in the strange quark mass, and in the chiral limit for nonstrange ($u$, $d$) quarks with an isospin-symmetric vacuum $⟨\overline{n}n⟩=⟨\overline{u}u⟩=⟨\overline{d}d⟩$. Apart from the strange quark mass parameter ${m}_{s}$, the strange quark condensate parameter $\ensuremath{\kappa}=⟨\overline{s}s⟩/⟨\overline{n}n⟩$ has an important impact on $SU(3)$ flavor splittings. A Laplace sum-rule analysis methodology is developed for the mass difference ${M}_{[Qs]}\ensuremath{-}{M}_{[Qn]}$ between the strange and nonstrange heavy-light diquarks to reduce the theoretical uncertainties from all other QCD input parameters. The mass splitting is found to decrease with increasing $\ensuremath{\kappa}$, providing an upper bound on $\ensuremath{\kappa}$ where the ${M}_{[Qs]}\ensuremath{-}{M}_{[Qn]}$ mass hierarchy reverses. In the typical QCD sum-rule range $0.56<\ensuremath{\kappa}<0.74$, $55\text{ }\text{ }\mathrm{MeV}\ensuremath{\lesssim}{M}_{[cs]}\ensuremath{-}{M}_{[cn]}\ensuremath{\lesssim}100\text{ }\text{ }\mathrm{MeV}$ and $75\text{ }\text{ }\mathrm{MeV}\ensuremath{\lesssim}{M}_{[bs]}\ensuremath{-}{M}_{[bn]}\ensuremath{\lesssim}\phantom{\rule{0ex}{0ex}}150\text{ }\text{ }\mathrm{MeV}$, with a slight tendency for larger splittings for the ${J}^{P}={1}^{+}$ axial-vector channels. These constituent mass splitting results are discussed in comparison with values used in constituent diquark models for tetraquark and pentaquark hadronic states.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.462 | 0.317 |
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".