Proton Acceleration: New Developments in Energy Increase, Focusing and Energy Selection
Bibliographic record
Abstract
In the last few years, intense research has been conducted on laser‐accelerated ion sources and their applications. These sources have exceptional properties, i.e. high brightness and high spectral cut‐oft high directionality and laminarity, short burst duration. These proton sources open new opportunities for ion beam generation and control, and could stimulate development of compact ion accelerators for many applications. We have studied the variations of the proton acceleration characteristic time with target and laser parameters. We used these variations to correct one of the model recently developed to predict maximum energies of laser‐accelerated protons for low energy, short duration laser pulses. We have also developed an ultra‐fast laser‐triggered micro‐lens that allows tunable control of the beam divergence as well as energy selection, therefore solving two of the major problems that these proton beams were facing. We used PIC simulations to explain the focusing and energy selection mechanisms, and to study the symmetry of the expanding plasma inside the cylinder.
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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 | 0.001 |
| 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 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".