Evolution of a plasma column measured through modulation of a high-energy proton beam
Bibliographic record
Abstract
Plasma wakefield acceleration is a method for accelerating particle beams using electromagnetic fields that are orders of magnitude larger than those found in conventional radio frequency cavities. The core component of a plasma wakefield accelerator is the plasma source, which ranges from millimeter-scale gas jets used in laser-driven experiments, to the ten-meter-long rubidium cell used in the AWAKE experiment. The density of the neutral gas is a controlled input to the experiment, but the density of the plasma after ionization depends on many factors. AWAKE uses a high-energy proton beam to drive the plasma wakefield, and the wakefield acts back on the proton bunch by modulating it at the plasma frequency. We infer the plasma density by measuring the frequency of modulation of the proton bunch, and we measure the evolution of the density versus time by varying the arrival of the proton beam with respect to the ionizing laser pulse. Using this technique, we uncover a microsecond-long period of a stable plasma density followed by a rapid decay in density. The stability of the plasma after ionization has implications for the design of much longer vapor cells that could be used to accelerate particle beams to extremely high energies.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".