Ambient air plasma acceleration in tightly-focused ultrashort infrared laser beams
Bibliographic record
Abstract
Recent experimental and theoretical results have demonstrated the possibility of accelerating electrons in the MeV range by focusing tightly a few-cycle laser beam in ambient air. Using Particle-In-Cell (PIC) simulations, this configuration is revisited within a more accurate modelling approach to analyze and optimize the mechanism responsible for electron acceleration. In particular, an analytical model for a linearly polarized tightly-focused ultrashort laser field is derived and coupled to a PIC code, allowing us to model the interaction of laser beams reflected by high-numerical aperture mirrors with laser-induced plasmas. A set of 3D PIC simulations is performed where the laser wavelength is varied from 800 nm to 7.0 $μ$m while the normalized amplitude of the electric field is varied from $a_{0} = 3.6$ to $a_{0} = 7.0$. The preferential forward acceleration of electrons, as well as the analysis of the laser intensity evolution in the plasma and data on electron number density, confirm that the relativistic ponderomotive force is responsible for the acceleration. We also demonstrate that the electron kinetic energy reaches a maximum of $\approx1.6$ MeV when the central wavelength is of 2.5 $μ$m.
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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 | 0.000 |
| 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".