Chaotic electron dynamics in a FEL with realizable quadrupole wiggler and Gaussian electron beam
Bibliographic record
Abstract
Chaotic motion of electrons causes a considerable decrease in gain and efficiency of free-electron lasers (FELs). In this paper, we study chaotic dynamics of electrons moving with relativistic velocity in a realizable (three-dimensional) quadrupole wiggler when the radial dependency of wiggler magnetic field is fully taken into account using time series, Poincaré surface-of-section maps, and Liapunov exponents. The electron beam is also considered to be realizable with Gaussian density profile and an ion channel is considered as a guiding device for the electron beam. We show that the chaotic behavior of electron motion is due to the nonlinearity of quadrupole wiggler magnetic field and the chaotic electron motion occurs at almost large radial distances in which the wiggler magnetic field is large. Also, we find that one can control the electron chaotic motion by using electron beam with Gaussian density rather than the electron beam with uniform density. Furthermore, we investigate the effect of ion channel and find that when the electrostatic force of ion channel overcomes the nonlinearity effect of quadrupole wiggler magnetic field and self-repulsive force arises from electron beam, the electron motion becomes non-chaotic. We also investigate the electron motion under Budker condition and show that the Budker condition cannot guarantee the electron motion becoming completely non-chaotic.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".