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Record W2953040826 · doi:10.1139/cjp-2019-0002

Improvement of harmonic spectra from superposition of initial state driven by homogeneous and inhomogeneous combined field

2019· article· en· W2953040826 on OpenAlexvenueno aff
Yi Li, Renyu Feng, Yan Qiao

Bibliographic record

VenueCanadian Journal of Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsHarmonicsSuperposition principleHarmonicWater windowCutoffAttosecondHigh harmonic generationAtomic physicsOpticsWavelengthLaserQuantum mechanicsUltrashort pulse

Abstract

fetched live from OpenAlex

A larger harmonic cutoff with a higher harmonic yield is a necessary requirement for producing intense ultrashort extreme ultraviolet (XUV) and X-ray sources. In this paper, we present a potential method to improve the harmonic cutoff and harmonic yield from the superposition of initial states in the He atom driven by the low-intensity homogeneous and inhomogeneous combined field. The results can be separated into two parts, that is, (i) the extension of harmonic cutoff via the optimization of three-color homogeneous and inhomogeneous field (covering the carrier envelope phase, delay time, intensity ratio, and inhomogeneous effect); and (ii) the enhancement of harmonic yield via the superposition of ground state and excited state as the initial state. Consequently, a water window harmonic plateau with an intensity enhancement of six orders of magnitude can be obtained. Moreover, the harmonic plateau is contributed by a single harmonic emission peak. Finally, through the Fourier transformation of some selected harmonics on the spectral continuum, a number of sub-50 as water window attosecond pulses with the intensity enhancement of six orders of magnitude can be obtained.

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 score0.100
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

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

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 head0.005
GPT teacher head0.223
Teacher spread0.218 · 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

Citations28
Published2019
Admission routes1
Has abstractyes

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