Magnetization amplification in the interlayer pairing superconductor <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>4</mml:mn><mml:mrow><mml:mi>H</mml:mi><mml:mi>b</mml:mi></mml:mrow><mml:mtext>−</mml:mtext><mml:msub><mml:mi>TaS</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:math>
Bibliographic record
Abstract
A recent experiment on the bulk compound $4Hb\text{\ensuremath{-}}{\mathrm{TaS}}_{2}$ reveals an unusual time-reversal symmetry-breaking superconducting state that possesses a magnetic memory not manifest in the normal state. Here we provide a mechanism for this observation by studying the magnetic and electronic properties of $4Hb\text{\ensuremath{-}}{\mathrm{TaS}}_{2}$. We discuss the criterion for a small magnetization in the normal state in terms of spin and orbital magnetizations. Based on an analysis of lattice symmetry and Fermi surface structure, we propose that $4Hb\text{\ensuremath{-}}{\mathrm{TaS}}_{2}$ realizes superconductivity in the interlayer, equal-spin channel with a gap function whose phase winds along the Fermi surface by an integer multiple of $6\ensuremath{\pi}$. The enhancement of the magnetization in the superconducting state compared to the normal state can be explained if the state with a gap winding of $6\ensuremath{\pi}$ is realized, accounting for the observed magnetic memory. We discuss how this superconducting state can be probed experimentally by spin-polarized scanning tunneling microscopy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".