Collective optical Thomson scattering in pulsed-power driven high energy density physics experiments (invited)
Bibliographic record
Abstract
Optical collective Thomson scattering (TS) is used to diagnose magnetized high energy density physics experiments at the Magpie pulsed-power generator at Imperial College London. The system uses an amplified pulse from the second harmonic of a Nd:YAG laser (3 J, 8 ns, 532 nm) to probe a wide diversity of high-temperature plasma objects, with densities in the range of 1017–1019 cm−3 and temperatures between 10 eV and a few keV. The scattered light is collected from 100 μm-scale volumes within the plasmas, which are imaged onto optical fiber arrays. Multiple collection systems observe these volumes from different directions, providing simultaneous probing with different scattering K-vectors (and different associated α-parameters, typically in the range of 0.5–3), allowing independent measurements of separate velocity components of the bulk plasma flow. The fiber arrays are coupled to an imaging spectrometer with a gated intensified charge coupled device. The spectrometer is configured to view the ion-acoustic waves of the collective Thomson scattered spectrum. Fits to the spectra with the theoretical spectral density function S(K, ω) yield measurements of the local plasma temperatures and velocities. Fitting is constrained by independent measurements of the electron density from laser interferometry and the corresponding spectra for different scattering vectors. This TS diagnostic has been successfully implemented on a wide range of experiments, revealing temperature and flow velocity transitions across magnetized shocks, inside rotating plasma jets and imploding wire arrays, as well as providing direct measurements of drift velocities inside a magnetic reconnection current sheet.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".