Charging mechanisms and orbital dynamics of charged dust grains in the LHC
Bibliographic record
Abstract
Dust grains interacting with the beam of particle accelerators are believed to be the cause of several detrimental effects such as beam losses, emittance growth, pressure bursts, and even quenches of superconducting magnets. Experimental observations suggest that these grains are positively charged in electron storage rings and negatively charged in the Large Hadron Collider (LHC). In this paper, the charging mechanisms for dust grains in the LHC are discussed and a possible explanation for the observed polarity is presented. Electron collection, secondary electron emission, and photoelectric emission are considered because of the presence of electron clouds and synchrotron radiation. It is found that the same mechanisms can explain both the positive grain polarity observed in electron storage rings and the negative polarity in the LHC. As a consequence of the charge acquired, the possibility of grains orbiting the beam is discussed. The orbital dynamics in a logarithmic potential is analyzed and critical parameters for describing such orbits are introduced. Finally, LHC beam losses attributed to beam-dust interactions with multiple loss peaks are presented. It is shown that they have an amplitude and a peak separation consistent with what can be expected for orbiting grains.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".