Phenomenology of photons-enriched semi-visible jets
Bibliographic record
Abstract
Abstract This Letter proposes a new signature for confining dark sectors at the LHC. Under the assumption of a QCD-like hidden sector, hadronic jets containing stable dark bound states originating from hidden strong dynamics, known as semi-visible jets, could manifest in proton-proton collisions. In the proposed simplified model, a heavy $$Z'$$ Z ′ mediator coupling to SM quarks allows the resonant production of dark quarks, subsequently hadronizing in stable and unstable dark bound states. The unstable dark bound states can then decay back to SM quarks via the same $$Z'$$ Z ′ portal or photons via a lighter pseudo-scalar portal (such as an axion-like particle). This mechanism creates a new signature where semi-visible jets are enriched in non-isolated photons. We show that these exotic jets evade the phase space probed by current LHC searches exploiting jets or photons due to the expected high jet neutral electromagnetic fraction and photons candidates non-isolation, respectively. In the proposed analysis strategy to tackle such signature, we exploit jets as final state objects to represent the underlying QCD-like hidden sector. We show that, by removing any selection on the neutral electromagnetic fraction from the jet identification criteria, higher signal efficiency can be reached. To enhance the signal-to-background discrimination, we train a deep neural network as a jet tagger that exploits differences in the substructure of signal and background jets. We estimate that with the available triggers for Run 2 and this new strategy, a high mass search can claim a $$5 \sigma $$ 5 σ discovery (exclusion) of the $$Z'$$ Z ′ boson with a mass up to 5 TeV (5 TeV) with the full Run 2 data of the LHC when the fraction of unstable dark hadrons decaying to photons pairs is around $${30}{\%}$$ 30 % , and with a coupling of the $$Z'$$ Z ′ to SM quarks of 0.25.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".