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Record W4382654588 · doi:10.1117/12.2665586

Transient laser-induced breakdown of dielectrics in ultra-relativistic laser-solid interactions (Conference Presentation)

2023· article· en· W4382654588 on OpenAlexaff
Constantin Bernert, Stefan Assenbaum, Stefan Bock, Florian‐Emanuel Brack, T. E. Cowan, C. B. Curry, Marco Garten, Lennart Gaus, M. Gauthier, René Gebhardt, Sebastian Göde, S. H. Glenzer, Uwe Helbig, T. Kluge, Stephan Kraft, Florian Kroll, Lieselotte Obst-Huebl, Thomas Pueschel, Martin Rehwald, Hans-Peter Schlenvoigt, Christopher Schönwälder, U. Schramm, F. Treffert, M. Vescovi, Tim Ziegler, Karl Zeil

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLaserIonizationAtomic physicsDielectricTransient (computer programming)Pulse (music)Materials scienceOpticsPhysicsOptoelectronicsIon

Abstract

fetched live from OpenAlex

We report on the time-resolved observation of transient laser-induced breakdown (LIB) during the leading edge of high-intensity petawatt-class laser pulses with peak intensities up to 6x10^21 W/cm^2 in interaction with dielectric cryogenic hydrogen jet targets. The results show that LIB occurs much earlier than what is typically expected following the concept of barrier suppression ionization and that the laser pulse duration dependence of LIB and laser-induced damage threshold (LIDT) is very relevant to high-intensity laser-solid interactions. We demonstrate an effective approach to determine the onset of LIB, i.e. the starting point of target pre-expansion, by comparing a laser contrast measurement with a characterization study of the target specific LIB thresholds.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.278
Teacher spread0.252 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2023
Admission routes1
Has abstractyes

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