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Record W2755771086 · doi:10.1063/1.4990487

High repetition rate, multi-MeV proton source from cryogenic hydrogen jets

2017· article· en· W2755771086 on OpenAlexaff
M. Gauthier, C. B. Curry, S. Göde, Florian‐Emanuel Brack, Jongjin B. Kim, M. J. MacDonald, Josefine Metzkes-Ng, Lieselotte Obst-Huebl, Martin Rehwald, Christian Rödel, Hans-Peter Schlenvoigt, W. Schumaker, U. Schramm, Karl Zeil, S. H. Glenzer

Bibliographic record

VenueApplied Physics Letters · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
FundersVolkswagen FoundationU.S. Department of Energy
KeywordsProtonLaserHydrogenAtomic physicsSpectral lineIrradiationRadiationJet (fluid)Materials scienceNuclear physicsPhysicsOptics

Abstract

fetched live from OpenAlex

We report on a high repetition rate proton source produced by high-intensity laser irradiation of a continuously flowing, cryogenic hydrogen jet. The proton energy spectra are recorded at 1 Hz for Draco laser powers of 6, 20, 40, and 100 TW. The source delivers ∼1013 protons/MeV/sr/min. We find that the average proton number over one minute, at energies sufficiently far from the cut-off energy, is robust to laser-target overlap and nearly constant. This work is therefore a first step towards pulsed laser-driven proton sources for time-resolved radiation damage studies and applications which require quasi-continuous doses at MeV energies.

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 science0.0010.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.236
Teacher spread0.223 · 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

Citations60
Published2017
Admission routes1
Has abstractyes

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