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Record W1989854453 · doi:10.1143/jjap.39.1939

On Landau Damping by Bunch Filling Pattern in the Pohang Light Source Storage Ring

2000· article· en· W1989854453 on OpenAlexfundno aff
Y Kim, M.K. Park, Jung-Yun Huang Jung-Yun Huang, Myeun Kwon, Won Namkung, I. S. Ko

Bibliographic record

VenueJapanese Journal of Applied Physics · 2000
Typearticle
Languageen
FieldEngineering
TopicParticle Accelerators and Free-Electron Lasers
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStorage ringBeam (structure)PhysicsSynchrotronOscillation (cell signaling)HarmonicsLandau dampingDynamic apertureSynchrotron light sourceOpticsSynchrotron radiationSIGNAL (programming language)Spectral lineNuclear physicsPlasmaChemistry

Abstract

fetched live from OpenAlex

The stable beam current of the Pohang Light Source (PLS) is normally limited to about 150 mA despite the design value of 400 mA at 2.0 GeV due to the coupled bunch mode instabilities (CBMIs) which are generated by the interaction between higher order modes of RF cavities and circulating beams. In order to improve this situation, a longitudinal feedback system (LFS) using parallel digital signal processors was installed during the summer maintenance period in 1999. Besides the cure of the CBMIs, this programmable LFS is useful for various beam diagnostics such as the synchrotron oscillation phases and their spreads, and the beam pseudo-spectra that are the beam spectra without beam revolution harmonics. With this bunch-to-bunch diagnostic information, it is found that properly arranged bunch filling patterns can increase the stored beam current significantly without an active longitudinal feedback due to Landau damping by bunch-to-bunch synchrotron frequency spreads.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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 designSimulation or modeling
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
Published2000
Admission routes1
Has abstractyes

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