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Record W4399178896 · doi:10.18280/mmep.110516

Investigating Xenon Aggregates Irradiated by Intense Attosecond Laser Pulses

2024· article· en· W4399178896 on OpenAlexvenueno aff
Bariza Boudour

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsXenonAttosecondIrradiationLaserOpticsMaterials scienceAtomic physicsPhysicsOptoelectronicsNuclear physicsUltrashort pulse

Abstract

fetched live from OpenAlex

Ultra-short and intense laser interactions with noble gas are used for accelerating or generating different particles such as electrons, protons or X-rays.Few works have addressed gases, particularly Xenon (Xe).Nevertheless, the analysis of attosecond electron pulses remains a major challenge.Thus, we study clusters of Xe, which leads to high excitation energy.To do this, we adopted the nanoplasma model.Thereby, we simulate the emission electron beam generated by laser absorption to optimize the electron energy and develop ultra-short pulse dense for the development of better detectors capable of resolving higher photon numbers and heat source length.From the simulation results, we found an important production of electrons, proportionally to the number of aggregates under the short and intense laser.In the first ionization, the minimum estimated energy absorbed agrees with the theory.These results enable real progress in different areas, for example, research in physics and chemistry, communication technology, surgery and medical treatment.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.526
Threshold uncertainty score0.551

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 head0.015
GPT teacher head0.221
Teacher spread0.207 · 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 designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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