Collisionless shock acceleration of narrow energy spread ion beams from mixed species plasmas using <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mn>1</mml:mn><mml:mtext> </mml:mtext><mml:mtext> </mml:mtext><mml:mi>μ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math> lasers
Bibliographic record
Abstract
Collisionless shock acceleration of protons and ${\mathrm{C}}^{6+}$ ions has been achieved by the interaction of a ${10}^{20}\text{ }\text{ }\mathrm{W}/{\mathrm{cm}}^{2}$, $1\text{ }\text{ }\ensuremath{\mu}\mathrm{m}$ laser with a near-critical density plasma. Ablation of the initially solid density target by a secondary laser allows for systematic control of the plasma profile. This enables the production of beams with peaked spectra with energies of $10--18\text{ }\text{ }\mathrm{MeV}/\mathrm{amu}$ and energy spreads of 10%--20% with up to $3\ifmmode\times\else\texttimes\fi{}{10}^{9}$ particles within these narrow spectral features. The narrow energy spread and similar velocity of ion species with different charge-to-mass ratios are consistent with acceleration by the moving potential of a shock wave. Particle-in-cell simulations show shock accelerated beams of protons and ${\mathrm{C}}^{6+}$ ions with energy distributions consistent with the experiments. Simulations further indicate the plasma profile determines the trade-off between the beam charge and energy and that with additional target optimization narrow energy spread beams exceeding $100\text{ }\text{ }\mathrm{MeV}/\mathrm{amu}$ can be produced using the same laser conditions.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".