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Record W2087449230 · doi:10.1063/1.4789748

Investigation of laser-driven proton acceleration using ultra-short, ultra-intense laser pulses

2013· article· en· W2087449230 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysics of Plasmas · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of TorontoInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsLaserPhysicsProtonPulse durationUltrashort pulsePulse (music)OpticsAccelerationRange (aeronautics)Atomic physicsIrradiationUltrafast laser spectroscopySapphireMaterials scienceNuclear physics

Abstract

fetched live from OpenAlex

We report optimization of laser-driven proton acceleration, for a range of experimental parameters available from a single ultrafast Ti:sapphire laser system. We have characterized laser-generated protons produced at the rear and front target surfaces of thin solid targets (15 nm to 90 μm thicknesses) irradiated with an ultra-intense laser pulse (up to 1020 W⋅cm−2, pulse duration 30 to 500 fs, and pulse energy 0.1 to 1.8 J). We find an almost symmetric behaviour for protons accelerated from rear and front sides, and a linear scaling of proton energy cut-off with increasing pulse energy. At constant laser intensity, we observe that the proton cut-off energy increases with increasing laser pulse duration, then roughly constant for pulses longer than 300 fs. Finally, we demonstrate that there is an optimum target thickness and pulse duration.

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.

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 score0.313
Threshold uncertainty score0.880

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 communication0.0000.001
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 head0.037
GPT teacher head0.267
Teacher spread0.230 · 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