How Kondo-holes create intense nanoscale heavy-fermion hybridization disorder
Bibliographic record
Abstract
Replacing a magnetic atom by a spinless atom in a heavy-fermion compound generates a quantum state often referred to as a "Kondo-hole". No experimental imaging has been achieved of the atomic-scale electronic structure of a Kondo-hole, or of their destructive impact [Lawrence JM, et al. (1996) Phys Rev B 53:12559-12562] [Bauer ED, et al. (2011) Proc Natl Acad Sci. 108:6857-6861] on the hybridization process between conduction and localized electrons which generates the heavy-fermion state. Here we report visualization of the electronic structure at Kondo-holes created by substituting spinless thorium atoms for magnetic uranium atoms in the heavy-fermion system URu(2)Si(2). At each thorium atom, an electronic bound state is observed. Moreover, surrounding each thorium atom we find the unusual modulations of hybridization strength recently predicted to occur at Kondo-holes [Figgins J, Morr DK (2011) Phys Rev Lett 107:066401]. Then, by introducing the "hybridization gapmap" technique to heavy-fermion studies, we discover intense nanoscale heterogeneity of hybridization due to a combination of the randomness of Kondo-hole sites and the long-range nature of the hybridization oscillations. These observations provide direct insight into both the microscopic processes of heavy-fermion forming hybridization and the macroscopic effects of Kondo-hole doping.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".