Effect of electron temperature fluctuations on slowly swept Langmuir probe measurements
Bibliographic record
Abstract
Swept Langmuir probes are widely used to measure electron temperature (Te) in laboratory plasmas by performing an exponential fit to the measured volt–ampere (I–V) characteristic. Often the probe voltage sweep frequency is much lower than the characteristic frequencies of the plasma fluctuations and a time-averaged I–V characteristic is used for the fit. We show by numerical modeling that in the presence of Te fluctuations with frequencies well above the voltage sweep frequency this standard technique applied to a swept single probe tends to read higher than the actual time-averaged Te provided no correlated plasma potential (Vp) fluctuations are present. In the presence of coupled Te and Vp fluctuations a slowly swept single probe may read either higher or lower than the average Te, depending on the relative amplitude and phase of the temperature and potential fluctuations. In contrast, swept double probe measurements of Te are virtually unaffected by either Te or Vp fluctuations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.008 | 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".