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Record W1581171234 · doi:10.1063/1.3241199

Progress in Fast Ignition Studies with Electrons and Protons

2009· article· en· W1581171234 on OpenAlexaff
A. J. Mackinnon, K. U. Akli, T. Bartal, F. N. Beg, S. Chawla, C. D. Chen, Hui Chen, S. Chen, Enam Chowdhury, R. Fedosejevs, R. R. Freeman, D. Hey, D. P. Higginson, M. H. Key, Jonathan A. King, A. Link, T. Ma, A. G. MacPhee, Dustin Offermann, V. Ovchinnikov, J. Pasley, P. K. Patel, Douglass Schumacher, R. B. Stephens, Ying Y. Tsui, M. S. Wei, L. D. Van Woerkom, K. B. Fournier

Bibliographic record

VenueAIP conference proceedings · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInertial confinement fusionElectronLaserIgnition systemPlasmaNational Ignition FacilityThermonuclear fusionFusion powerAtomic physicsProtonPhysicsMaterials scienceNuclear engineeringNuclear physicsOptics

Abstract

fetched live from OpenAlex

Isochoric heating of inertially confined fusion plasmas by laser driven MeV electrons or protons is an area of great topical interest in the inertial confinement fusion community, particularly with respect to the fast ignition (FI) concept for initiating burn in a fusion capsule. In order to investigate critical aspects needed for a FI point design, experiments were performed to study 1) laser‐to‐electrons or protons conversion issues and 2) laser‐cone interactions including prepulse effects. A large suite of diagnostics was utilized to study these important parameters. Using cone—wire surrogate targets it is found that pre‐pulse levels on medium scale lasers such as Titan at Lawrence Livermore National Laboratory produce long scale length plasmas that strongly effect coupling of the laser to FI relevant electrons inside cones. The cone wall thickness also affects coupling to the wire. Conversion efficiency to protons has also been measured and modeled as a function of target thickness, material. Conclusions from the proton and electron source experiments will be presented. Recent advances in modeling electron transport and innovative target designs for reducing igniter energy and increasing gain curves will also be discussed. In conclusion, a program of study will be presented based on understanding the fundamental physics of the electron or proton source relevant to FI.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.401

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 head0.018
GPT teacher head0.279
Teacher spread0.262 · 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 designObservational
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

Citations1
Published2009
Admission routes1
Has abstractyes

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