The effects of laser polarization and wavelength on injection dynamics of a laser wakefield accelerator
Bibliographic record
Abstract
Here, we investigate the effects of laser polarization and wavelength on electron injection dynamics in a laser wakefield accelerator. During the ionization process, electrons gain residual momentum and kinetic energy via above threshold ionization, which has a strong dependence on laser polarization. A circularly polarized laser pulse results in a much higher residual momentum and kinetic energy gain for the ionized electrons compared with the linearly polarized case. This residual momentum results in particle injection because of the sensitivity of particle trapping to the initial conditions and enhanced the total injected beam charge in both experiments and particle-in-cell simulations. Due to the strong correlation of above threshold ionization with laser wavelength, in this work we extended the investigation to long wavelength (up to 20 μm) drive pulses using particle-in-cell simulations. Owing to the gain in kinetic energy, it may be expected that the charge trapped would consistently increase for circular polarization with increasing laser wavelength, but this was not observed. Instead, there are oscillations with wavelength in the relative trapped charge between linear and circular polarization cases, which arise because of ionization and heating effects on the plasma. Our studies highlight the complex interplay between several different physical effects, including injection regimes—above threshold ionization assisted injection, wave-breaking injection by carrier-envelope-phase effects and ionization injection—ionization gradient induced laser pulse evolution, and thermal modifications to the wake structure that need considering when extrapolating laser wakefield acceleration to different wavelength regimes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".