COMPARISON OF SPARSE LINEAR SYSTEMS SOLVERS ON 3-D SUPERCONDUCTOR PROBLEMS
Bibliographic record
Abstract
This paper proposes to compare several solvers on two transient magnetic problems using superconductor material. Because of the highly non-linearity of the conductivity law, the two superconductor problems generate particularly illconditioned matrices. We choose to test three solvers. They are the well-known "Incomplete Gauss Bi-Conjugate Gradient" (IGBCG), "Bi-Conjugate Gradient Stabilized" (Bi-CGStab) from H.A. Van Der Vorst and "Generalized Minimum RESidual" (GMRES) from Y. Saad. Our aim is to compare their respective robustness. After having presented solvers and problems, we compare the obtained results. We conclude that Bi-CGStab and GMRES are more robust than IGBCG on both superconductor problems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".