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Record W2901556999 · doi:10.48550/arxiv.1811.06400

Generation of high energy laser-driven electron and proton sources with the 200 TW system VEGA 2 at the Centro de Laseres Pulsados

2018· preprint· en· W2901556999 on OpenAlexaff
L. Volpe, R. Fedosejevs, G. Gatti, J. A. Pérez-Hernández, C. Méndez, Jon Imanol Apiñaniz, X. Vaisseau, C. Salgado, M. Huault, S. Malko, G. Zeraouli, V. Ospina, Andrew Longman, K. Li, O. Varela, Enrique García-García, Irene Hernández-Palmero, J.D. Pisonero, Javier García Ajates, Jesús M. Álvarez, C. L. GARCIA, M. Rico, D. Arana, J. Hernández-Toro, L. Roso

Bibliographic record

VenuearXiv (Cornell University) · 2018
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBetatronVegaPhysicsLaserElectronProtonAccelerationFocal lengthEnergy (signal processing)OpticsAtomic physicsNuclear physicsAstronomy

Abstract

fetched live from OpenAlex

The Centro de Laseres Pulsados in Salamanca Spain has recently started operation phase and the first User access period on the 6 J 30 fs 200 TW system (VEGA 2) already started at the beginning of 2018. In this paper we report on two commissioning experiments recently performed on the VEGA 2 system in preparation for the user campaign. VEGA 2 system has been tested in different configurations depending on the focusing optics and targets used. One configuration (long focal length f=130 cm) is for under-dense laser-matter interaction where VEGA 2 is focused onto a low density gas-jet generating electron beams (via laser wake field acceleration mechanism) with maximum energy up to 500 MeV and an X-ray betatron source with a 10 keV critical energy. A second configuration (short focal length f=40 cm) is for over-dense laser-matter interaction where VEGA 2 is focused onto an 5 microns thick Al target generating a proton beam with a maximum energy of 10 MeV and average energy of 7-8 MeV and temperature of 2.5 MeV. In this paper we present preliminary experimental results.

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: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.588

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 head0.024
GPT teacher head0.176
Teacher spread0.153 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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