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Record W2888197213 · doi:10.1063/1.5041498

Apparatus for soft x-ray table-top high harmonic generation

2018· article· en· W2888197213 on OpenAlexfundno aff
Allan S. Johnson, David Wood, Dane R. Austin, Christian Brahms, Andrew Gregory, Konstantin Holzner, Sebastian Jarosch, Esben W. Larsen, Susan Parker, Christian Strüber, Peng Ye, J. W. G. Tisch, J. P. Marangos

Bibliographic record

VenueReview of Scientific Instruments · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMultidisciplinary University Research InitiativeEngineering and Physical Sciences Research CouncilDefence Science and Technology LaboratoryFP7 People: Marie-Curie ActionsMinisterio de Economía y CompetitividadGeneralitat de CatalunyaH2020 European Research CouncilFundación CellexImperial College LondonAstex Pharmaceuticals
KeywordsWater windowAttosecondHigh harmonic generationLaserIonizationSoft X-raysPhoton energyPhysicsPhotonExtreme ultravioletOpticsAtomic physicsRadiationHarmonicWavelengthAbsorption (acoustics)IonUltrashort pulse

Abstract

fetched live from OpenAlex

There has been considerable recent interest in tabletop soft X-ray attosecond sources enabled by the new generation of intense, few-cycle laser sources at operating wavelengths longer than 800 nm. In our recent work [Johnson et al., Sci. Adv. 4(5), eaar3761 (2018)], we have demonstrated a new regime for the generation of X-ray attosecond pulses in the water window (284-540 eV) by high-harmonic generation, which resulted in soft X-ray fluxes of ≈109 photons/s and a maximum photon energy of 600 eV, an order of magnitude and 50 eV higher, respectively, than previously attained with few-cycle drivers. Here we present the key elements of our apparatus for the generation and detection of soft X-ray high harmonic radiation in the water window. Of critical importance is a differentially pumped gas target capable of supporting the multi-atmospheric pressures required to phase-match the high energy emission while strongly constraining the gas density, suppressing the effects of ionization and absorption outside the interaction region.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.012

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 head0.301
Teacher spread0.275 · 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

Citations23
Published2018
Admission routes1
Has abstractyes

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