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Record W2803085010 · doi:10.1088/1361-6587/aabf4f

Optical probing of high intensity laser interaction with micron-sized cryogenic hydrogen jets

2018· article· en· W2803085010 on OpenAlexaff
Tim Ziegler, Martin Rehwald, Lieselotte Obst-Huebl, Constantin Bernert, Florian‐Emanuel Brack, C. B. Curry, M. Gauthier, S. H. Glenzer, Sebastian Göde, Lev Kazak, Stephan Kraft, Michael Kuntzsch, Markus Loeser, Josefine Metzkes-Ng, Christian Rödel, Hans-Peter Schlenvoigt, U. Schramm, M. Siebold, J. Tiggesbäumker, Steffen Wolter, Karl Zeil

Bibliographic record

VenuePlasma Physics and Controlled Fusion · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
FundersFusion Energy SciencesOffice of ScienceVolkswagen FoundationLaserlab-Europe
KeywordsLaserPlasmaContext (archaeology)HarmonicsAccelerationOpticsJet (fluid)PhysicsWavelengthPlasma diagnosticsNuclear physicsMechanicsVoltage

Abstract

fetched live from OpenAlex

Abstract Probing the rapid dynamics of plasma evolution in laser-driven plasma interactions provides deeper understanding of experiments in the context of laser-driven ion acceleration and facilitates the interplay with complementing numerical investigations. Besides the microscopic scales involved, strong plasma (self-)emission, predominantly around the harmonics of the driver laser, often complicates the data analysis. We present the concept and the implementation of a stand-alone probe laser system that is temporally synchronized to the driver laser, providing probing wavelengths beyond the harmonics of the driver laser. The capability of this system is shown during a full-scale laser proton acceleration experiment using renewable cryogenic hydrogen jet targets. For further improvements, we studied the influence of probe color, observation angle of the probe and temporal contrast of the driver laser on the probe image quality.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.218
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2018
Admission routes1
Has abstractyes

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