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Record W4387535132 · doi:10.1016/j.nima.2023.168770

Wakefield damping in a distributed coupling linear accelerator

2023· article· en· W4387535132 on OpenAlexafffund
Evan Ericson, Alexej Grudiev, Drew Bertwistle, Mark Boland

Bibliographic record

VenueNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment · 2023
Typearticle
Languageen
FieldEngineering
TopicParticle Accelerators and Free-Electron Lasers
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
FundersCERNUniversity of Saskatchewan
KeywordsCoupling (piping)WakePhysicsLinear particle acceleratorBoundary (topology)Mode (computer interface)WaveguideTransverse planeIdeal (ethics)Computational physicsTopology (electrical circuits)OpticsMechanicsComputer scienceElectrical engineeringEngineeringMathematical analysisMathematicsBeam (structure)

Abstract

fetched live from OpenAlex

The number of cells in a π-mode standing wave (SW) accelerating structure for the Compact Linear Collider (CLIC) project is limited by mode overlap with nearby modes. The distributed coupling scheme avoids mode overlap by treating each cell as independent. Designs of cells suitable for distributed coupling with strong wakefield suppression by waveguide damping have not previously been studied. In this paper we develop a SW cell to be used in a distributed coupling structure that can satisfy the CLIC transverse wake potential limit. From the middle cell of the CLIC-G* travelling wave (TW) structure, a SW cell is designed and then adapted to perform as a cell in a distributed coupling structure. Its wake potentials in an ideal case of open boundaries are reduced to satisfy the wake potential threshold. An electric boundary is added to the model to simulate total reflection at the distribution network. A horizontal coupler cell that connects to the distribution network such that the reflected wakefields remain similar to the open boundary case is simulated. A triplet module which takes advantage of cell-to-cell coupling to reduce reflected wake potential is 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 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: Bench or experimental · 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 science0.0010.001
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 head0.064
GPT teacher head0.375
Teacher spread0.311 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated EquipmentSame topicParticle Accelerators and Free-Electron LasersFrench-language works237,207