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Temporal Narrowing of Neutrons Produced by High-Intensity Short-Pulse Lasers

2015· article· en· W2341096087 on OpenAlexaff
D. P. Higginson, L. Vassura, M. Gugiu, P. Antici, M. Borghesi, Stephanie Brauckmann, Cheikh Tidiane DIOUF, A. Green, L. Palumbo, H. Petrascu, Sarah E. Sofia, M. Stardubtsev, O. Willi, S. Kar, F. Negoiţă, J. Fuchs

Bibliographic record

VenuePhysical Review Letters · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsInstitut National de la Recherche Scientifique
FundersLawrence Livermore National LaboratoryEngineering and Physical Sciences Research CouncilUnitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si InovariiLaserlab-EuropeMinisterstvo Průmyslu a ObchoduMinistry of Education and Science of the Russian FederationConseil Régional, Île-de-FranceAgence Nationale de la RechercheAutoritatea Natională pentru Cercetare StiintificăDeutsche ForschungsgemeinschaftEuropean Social FundU.S. Department of Energy
KeywordsLaserNeutronPulse durationProtonNeutron sourceUltrashort pulseOpticsPulse (music)PhysicsIrradiationMaterials scienceElectromagnetic shieldingNuclear physicsAtomic physics

Abstract

fetched live from OpenAlex

The production of neutron beams having short temporal duration is studied using ultraintense laser pulses. Laser-accelerated protons are spectrally filtered using a laser-triggered microlens to produce a short duration neutron pulse via nuclear reactions induced in a converter material (LiF). This produces a ∼3 ns duration neutron pulse with 10(4) n/MeV/sr/shot at 0.56 m from the laser-irradiated proton source. The large spatial separation between the neutron production and the proton source allows for shielding from the copious and undesirable radiation resulting from the laser-plasma interaction. This neutron pulse compares favorably to the duration of conventional accelerator sources and should scale up with, present and future, higher energy laser facilities to produce brighter and shorter neutron beams for ultrafast probing of dense materials.

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)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.023
GPT teacher head0.289
Teacher spread0.266 · 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

Citations41
Published2015
Admission routes1
Has abstractyes

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