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Simulations of a new electron gun for the TITAN EBIT

2022· article· en· W4224442718 on OpenAlexaff
J. D. Cardona, K. Dietrich, Ish Mukul, J. Dilling, G. Gwinner, O. Kester, A. A. Kwiatkowski

Bibliographic record

VenueJournal of Physics Conference Series · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversity of VictoriaUniversity of ManitobaTRIUMF
Fundersnot available
KeywordsElectron gunTitan (rocket family)Penning trapPhysicsElectronElectron beam ion trapAtomic physicsNuclear physicsCathode rayElectromagnetic shieldingIon trapNuclear engineeringMass spectrometryEngineering

Abstract

fetched live from OpenAlex

Abstract Penning trap mass spectrometry is the tool of choice for mass measurements to test the Standard Model or lay the nuclear-physics foundation of neutrino physics due to the high precisions achievable. This precision can be further boosted by higher charge states (Ettenauer et al 2011). For this purpose, an electron beam ion trap (EBIT) provides radioactive HCIs at the TITAN facility at TRIUMF. To improve the electron beam properties and its control, a new electron gun is under development. The electron gun within its TITAN EBIT environment was simulated using Field Precision’s TRAK software. A new electrode geometry was chosen and optimized to extract up to 5A, 66 keV electron beams. Due to the strong fringe field of the unshielded 6T magnet, options for the passive and active shielding of the gun were explored to compress the electron beam. During the design process, careful attention was paid to safety and mechanical considerations. Simulations and the status of the new electron gun will be presented.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score0.279

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 head0.022
GPT teacher head0.270
Teacher spread0.249 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

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