Quantum theory of an atom in proximity to a superconductor
Bibliographic record
Abstract
The impact of superconducting correlations on localized electronic states is important for a wide range of experiments in fundamental and applied superconductivity. This includes scanning tunneling microscopy of atomic impurities at the surface of superconductors, as well as superconducting-ion-chip spectroscopy of neutral ions and Rydberg states. Moreover, atomlike centers close to the surface are currently believed to be the main source of noise and decoherence in qubits based on superconducting devices. The proximity effect is known to dress atomic orbitals in Cooper-pair-like states known as Yu-Shiba-Rusinov (YSR) states, but the impact of superconductivity on the measured orbital splittings and optical-noise transitions is not known. Here we study the interplay between orbital degeneracy and particle-number admixture in atomic states, beyond the usual classical spin approximation. We model the atom as a generalized Anderson model interacting with a conventional $s$-wave superconductor. In the limit of zero on-site Coulomb repulsion ($U=0$), we obtain YSR subgap energy levels that are identical to the ones obtained from the classical spin model. When $\mathrm{\ensuremath{\Delta}}$ is large and $U>0$, the YSR spectra are no longer quasiparticle-like, and the highly degenerate orbital subspaces are split according to their spin, orbital, and number-parity symmetry. We show that $U>0$ activates additional poles in the atomic Green's function, suggesting an alternative explanation for the peak splittings recently observed in scanning tunneling microscopy of orbitally-degenerate impurities in superconductors. We describe optical excitation and absorption of photons by YSR states, showing that many additional optical channels open up in comparison to the nonsuperconducting case. Conversely, the additional dissipation channels imply increased electromagnetic noise due to impurities in superconducting devices.
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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 | 0.001 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".