The information loss for QCD matter in mini black holes at LHC
Bibliographic record
Abstract
In this paper we find information loss in mini black holes at LHC by extending the Horowitz and Maldacena mechanism to gluons and calculate the information transformation from the collapsing matter to the state of outgoing Hawking radiation for gluons, quarks, and mesons. Next, we calculate the total cross-section for mesons produced from black holes at LHC. We conclude that the more the mass of the quark within the hadrons, the lower is the cross-section. Then, we consider the effect of quarks inside the black hole on the density matrix of individual quarks within the meson outside of a black hole. At the end, we show that information is not lost in black holes if we ignore interactions between particles inside the event horizon in comparison with the effect of a black hole on particles. However, we observe that the unstable condition of excited black holes causes information loss in them. After that, we anticipate quantum black hole production by using electron–positron annihilation modeling at TeV centre of mass energies and compare the corresponding cross-sections calculated, at this stage, for different black hole states. Finally, we calculate the dependence of gluon tree level amplitudes to their thermal distributions near mini black holes at LHC.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".