Interferometrio characterization of preplasma density for high intensity laser plasma interaction studies
Bibliographic record
Abstract
Summary form only given. High intensity laser plasma interactions are often affected by the preplasma created by the inherent prepulse of the system due to leakage laser light (typically millijoules over nanoseconds) prior to the arrival of the main high energy laser pulse (typically 100's of joules). Even small scalelength preplasma can alter the absorption of laser light and the subsequent creation of high energy electrons and ions in the interaction process. This can have significant effects on the application of such pulses for areas such as Fast Ignition Laser Fusion Energy. In order to correctly model the interaction process it is important to know the plasma density profile accurately prior to the main interaction process. The current study is focussed on characterizing the expected preplasma conditions for experiments carried out at the Titan laser facility at the Lawrence Livermore National Laboratory (LLNL) and similar facilities. Interferometric measurements for accurate characterization of the plasma density profile of an aluminum plasma created by nanosecond duration 532nm Nd:YAG laser pulses are carried out using a femtosecond-laser probe pulse (400nm/130fs). The main laser pulse is focussed onto an aluminum rod using f/20 optics producing a 20μm diameter focal spot and the interferometry is carried out using a Mach Zehnder Interferometer. The interferograms are used to determine the evolution of the density profile of the plasma with time over a time scale of 1 to 5 nanoseconds. The results are then compared to 2D hydrodynamic modeling of the plasma expansion and used to determine the equation of state models which best fit the experiment. From these results, we expect that more accurate preplasma density models can be developed and incorporated into the analysis of high intensity laser plasma interaction experiments. The experimental and simulation results will be presented and discussed.
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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 | 0.000 | 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 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".