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Record W2994289693 · doi:10.1103/physreva.100.063402

Intense VUV–xenon-cluster interaction revisited

2019· article· en· W2994289693 on OpenAlexafffund
Rishi Pandit, Nicolas Bigaouette, Valerie R. Becker, Jeremy Thurston, Kasey Barrington, Edward Ackad, Lora Ramunno

Bibliographic record

VenuePhysical review. A/Physical review, A · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Ottawa
FundersAir Force Office of Scientific ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsNational Science Foundation
KeywordsXenonBremsstrahlungPhysicsAtomic physicsExcitationExtreme ultravioletCluster (spacecraft)ElectronLaserWork (physics)PhotoexcitationNuclear physicsExcited stateQuantum mechanics

Abstract

fetched live from OpenAlex

During the inaugural experiment at FLASH, the first vacuum ultraviolet (VUV) free-electron laser facility, Wabnitz et al. [Nature 420, 482 (2002)] irradiated xenon clusters and sparked a concerted theoretical and experimental effort to understand how dense, finite plasmas behave under intense irradiation. In this work, we revisit this experiment with a model that is based only on well-established atomic processes. We find that the experimental results can be explained by hybrid quantum-classical molecular-dynamics simulations if collisional excitation, recombination, and a sufficiently deep soft-core potential is used. Our recent theoretical model for inverse bremsstrahlung heating (IBH) is used to show that the measured energy absorbed by the cluster in the experiment is well predicted by our model.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.028

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.

Opus teacher head0.012
GPT teacher head0.350
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2019
Admission routes2
Has abstractyes

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