Beam-Beam Resonance Widths in the HL-LHC, and Reduction by Phasing of Interaction Points
Bibliographic record
Abstract
Beam-beam interactions are a limiting factor in the planned high luminosity (HL) upgrade to the Large Hadron Collider (HL-LHC). Over the two main interaction regions of the LHC, a particle experiences two head-on and over a hundred long-range beam-beam interactions which drive betatron resonances in the system. Each resonance line in the space of horizontal and vertical tunes has a finite (non-zero) lock-on width. If the particles tunes fall within this width, they will eventually lock on to the resonance and be driven to large amplitude. We show that it is possible to reduce the resonances widths of a given order by using specific values of the phase advance between interaction points. This paper presents the derivation of resonance width for the weak-strong beam-beam effect, as an extension of A.Chaos width formulae for magnetic sextupoles. (A Lie-algebraic approach is used to combine the effect of the individual beam-beam impulses.) The paper then studies the lock-on width arising from two interaction regions containing 140 beam-beam impulses, and shows the cancellation of specific resonances by relative phasing of interaction points in the HL-LHC lattice.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".