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Characterization of laser wakefield acceleration efficiency with octave spanning near-IR spectrum measurements

2022· article· en· W4307890051 on OpenAlexaff
M. J. V. Streeter, Y. Ma, B. Kettle, S. J. D. Dann, E. Gerstmayr, F. Albert, Nicolas Bourgeois, Silvia Cipiccia, J. M. Cole, I. Gallardo González, Amina Hussein, D. A. Jaroszynski, K. Falk, K. Krushelnick, N. Lemos, N. Lopes, C. Lumsdon, O. Lundh, S. P. D. Mangles, Z. Najmudin, P. P. Rajeev, Ryan Sandberg, M. Shahzad, Roman Spesyvtsev, D. R. Symes, G. Vieux, A. G. R. Thomas

Bibliographic record

VenuePhysical Review Accelerators and Beams · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
FundersAir Force Office of Scientific ResearchEngineering and Physical Sciences Research CouncilHorizon 2020 Framework ProgrammeScience and Technology Facilities CouncilEuropean CommissionCockcroft InstituteLaserlab-EuropeFusion Energy SciencesU.S. Department of EnergyNational Science Foundation
KeywordsLaserPlasma accelerationPlasmaAccelerationPhysicsOpticsElectronCathode rayAtomic physicsNuclear physics

Abstract

fetched live from OpenAlex

We report on experimental measurements of energy transfer efficiencies in a GeV-class laser wakefield accelerator. Both the transfer of energy from the laser to the plasma wakefield and from the plasma to the accelerated electron beam was diagnosed by simultaneous measurement of the deceleration of laser photons and the acceleration of electrons as a function of plasma length. The extraction efficiency, which we define as the ratio of the energy gained by the electron beam to the energy lost by the self-guided laser mode, was maximized at $19\ifmmode\pm\else\textpm\fi{}3%$ by tuning the plasma density and length. The additional information provided by the octave-spanning laser spectrum measurement allows for independent optimization of the plasma efficiency terms, which is required for the key goal of improving the overall efficiency of laser wakefield accelerators.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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