Laser acceleration of low emittance, high energy ions and applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Laser-accelerated ion sources have exceptional properties, i.e. high brightness and high spectral cut-off (56 MeV at present), high directionality and laminarity (at least 100-fold better than conventional accelerators beams), short burst duration (ps). Thanks to these properties, these sources open new opportunities for applications. Among these, we have already explored their use for proton radiography of fields in plasmas and for warm dense matter generation. These sources could also stimulate development of compact ion accelerators or be used for medical applications. To extend the range of applications, ion energy and conversion efficiency must however be increased. Two strategies for doing so using present-day lasers have been successfully explored in LULI experiments. In view of applications, it is also essential to control (i.e. collimate and energy select) these beams. For this purpose, we have developed an ultra-fast laser-triggered micro-lens providing tuneable control of the beam divergence as well as energy selection.
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.
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 it